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LJ/www/build/clmtrackr.js

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[fix] there should be a js file for auduno/clmtrackr
2020-09-27 16:52:10 +00:00
(function (global, factory) {
typeof exports === 'object' && typeof module !== 'undefined' ? module.exports = factory() :
typeof define === 'function' && define.amd ? define(factory) :
(global.clm = factory());
}(this, (function () { 'use strict';
var commonjsGlobal = typeof window !== 'undefined' ? window : typeof global !== 'undefined' ? global : typeof self !== 'undefined' ? self : {};
function createCommonjsModule(fn, module) {
return module = { exports: {} }, fn(module, module.exports), module.exports;
}
var numeric1_2_6 = createCommonjsModule(function (module, exports) {
"use strict";
var numeric = exports;
if(typeof commonjsGlobal !== "undefined") { commonjsGlobal.numeric = numeric; }
numeric.version = "1.2.6";
// 1. Utility functions
numeric.bench = function bench (f,interval) {
var t1,t2,n,i;
if(typeof interval === "undefined") { interval = 15; }
n = 0.5;
t1 = new Date();
while(1) {
n*=2;
for(i=n;i>3;i-=4) { f(); f(); f(); f(); }
while(i>0) { f(); i--; }
t2 = new Date();
if(t2-t1 > interval) break;
}
for(i=n;i>3;i-=4) { f(); f(); f(); f(); }
while(i>0) { f(); i--; }
t2 = new Date();
return 1000*(3*n-1)/(t2-t1);
};
numeric._myIndexOf = (function _myIndexOf(w) {
var n = this.length,k;
for(k=0;k<n;++k) if(this[k]===w) return k;
return -1;
});
numeric.myIndexOf = (Array.prototype.indexOf)?Array.prototype.indexOf:numeric._myIndexOf;
numeric.Function = Function;
numeric.precision = 4;
numeric.largeArray = 50;
numeric.prettyPrint = function prettyPrint(x) {
function fmtnum(x) {
if(x === 0) { return '0'; }
if(isNaN(x)) { return 'NaN'; }
if(x<0) { return '-'+fmtnum(-x); }
if(isFinite(x)) {
var scale = Math.floor(Math.log(x) / Math.log(10));
var normalized = x / Math.pow(10,scale);
var basic = normalized.toPrecision(numeric.precision);
if(parseFloat(basic) === 10) { scale++; normalized = 1; basic = normalized.toPrecision(numeric.precision); }
return parseFloat(basic).toString()+'e'+scale.toString();
}
return 'Infinity';
}
var ret = [];
function foo(x) {
var k;
if(typeof x === "undefined") { ret.push(Array(numeric.precision+8).join(' ')); return false; }
if(typeof x === "string") { ret.push('"'+x+'"'); return false; }
if(typeof x === "boolean") { ret.push(x.toString()); return false; }
if(typeof x === "number") {
var a = fmtnum(x);
var b = x.toPrecision(numeric.precision);
var c = parseFloat(x.toString()).toString();
var d = [a,b,c,parseFloat(b).toString(),parseFloat(c).toString()];
for(k=1;k<d.length;k++) { if(d[k].length < a.length) a = d[k]; }
ret.push(Array(numeric.precision+8-a.length).join(' ')+a);
return false;
}
if(x === null) { ret.push("null"); return false; }
if(typeof x === "function") {
ret.push(x.toString());
var flag = false;
for(k in x) { if(x.hasOwnProperty(k)) {
if(flag) ret.push(',\n');
else ret.push('\n{');
flag = true;
ret.push(k);
ret.push(': \n');
foo(x[k]);
} }
if(flag) ret.push('}\n');
return true;
}
if(x instanceof Array) {
if(x.length > numeric.largeArray) { ret.push('...Large Array...'); return true; }
var flag = false;
ret.push('[');
for(k=0;k<x.length;k++) { if(k>0) { ret.push(','); if(flag) ret.push('\n '); } flag = foo(x[k]); }
ret.push(']');
return true;
}
ret.push('{');
var flag = false;
for(k in x) { if(x.hasOwnProperty(k)) { if(flag) ret.push(',\n'); flag = true; ret.push(k); ret.push(': \n'); foo(x[k]); } }
ret.push('}');
return true;
}
foo(x);
return ret.join('');
};
numeric.parseDate = function parseDate(d) {
function foo(d) {
if(typeof d === 'string') { return Date.parse(d.replace(/-/g,'/')); }
if(!(d instanceof Array)) { throw new Error("parseDate: parameter must be arrays of strings"); }
var ret = [],k;
for(k=0;k<d.length;k++) { ret[k] = foo(d[k]); }
return ret;
}
return foo(d);
};
numeric.parseFloat = function parseFloat_(d) {
function foo(d) {
if(typeof d === 'string') { return parseFloat(d); }
if(!(d instanceof Array)) { throw new Error("parseFloat: parameter must be arrays of strings"); }
var ret = [],k;
for(k=0;k<d.length;k++) { ret[k] = foo(d[k]); }
return ret;
}
return foo(d);
};
numeric.parseCSV = function parseCSV(t) {
var foo = t.split('\n');
var j,k;
var ret = [];
var pat = /(([^'",]*)|('[^']*')|("[^"]*")),/g;
var patnum = /^\s*(([+-]?[0-9]+(\.[0-9]*)?(e[+-]?[0-9]+)?)|([+-]?[0-9]*(\.[0-9]+)?(e[+-]?[0-9]+)?))\s*$/;
var stripper = function(n) { return n.substr(0,n.length-1); };
var count = 0;
for(k=0;k<foo.length;k++) {
var bar = (foo[k]+",").match(pat),baz;
if(bar.length>0) {
ret[count] = [];
for(j=0;j<bar.length;j++) {
baz = stripper(bar[j]);
if(patnum.test(baz)) { ret[count][j] = parseFloat(baz); }
else ret[count][j] = baz;
}
count++;
}
}
return ret;
};
numeric.toCSV = function toCSV(A) {
var s = numeric.dim(A);
var i,j,m,n,row,ret;
m = s[0];
n = s[1];
ret = [];
for(i=0;i<m;i++) {
row = [];
for(j=0;j<m;j++) { row[j] = A[i][j].toString(); }
ret[i] = row.join(', ');
}
return ret.join('\n')+'\n';
};
numeric.getURL = function getURL(url) {
var client = new XMLHttpRequest();
client.open("GET",url,false);
client.send();
return client;
};
numeric.imageURL = function imageURL(img) {
function base64(A) {
var n = A.length, i,x,y,z,p,q,r,s;
var key = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/=";
var ret = "";
for(i=0;i<n;i+=3) {
x = A[i];
y = A[i+1];
z = A[i+2];
p = x >> 2;
q = ((x & 3) << 4) + (y >> 4);
r = ((y & 15) << 2) + (z >> 6);
s = z & 63;
if(i+1>=n) { r = s = 64; }
else if(i+2>=n) { s = 64; }
ret += key.charAt(p) + key.charAt(q) + key.charAt(r) + key.charAt(s);
}
return ret;
}
function crc32Array (a,from,to) {
if(typeof from === "undefined") { from = 0; }
if(typeof to === "undefined") { to = a.length; }
var table = [0x00000000, 0x77073096, 0xEE0E612C, 0x990951BA, 0x076DC419, 0x706AF48F, 0xE963A535, 0x9E6495A3,
0x0EDB8832, 0x79DCB8A4, 0xE0D5E91E, 0x97D2D988, 0x09B64C2B, 0x7EB17CBD, 0xE7B82D07, 0x90BF1D91,
0x1DB71064, 0x6AB020F2, 0xF3B97148, 0x84BE41DE, 0x1ADAD47D, 0x6DDDE4EB, 0xF4D4B551, 0x83D385C7,
0x136C9856, 0x646BA8C0, 0xFD62F97A, 0x8A65C9EC, 0x14015C4F, 0x63066CD9, 0xFA0F3D63, 0x8D080DF5,
0x3B6E20C8, 0x4C69105E, 0xD56041E4, 0xA2677172, 0x3C03E4D1, 0x4B04D447, 0xD20D85FD, 0xA50AB56B,
0x35B5A8FA, 0x42B2986C, 0xDBBBC9D6, 0xACBCF940, 0x32D86CE3, 0x45DF5C75, 0xDCD60DCF, 0xABD13D59,
0x26D930AC, 0x51DE003A, 0xC8D75180, 0xBFD06116, 0x21B4F4B5, 0x56B3C423, 0xCFBA9599, 0xB8BDA50F,
0x2802B89E, 0x5F058808, 0xC60CD9B2, 0xB10BE924, 0x2F6F7C87, 0x58684C11, 0xC1611DAB, 0xB6662D3D,
0x76DC4190, 0x01DB7106, 0x98D220BC, 0xEFD5102A, 0x71B18589, 0x06B6B51F, 0x9FBFE4A5, 0xE8B8D433,
0x7807C9A2, 0x0F00F934, 0x9609A88E, 0xE10E9818, 0x7F6A0DBB, 0x086D3D2D, 0x91646C97, 0xE6635C01,
0x6B6B51F4, 0x1C6C6162, 0x856530D8, 0xF262004E, 0x6C0695ED, 0x1B01A57B, 0x8208F4C1, 0xF50FC457,
0x65B0D9C6, 0x12B7E950, 0x8BBEB8EA, 0xFCB9887C, 0x62DD1DDF, 0x15DA2D49, 0x8CD37CF3, 0xFBD44C65,
0x4DB26158, 0x3AB551CE, 0xA3BC0074, 0xD4BB30E2, 0x4ADFA541, 0x3DD895D7, 0xA4D1C46D, 0xD3D6F4FB,
0x4369E96A, 0x346ED9FC, 0xAD678846, 0xDA60B8D0, 0x44042D73, 0x33031DE5, 0xAA0A4C5F, 0xDD0D7CC9,
0x5005713C, 0x270241AA, 0xBE0B1010, 0xC90C2086, 0x5768B525, 0x206F85B3, 0xB966D409, 0xCE61E49F,
0x5EDEF90E, 0x29D9C998, 0xB0D09822, 0xC7D7A8B4, 0x59B33D17, 0x2EB40D81, 0xB7BD5C3B, 0xC0BA6CAD,
0xEDB88320, 0x9ABFB3B6, 0x03B6E20C, 0x74B1D29A, 0xEAD54739, 0x9DD277AF, 0x04DB2615, 0x73DC1683,
0xE3630B12, 0x94643B84, 0x0D6D6A3E, 0x7A6A5AA8, 0xE40ECF0B, 0x9309FF9D, 0x0A00AE27, 0x7D079EB1,
0xF00F9344, 0x8708A3D2, 0x1E01F268, 0x6906C2FE, 0xF762575D, 0x806567CB, 0x196C3671, 0x6E6B06E7,
0xFED41B76, 0x89D32BE0, 0x10DA7A5A, 0x67DD4ACC, 0xF9B9DF6F, 0x8EBEEFF9, 0x17B7BE43, 0x60B08ED5,
0xD6D6A3E8, 0xA1D1937E, 0x38D8C2C4, 0x4FDFF252, 0xD1BB67F1, 0xA6BC5767, 0x3FB506DD, 0x48B2364B,
0xD80D2BDA, 0xAF0A1B4C, 0x36034AF6, 0x41047A60, 0xDF60EFC3, 0xA867DF55, 0x316E8EEF, 0x4669BE79,
0xCB61B38C, 0xBC66831A, 0x256FD2A0, 0x5268E236, 0xCC0C7795, 0xBB0B4703, 0x220216B9, 0x5505262F,
0xC5BA3BBE, 0xB2BD0B28, 0x2BB45A92, 0x5CB36A04, 0xC2D7FFA7, 0xB5D0CF31, 0x2CD99E8B, 0x5BDEAE1D,
0x9B64C2B0, 0xEC63F226, 0x756AA39C, 0x026D930A, 0x9C0906A9, 0xEB0E363F, 0x72076785, 0x05005713,
0x95BF4A82, 0xE2B87A14, 0x7BB12BAE, 0x0CB61B38, 0x92D28E9B, 0xE5D5BE0D, 0x7CDCEFB7, 0x0BDBDF21,
0x86D3D2D4, 0xF1D4E242, 0x68DDB3F8, 0x1FDA836E, 0x81BE16CD, 0xF6B9265B, 0x6FB077E1, 0x18B74777,
0x88085AE6, 0xFF0F6A70, 0x66063BCA, 0x11010B5C, 0x8F659EFF, 0xF862AE69, 0x616BFFD3, 0x166CCF45,
0xA00AE278, 0xD70DD2EE, 0x4E048354, 0x3903B3C2, 0xA7672661, 0xD06016F7, 0x4969474D, 0x3E6E77DB,
0xAED16A4A, 0xD9D65ADC, 0x40DF0B66, 0x37D83BF0, 0xA9BCAE53, 0xDEBB9EC5, 0x47B2CF7F, 0x30B5FFE9,
0xBDBDF21C, 0xCABAC28A, 0x53B39330, 0x24B4A3A6, 0xBAD03605, 0xCDD70693, 0x54DE5729, 0x23D967BF,
0xB3667A2E, 0xC4614AB8, 0x5D681B02, 0x2A6F2B94, 0xB40BBE37, 0xC30C8EA1, 0x5A05DF1B, 0x2D02EF8D];
var crc = -1, y = 0, n = a.length,i;
for (i = from; i < to; i++) {
y = (crc ^ a[i]) & 0xFF;
crc = (crc >>> 8) ^ table[y];
}
return crc ^ (-1);
}
var h = img[0].length, w = img[0][0].length, s1, s2, next,k,length,a,b,i,j,adler32,crc32;
var stream = [
137, 80, 78, 71, 13, 10, 26, 10, // 0: PNG signature
0,0,0,13, // 8: IHDR Chunk length
73, 72, 68, 82, // 12: "IHDR"
(w >> 24) & 255, (w >> 16) & 255, (w >> 8) & 255, w&255, // 16: Width
(h >> 24) & 255, (h >> 16) & 255, (h >> 8) & 255, h&255, // 20: Height
8, // 24: bit depth
2, // 25: RGB
0, // 26: deflate
0, // 27: no filter
0, // 28: no interlace
-1,-2,-3,-4, // 29: CRC
-5,-6,-7,-8, // 33: IDAT Chunk length
73, 68, 65, 84, // 37: "IDAT"
// RFC 1950 header starts here
8, // 41: RFC1950 CMF
29 // 42: RFC1950 FLG
];
crc32 = crc32Array(stream,12,29);
stream[29] = (crc32>>24)&255;
stream[30] = (crc32>>16)&255;
stream[31] = (crc32>>8)&255;
stream[32] = (crc32)&255;
s1 = 1;
s2 = 0;
for(i=0;i<h;i++) {
if(i<h-1) { stream.push(0); }
else { stream.push(1); }
a = (3*w+1+(i===0))&255; b = ((3*w+1+(i===0))>>8)&255;
stream.push(a); stream.push(b);
stream.push((~a)&255); stream.push((~b)&255);
if(i===0) stream.push(0);
for(j=0;j<w;j++) {
for(k=0;k<3;k++) {
a = img[k][i][j];
if(a>255) a = 255;
else if(a<0) a=0;
else a = Math.round(a);
s1 = (s1 + a )%65521;
s2 = (s2 + s1)%65521;
stream.push(a);
}
}
stream.push(0);
}
adler32 = (s2<<16)+s1;
stream.push((adler32>>24)&255);
stream.push((adler32>>16)&255);
stream.push((adler32>>8)&255);
stream.push((adler32)&255);
length = stream.length - 41;
stream[33] = (length>>24)&255;
stream[34] = (length>>16)&255;
stream[35] = (length>>8)&255;
stream[36] = (length)&255;
crc32 = crc32Array(stream,37);
stream.push((crc32>>24)&255);
stream.push((crc32>>16)&255);
stream.push((crc32>>8)&255);
stream.push((crc32)&255);
stream.push(0);
stream.push(0);
stream.push(0);
stream.push(0);
// a = stream.length;
stream.push(73); // I
stream.push(69); // E
stream.push(78); // N
stream.push(68); // D
stream.push(174); // CRC1
stream.push(66); // CRC2
stream.push(96); // CRC3
stream.push(130); // CRC4
return 'data:image/png;base64,'+base64(stream);
};
// 2. Linear algebra with Arrays.
numeric._dim = function _dim(x) {
var ret = [];
while(typeof x === "object") { ret.push(x.length); x = x[0]; }
return ret;
};
numeric.dim = function dim(x) {
var y,z;
if(typeof x === "object") {
y = x[0];
if(typeof y === "object") {
z = y[0];
if(typeof z === "object") {
return numeric._dim(x);
}
return [x.length,y.length];
}
return [x.length];
}
return [];
};
numeric.mapreduce = function mapreduce(body,init) {
return Function('x','accum','_s','_k',
'if(typeof accum === "undefined") accum = '+init+';\n'+
'if(typeof x === "number") { var xi = x; '+body+'; return accum; }\n'+
'if(typeof _s === "undefined") _s = numeric.dim(x);\n'+
'if(typeof _k === "undefined") _k = 0;\n'+
'var _n = _s[_k];\n'+
'var i,xi;\n'+
'if(_k < _s.length-1) {\n'+
' for(i=_n-1;i>=0;i--) {\n'+
' accum = arguments.callee(x[i],accum,_s,_k+1);\n'+
' }'+
' return accum;\n'+
'}\n'+
'for(i=_n-1;i>=1;i-=2) { \n'+
' xi = x[i];\n'+
' '+body+';\n'+
' xi = x[i-1];\n'+
' '+body+';\n'+
'}\n'+
'if(i === 0) {\n'+
' xi = x[i];\n'+
' '+body+'\n'+
'}\n'+
'return accum;'
);
};
numeric.mapreduce2 = function mapreduce2(body,setup) {
return Function('x',
'var n = x.length;\n'+
'var i,xi;\n'+setup+';\n'+
'for(i=n-1;i!==-1;--i) { \n'+
' xi = x[i];\n'+
' '+body+';\n'+
'}\n'+
'return accum;'
);
};
numeric.same = function same(x,y) {
var i,n;
if(!(x instanceof Array) || !(y instanceof Array)) { return false; }
n = x.length;
if(n !== y.length) { return false; }
for(i=0;i<n;i++) {
if(x[i] === y[i]) { continue; }
if(typeof x[i] === "object") { if(!same(x[i],y[i])) return false; }
else { return false; }
}
return true;
};
numeric.rep = function rep(s,v,k) {
if(typeof k === "undefined") { k=0; }
var n = s[k], ret = Array(n), i;
if(k === s.length-1) {
for(i=n-2;i>=0;i-=2) { ret[i+1] = v; ret[i] = v; }
if(i===-1) { ret[0] = v; }
return ret;
}
for(i=n-1;i>=0;i--) { ret[i] = numeric.rep(s,v,k+1); }
return ret;
};
numeric.dotMMsmall = function dotMMsmall(x,y) {
var i,j,k,p,q,r,ret,foo,bar,woo,i0,k0,p0,r0;
p = x.length; q = y.length; r = y[0].length;
ret = Array(p);
for(i=p-1;i>=0;i--) {
foo = Array(r);
bar = x[i];
for(k=r-1;k>=0;k--) {
woo = bar[q-1]*y[q-1][k];
for(j=q-2;j>=1;j-=2) {
i0 = j-1;
woo += bar[j]*y[j][k] + bar[i0]*y[i0][k];
}
if(j===0) { woo += bar[0]*y[0][k]; }
foo[k] = woo;
}
ret[i] = foo;
}
return ret;
};
numeric._getCol = function _getCol(A,j,x) {
var n = A.length, i;
for(i=n-1;i>0;--i) {
x[i] = A[i][j];
--i;
x[i] = A[i][j];
}
if(i===0) x[0] = A[0][j];
};
numeric.dotMMbig = function dotMMbig(x,y){
var gc = numeric._getCol, p = y.length, v = Array(p);
var m = x.length, n = y[0].length, A = new Array(m), xj;
var VV = numeric.dotVV;
var i,j,k,z;
--p;
--m;
for(i=m;i!==-1;--i) A[i] = Array(n);
--n;
for(i=n;i!==-1;--i) {
gc(y,i,v);
for(j=m;j!==-1;--j) {
z=0;
xj = x[j];
A[j][i] = VV(xj,v);
}
}
return A;
};
numeric.dotMV = function dotMV(x,y) {
var p = x.length, q = y.length,i;
var ret = Array(p), dotVV = numeric.dotVV;
for(i=p-1;i>=0;i--) { ret[i] = dotVV(x[i],y); }
return ret;
};
numeric.dotVM = function dotVM(x,y) {
var i,j,k,p,q,r,ret,foo,bar,woo,i0,k0,p0,r0,s1,s2,s3,baz,accum;
p = x.length; q = y[0].length;
ret = Array(q);
for(k=q-1;k>=0;k--) {
woo = x[p-1]*y[p-1][k];
for(j=p-2;j>=1;j-=2) {
i0 = j-1;
woo += x[j]*y[j][k] + x[i0]*y[i0][k];
}
if(j===0) { woo += x[0]*y[0][k]; }
ret[k] = woo;
}
return ret;
};
numeric.dotVV = function dotVV(x,y) {
var i,n=x.length,i1,ret = x[n-1]*y[n-1];
for(i=n-2;i>=1;i-=2) {
i1 = i-1;
ret += x[i]*y[i] + x[i1]*y[i1];
}
if(i===0) { ret += x[0]*y[0]; }
return ret;
};
numeric.dot = function dot(x,y) {
var d = numeric.dim;
switch(d(x).length*1000+d(y).length) {
case 2002:
if(y.length < 10) return numeric.dotMMsmall(x,y);
else return numeric.dotMMbig(x,y);
case 2001: return numeric.dotMV(x,y);
case 1002: return numeric.dotVM(x,y);
case 1001: return numeric.dotVV(x,y);
case 1000: return numeric.mulVS(x,y);
case 1: return numeric.mulSV(x,y);
case 0: return x*y;
default: throw new Error('numeric.dot only works on vectors and matrices');
}
};
numeric.diag = function diag(d) {
var i,i1,j,n = d.length, A = Array(n), Ai;
for(i=n-1;i>=0;i--) {
Ai = Array(n);
i1 = i+2;
for(j=n-1;j>=i1;j-=2) {
Ai[j] = 0;
Ai[j-1] = 0;
}
if(j>i) { Ai[j] = 0; }
Ai[i] = d[i];
for(j=i-1;j>=1;j-=2) {
Ai[j] = 0;
Ai[j-1] = 0;
}
if(j===0) { Ai[0] = 0; }
A[i] = Ai;
}
return A;
};
numeric.getDiag = function(A) {
var n = Math.min(A.length,A[0].length),i,ret = Array(n);
for(i=n-1;i>=1;--i) {
ret[i] = A[i][i];
--i;
ret[i] = A[i][i];
}
if(i===0) {
ret[0] = A[0][0];
}
return ret;
};
numeric.identity = function identity(n) { return numeric.diag(numeric.rep([n],1)); };
numeric.pointwise = function pointwise(params,body,setup) {
if(typeof setup === "undefined") { setup = ""; }
var fun = [];
var k;
var avec = /\[i\]$/,p,thevec = '';
var haveret = false;
for(k=0;k<params.length;k++) {
if(avec.test(params[k])) {
p = params[k].substring(0,params[k].length-3);
thevec = p;
} else { p = params[k]; }
if(p==='ret') haveret = true;
fun.push(p);
}
fun[params.length] = '_s';
fun[params.length+1] = '_k';
fun[params.length+2] = (
'if(typeof _s === "undefined") _s = numeric.dim('+thevec+');\n'+
'if(typeof _k === "undefined") _k = 0;\n'+
'var _n = _s[_k];\n'+
'var i'+(haveret?'':', ret = Array(_n)')+';\n'+
'if(_k < _s.length-1) {\n'+
' for(i=_n-1;i>=0;i--) ret[i] = arguments.callee('+params.join(',')+',_s,_k+1);\n'+
' return ret;\n'+
'}\n'+
setup+'\n'+
'for(i=_n-1;i!==-1;--i) {\n'+
' '+body+'\n'+
'}\n'+
'return ret;'
);
return Function.apply(null,fun);
};
numeric.pointwise2 = function pointwise2(params,body,setup) {
if(typeof setup === "undefined") { setup = ""; }
var fun = [];
var k;
var avec = /\[i\]$/,p,thevec = '';
var haveret = false;
for(k=0;k<params.length;k++) {
if(avec.test(params[k])) {
p = params[k].substring(0,params[k].length-3);
thevec = p;
} else { p = params[k]; }
if(p==='ret') haveret = true;
fun.push(p);
}
fun[params.length] = (
'var _n = '+thevec+'.length;\n'+
'var i'+(haveret?'':', ret = Array(_n)')+';\n'+
setup+'\n'+
'for(i=_n-1;i!==-1;--i) {\n'+
body+'\n'+
'}\n'+
'return ret;'
);
return Function.apply(null,fun);
};
numeric._biforeach = (function _biforeach(x,y,s,k,f) {
if(k === s.length-1) { f(x,y); return; }
var i,n=s[k];
for(i=n-1;i>=0;i--) { _biforeach(typeof x==="object"?x[i]:x,typeof y==="object"?y[i]:y,s,k+1,f); }
});
numeric._biforeach2 = (function _biforeach2(x,y,s,k,f) {
if(k === s.length-1) { return f(x,y); }
var i,n=s[k],ret = Array(n);
for(i=n-1;i>=0;--i) { ret[i] = _biforeach2(typeof x==="object"?x[i]:x,typeof y==="object"?y[i]:y,s,k+1,f); }
return ret;
});
numeric._foreach = (function _foreach(x,s,k,f) {
if(k === s.length-1) { f(x); return; }
var i,n=s[k];
for(i=n-1;i>=0;i--) { _foreach(x[i],s,k+1,f); }
});
numeric._foreach2 = (function _foreach2(x,s,k,f) {
if(k === s.length-1) { return f(x); }
var i,n=s[k], ret = Array(n);
for(i=n-1;i>=0;i--) { ret[i] = _foreach2(x[i],s,k+1,f); }
return ret;
});
/*numeric.anyV = numeric.mapreduce('if(xi) return true;','false');
numeric.allV = numeric.mapreduce('if(!xi) return false;','true');
numeric.any = function(x) { if(typeof x.length === "undefined") return x; return numeric.anyV(x); }
numeric.all = function(x) { if(typeof x.length === "undefined") return x; return numeric.allV(x); }*/
numeric.ops2 = {
add: '+',
sub: '-',
mul: '*',
div: '/',
mod: '%',
and: '&&',
or: '||',
eq: '===',
neq: '!==',
lt: '<',
gt: '>',
leq: '<=',
geq: '>=',
band: '&',
bor: '|',
bxor: '^',
lshift: '<<',
rshift: '>>',
rrshift: '>>>'
};
numeric.opseq = {
addeq: '+=',
subeq: '-=',
muleq: '*=',
diveq: '/=',
modeq: '%=',
lshifteq: '<<=',
rshifteq: '>>=',
rrshifteq: '>>>=',
bandeq: '&=',
boreq: '|=',
bxoreq: '^='
};
numeric.mathfuns = ['abs','acos','asin','atan','ceil','cos',
'exp','floor','log','round','sin','sqrt','tan',
'isNaN','isFinite'];
numeric.mathfuns2 = ['atan2','pow','max','min'];
numeric.ops1 = {
neg: '-',
not: '!',
bnot: '~',
clone: ''
};
numeric.mapreducers = {
any: ['if(xi) return true;','var accum = false;'],
all: ['if(!xi) return false;','var accum = true;'],
sum: ['accum += xi;','var accum = 0;'],
prod: ['accum *= xi;','var accum = 1;'],
norm2Squared: ['accum += xi*xi;','var accum = 0;'],
norminf: ['accum = max(accum,abs(xi));','var accum = 0, max = Math.max, abs = Math.abs;'],
norm1: ['accum += abs(xi)','var accum = 0, abs = Math.abs;'],
sup: ['accum = max(accum,xi);','var accum = -Infinity, max = Math.max;'],
inf: ['accum = min(accum,xi);','var accum = Infinity, min = Math.min;']
};
(function () {
var i,o;
for(i=0;i<numeric.mathfuns2.length;++i) {
o = numeric.mathfuns2[i];
numeric.ops2[o] = o;
}
for(i in numeric.ops2) {
if(numeric.ops2.hasOwnProperty(i)) {
o = numeric.ops2[i];
var code, codeeq, setup = '';
if(numeric.myIndexOf.call(numeric.mathfuns2,i)!==-1) {
setup = 'var '+o+' = Math.'+o+';\n';
code = function(r,x,y) { return r+' = '+o+'('+x+','+y+')'; };
codeeq = function(x,y) { return x+' = '+o+'('+x+','+y+')'; };
} else {
code = function(r,x,y) { return r+' = '+x+' '+o+' '+y; };
if(numeric.opseq.hasOwnProperty(i+'eq')) {
codeeq = function(x,y) { return x+' '+o+'= '+y; };
} else {
codeeq = function(x,y) { return x+' = '+x+' '+o+' '+y; };
}
}
numeric[i+'VV'] = numeric.pointwise2(['x[i]','y[i]'],code('ret[i]','x[i]','y[i]'),setup);
numeric[i+'SV'] = numeric.pointwise2(['x','y[i]'],code('ret[i]','x','y[i]'),setup);
numeric[i+'VS'] = numeric.pointwise2(['x[i]','y'],code('ret[i]','x[i]','y'),setup);
numeric[i] = Function(
'var n = arguments.length, i, x = arguments[0], y;\n'+
'var VV = numeric.'+i+'VV, VS = numeric.'+i+'VS, SV = numeric.'+i+'SV;\n'+
'var dim = numeric.dim;\n'+
'for(i=1;i!==n;++i) { \n'+
' y = arguments[i];\n'+
' if(typeof x === "object") {\n'+
' if(typeof y === "object") x = numeric._biforeach2(x,y,dim(x),0,VV);\n'+
' else x = numeric._biforeach2(x,y,dim(x),0,VS);\n'+
' } else if(typeof y === "object") x = numeric._biforeach2(x,y,dim(y),0,SV);\n'+
' else '+codeeq('x','y')+'\n'+
'}\nreturn x;\n');
numeric[o] = numeric[i];
numeric[i+'eqV'] = numeric.pointwise2(['ret[i]','x[i]'], codeeq('ret[i]','x[i]'),setup);
numeric[i+'eqS'] = numeric.pointwise2(['ret[i]','x'], codeeq('ret[i]','x'),setup);
numeric[i+'eq'] = Function(
'var n = arguments.length, i, x = arguments[0], y;\n'+
'var V = numeric.'+i+'eqV, S = numeric.'+i+'eqS\n'+
'var s = numeric.dim(x);\n'+
'for(i=1;i!==n;++i) { \n'+
' y = arguments[i];\n'+
' if(typeof y === "object") numeric._biforeach(x,y,s,0,V);\n'+
' else numeric._biforeach(x,y,s,0,S);\n'+
'}\nreturn x;\n');
}
}
for(i=0;i<numeric.mathfuns2.length;++i) {
o = numeric.mathfuns2[i];
delete numeric.ops2[o];
}
for(i=0;i<numeric.mathfuns.length;++i) {
o = numeric.mathfuns[i];
numeric.ops1[o] = o;
}
for(i in numeric.ops1) {
if(numeric.ops1.hasOwnProperty(i)) {
setup = '';
o = numeric.ops1[i];
if(numeric.myIndexOf.call(numeric.mathfuns,i)!==-1) {
if(Math.hasOwnProperty(o)) setup = 'var '+o+' = Math.'+o+';\n';
}
numeric[i+'eqV'] = numeric.pointwise2(['ret[i]'],'ret[i] = '+o+'(ret[i]);',setup);
numeric[i+'eq'] = Function('x',
'if(typeof x !== "object") return '+o+'x\n'+
'var i;\n'+
'var V = numeric.'+i+'eqV;\n'+
'var s = numeric.dim(x);\n'+
'numeric._foreach(x,s,0,V);\n'+
'return x;\n');
numeric[i+'V'] = numeric.pointwise2(['x[i]'],'ret[i] = '+o+'(x[i]);',setup);
numeric[i] = Function('x',
'if(typeof x !== "object") return '+o+'(x)\n'+
'var i;\n'+
'var V = numeric.'+i+'V;\n'+
'var s = numeric.dim(x);\n'+
'return numeric._foreach2(x,s,0,V);\n');
}
}
for(i=0;i<numeric.mathfuns.length;++i) {
o = numeric.mathfuns[i];
delete numeric.ops1[o];
}
for(i in numeric.mapreducers) {
if(numeric.mapreducers.hasOwnProperty(i)) {
o = numeric.mapreducers[i];
numeric[i+'V'] = numeric.mapreduce2(o[0],o[1]);
numeric[i] = Function('x','s','k',
o[1]+
'if(typeof x !== "object") {'+
' xi = x;\n'+
o[0]+';\n'+
' return accum;\n'+
'}'+
'if(typeof s === "undefined") s = numeric.dim(x);\n'+
'if(typeof k === "undefined") k = 0;\n'+
'if(k === s.length-1) return numeric.'+i+'V(x);\n'+
'var xi;\n'+
'var n = x.length, i;\n'+
'for(i=n-1;i!==-1;--i) {\n'+
' xi = arguments.callee(x[i]);\n'+
o[0]+';\n'+
'}\n'+
'return accum;\n');
}
}
}());
numeric.truncVV = numeric.pointwise(['x[i]','y[i]'],'ret[i] = round(x[i]/y[i])*y[i];','var round = Math.round;');
numeric.truncVS = numeric.pointwise(['x[i]','y'],'ret[i] = round(x[i]/y)*y;','var round = Math.round;');
numeric.truncSV = numeric.pointwise(['x','y[i]'],'ret[i] = round(x/y[i])*y[i];','var round = Math.round;');
numeric.trunc = function trunc(x,y) {
if(typeof x === "object") {
if(typeof y === "object") return numeric.truncVV(x,y);
return numeric.truncVS(x,y);
}
if (typeof y === "object") return numeric.truncSV(x,y);
return Math.round(x/y)*y;
};
numeric.inv = function inv(x) {
var s = numeric.dim(x), abs = Math.abs, m = s[0], n = s[1];
var A = numeric.clone(x), Ai, Aj;
var I = numeric.identity(m), Ii, Ij;
var i,j,k,x;
for(j=0;j<n;++j) {
var i0 = -1;
var v0 = -1;
for(i=j;i!==m;++i) { k = abs(A[i][j]); if(k>v0) { i0 = i; v0 = k; } }
Aj = A[i0]; A[i0] = A[j]; A[j] = Aj;
Ij = I[i0]; I[i0] = I[j]; I[j] = Ij;
x = Aj[j];
for(k=j;k!==n;++k) Aj[k] /= x;
for(k=n-1;k!==-1;--k) Ij[k] /= x;
for(i=m-1;i!==-1;--i) {
if(i!==j) {
Ai = A[i];
Ii = I[i];
x = Ai[j];
for(k=j+1;k!==n;++k) Ai[k] -= Aj[k]*x;
for(k=n-1;k>0;--k) { Ii[k] -= Ij[k]*x; --k; Ii[k] -= Ij[k]*x; }
if(k===0) Ii[0] -= Ij[0]*x;
}
}
}
return I;
};
numeric.det = function det(x) {
var s = numeric.dim(x);
if(s.length !== 2 || s[0] !== s[1]) { throw new Error('numeric: det() only works on square matrices'); }
var n = s[0], ret = 1,i,j,k,A = numeric.clone(x),Aj,Ai,alpha,temp,k1,k2,k3;
for(j=0;j<n-1;j++) {
k=j;
for(i=j+1;i<n;i++) { if(Math.abs(A[i][j]) > Math.abs(A[k][j])) { k = i; } }
if(k !== j) {
temp = A[k]; A[k] = A[j]; A[j] = temp;
ret *= -1;
}
Aj = A[j];
for(i=j+1;i<n;i++) {
Ai = A[i];
alpha = Ai[j]/Aj[j];
for(k=j+1;k<n-1;k+=2) {
k1 = k+1;
Ai[k] -= Aj[k]*alpha;
Ai[k1] -= Aj[k1]*alpha;
}
if(k!==n) { Ai[k] -= Aj[k]*alpha; }
}
if(Aj[j] === 0) { return 0; }
ret *= Aj[j];
}
return ret*A[j][j];
};
numeric.transpose = function transpose(x) {
var i,j,m = x.length,n = x[0].length, ret=Array(n),A0,A1,Bj;
for(j=0;j<n;j++) ret[j] = Array(m);
for(i=m-1;i>=1;i-=2) {
A1 = x[i];
A0 = x[i-1];
for(j=n-1;j>=1;--j) {
Bj = ret[j]; Bj[i] = A1[j]; Bj[i-1] = A0[j];
--j;
Bj = ret[j]; Bj[i] = A1[j]; Bj[i-1] = A0[j];
}
if(j===0) {
Bj = ret[0]; Bj[i] = A1[0]; Bj[i-1] = A0[0];
}
}
if(i===0) {
A0 = x[0];
for(j=n-1;j>=1;--j) {
ret[j][0] = A0[j];
--j;
ret[j][0] = A0[j];
}
if(j===0) { ret[0][0] = A0[0]; }
}
return ret;
};
numeric.negtranspose = function negtranspose(x) {
var i,j,m = x.length,n = x[0].length, ret=Array(n),A0,A1,Bj;
for(j=0;j<n;j++) ret[j] = Array(m);
for(i=m-1;i>=1;i-=2) {
A1 = x[i];
A0 = x[i-1];
for(j=n-1;j>=1;--j) {
Bj = ret[j]; Bj[i] = -A1[j]; Bj[i-1] = -A0[j];
--j;
Bj = ret[j]; Bj[i] = -A1[j]; Bj[i-1] = -A0[j];
}
if(j===0) {
Bj = ret[0]; Bj[i] = -A1[0]; Bj[i-1] = -A0[0];
}
}
if(i===0) {
A0 = x[0];
for(j=n-1;j>=1;--j) {
ret[j][0] = -A0[j];
--j;
ret[j][0] = -A0[j];
}
if(j===0) { ret[0][0] = -A0[0]; }
}
return ret;
};
numeric._random = function _random(s,k) {
var i,n=s[k],ret=Array(n), rnd;
if(k === s.length-1) {
rnd = Math.random;
for(i=n-1;i>=1;i-=2) {
ret[i] = rnd();
ret[i-1] = rnd();
}
if(i===0) { ret[0] = rnd(); }
return ret;
}
for(i=n-1;i>=0;i--) ret[i] = _random(s,k+1);
return ret;
};
numeric.random = function random(s) { return numeric._random(s,0); };
numeric.norm2 = function norm2(x) { return Math.sqrt(numeric.norm2Squared(x)); };
numeric.linspace = function linspace(a,b,n) {
if(typeof n === "undefined") n = Math.max(Math.round(b-a)+1,1);
if(n<2) { return n===1?[a]:[]; }
var i,ret = Array(n);
n--;
for(i=n;i>=0;i--) { ret[i] = (i*b+(n-i)*a)/n; }
return ret;
};
numeric.getBlock = function getBlock(x,from,to) {
var s = numeric.dim(x);
function foo(x,k) {
var i,a = from[k], n = to[k]-a, ret = Array(n);
if(k === s.length-1) {
for(i=n;i>=0;i--) { ret[i] = x[i+a]; }
return ret;
}
for(i=n;i>=0;i--) { ret[i] = foo(x[i+a],k+1); }
return ret;
}
return foo(x,0);
};
numeric.setBlock = function setBlock(x,from,to,B) {
var s = numeric.dim(x);
function foo(x,y,k) {
var i,a = from[k], n = to[k]-a;
if(k === s.length-1) { for(i=n;i>=0;i--) { x[i+a] = y[i]; } }
for(i=n;i>=0;i--) { foo(x[i+a],y[i],k+1); }
}
foo(x,B,0);
return x;
};
numeric.getRange = function getRange(A,I,J) {
var m = I.length, n = J.length;
var i,j;
var B = Array(m), Bi, AI;
for(i=m-1;i!==-1;--i) {
B[i] = Array(n);
Bi = B[i];
AI = A[I[i]];
for(j=n-1;j!==-1;--j) Bi[j] = AI[J[j]];
}
return B;
};
numeric.blockMatrix = function blockMatrix(X) {
var s = numeric.dim(X);
if(s.length<4) return numeric.blockMatrix([X]);
var m=s[0],n=s[1],M,N,i,j,Xij;
M = 0; N = 0;
for(i=0;i<m;++i) M+=X[i][0].length;
for(j=0;j<n;++j) N+=X[0][j][0].length;
var Z = Array(M);
for(i=0;i<M;++i) Z[i] = Array(N);
var I=0,J,ZI,k,l,Xijk;
for(i=0;i<m;++i) {
J=N;
for(j=n-1;j!==-1;--j) {
Xij = X[i][j];
J -= Xij[0].length;
for(k=Xij.length-1;k!==-1;--k) {
Xijk = Xij[k];
ZI = Z[I+k];
for(l = Xijk.length-1;l!==-1;--l) ZI[J+l] = Xijk[l];
}
}
I += X[i][0].length;
}
return Z;
};
numeric.tensor = function tensor(x,y) {
if(typeof x === "number" || typeof y === "number") return numeric.mul(x,y);
var s1 = numeric.dim(x), s2 = numeric.dim(y);
if(s1.length !== 1 || s2.length !== 1) {
throw new Error('numeric: tensor product is only defined for vectors');
}
var m = s1[0], n = s2[0], A = Array(m), Ai, i,j,xi;
for(i=m-1;i>=0;i--) {
Ai = Array(n);
xi = x[i];
for(j=n-1;j>=3;--j) {
Ai[j] = xi * y[j];
--j;
Ai[j] = xi * y[j];
--j;
Ai[j] = xi * y[j];
--j;
Ai[j] = xi * y[j];
}
while(j>=0) { Ai[j] = xi * y[j]; --j; }
A[i] = Ai;
}
return A;
};
// 3. The Tensor type T
numeric.T = function T(x,y) { this.x = x; this.y = y; };
numeric.t = function t(x,y) { return new numeric.T(x,y); };
numeric.Tbinop = function Tbinop(rr,rc,cr,cc,setup) {
var io = numeric.indexOf;
if(typeof setup !== "string") {
var k;
setup = '';
for(k in numeric) {
if(numeric.hasOwnProperty(k) && (rr.indexOf(k)>=0 || rc.indexOf(k)>=0 || cr.indexOf(k)>=0 || cc.indexOf(k)>=0) && k.length>1) {
setup += 'var '+k+' = numeric.'+k+';\n';
}
}
}
return Function(['y'],
'var x = this;\n'+
'if(!(y instanceof numeric.T)) { y = new numeric.T(y); }\n'+
setup+'\n'+
'if(x.y) {'+
' if(y.y) {'+
' return new numeric.T('+cc+');\n'+
' }\n'+
' return new numeric.T('+cr+');\n'+
'}\n'+
'if(y.y) {\n'+
' return new numeric.T('+rc+');\n'+
'}\n'+
'return new numeric.T('+rr+');\n'
);
};
numeric.T.prototype.add = numeric.Tbinop(
'add(x.x,y.x)',
'add(x.x,y.x),y.y',
'add(x.x,y.x),x.y',
'add(x.x,y.x),add(x.y,y.y)');
numeric.T.prototype.sub = numeric.Tbinop(
'sub(x.x,y.x)',
'sub(x.x,y.x),neg(y.y)',
'sub(x.x,y.x),x.y',
'sub(x.x,y.x),sub(x.y,y.y)');
numeric.T.prototype.mul = numeric.Tbinop(
'mul(x.x,y.x)',
'mul(x.x,y.x),mul(x.x,y.y)',
'mul(x.x,y.x),mul(x.y,y.x)',
'sub(mul(x.x,y.x),mul(x.y,y.y)),add(mul(x.x,y.y),mul(x.y,y.x))');
numeric.T.prototype.reciprocal = function reciprocal() {
var mul = numeric.mul, div = numeric.div;
if(this.y) {
var d = numeric.add(mul(this.x,this.x),mul(this.y,this.y));
return new numeric.T(div(this.x,d),div(numeric.neg(this.y),d));
}
return new T(div(1,this.x));
};
numeric.T.prototype.div = function div(y) {
if(!(y instanceof numeric.T)) y = new numeric.T(y);
if(y.y) { return this.mul(y.reciprocal()); }
var div = numeric.div;
if(this.y) { return new numeric.T(div(this.x,y.x),div(this.y,y.x)); }
return new numeric.T(div(this.x,y.x));
};
numeric.T.prototype.dot = numeric.Tbinop(
'dot(x.x,y.x)',
'dot(x.x,y.x),dot(x.x,y.y)',
'dot(x.x,y.x),dot(x.y,y.x)',
'sub(dot(x.x,y.x),dot(x.y,y.y)),add(dot(x.x,y.y),dot(x.y,y.x))'
);
numeric.T.prototype.transpose = function transpose() {
var t = numeric.transpose, x = this.x, y = this.y;
if(y) { return new numeric.T(t(x),t(y)); }
return new numeric.T(t(x));
};
numeric.T.prototype.transjugate = function transjugate() {
var t = numeric.transpose, x = this.x, y = this.y;
if(y) { return new numeric.T(t(x),numeric.negtranspose(y)); }
return new numeric.T(t(x));
};
numeric.Tunop = function Tunop(r,c,s) {
if(typeof s !== "string") { s = ''; }
return Function(
'var x = this;\n'+
s+'\n'+
'if(x.y) {'+
' '+c+';\n'+
'}\n'+
r+';\n'
);
};
numeric.T.prototype.exp = numeric.Tunop(
'return new numeric.T(ex)',
'return new numeric.T(mul(cos(x.y),ex),mul(sin(x.y),ex))',
'var ex = numeric.exp(x.x), cos = numeric.cos, sin = numeric.sin, mul = numeric.mul;');
numeric.T.prototype.conj = numeric.Tunop(
'return new numeric.T(x.x);',
'return new numeric.T(x.x,numeric.neg(x.y));');
numeric.T.prototype.neg = numeric.Tunop(
'return new numeric.T(neg(x.x));',
'return new numeric.T(neg(x.x),neg(x.y));',
'var neg = numeric.neg;');
numeric.T.prototype.sin = numeric.Tunop(
'return new numeric.T(numeric.sin(x.x))',
'return x.exp().sub(x.neg().exp()).div(new numeric.T(0,2));');
numeric.T.prototype.cos = numeric.Tunop(
'return new numeric.T(numeric.cos(x.x))',
'return x.exp().add(x.neg().exp()).div(2);');
numeric.T.prototype.abs = numeric.Tunop(
'return new numeric.T(numeric.abs(x.x));',
'return new numeric.T(numeric.sqrt(numeric.add(mul(x.x,x.x),mul(x.y,x.y))));',
'var mul = numeric.mul;');
numeric.T.prototype.log = numeric.Tunop(
'return new numeric.T(numeric.log(x.x));',
'var theta = new numeric.T(numeric.atan2(x.y,x.x)), r = x.abs();\n'+
'return new numeric.T(numeric.log(r.x),theta.x);');
numeric.T.prototype.norm2 = numeric.Tunop(
'return numeric.norm2(x.x);',
'var f = numeric.norm2Squared;\n'+
'return Math.sqrt(f(x.x)+f(x.y));');
numeric.T.prototype.inv = function inv() {
var A = this;
if(typeof A.y === "undefined") { return new numeric.T(numeric.inv(A.x)); }
var n = A.x.length, i, j, k;
var Rx = numeric.identity(n),Ry = numeric.rep([n,n],0);
var Ax = numeric.clone(A.x), Ay = numeric.clone(A.y);
var Aix, Aiy, Ajx, Ajy, Rix, Riy, Rjx, Rjy;
var i,j,k,d,d1,ax,ay,bx,by,temp;
for(i=0;i<n;i++) {
ax = Ax[i][i]; ay = Ay[i][i];
d = ax*ax+ay*ay;
k = i;
for(j=i+1;j<n;j++) {
ax = Ax[j][i]; ay = Ay[j][i];
d1 = ax*ax+ay*ay;
if(d1 > d) { k=j; d = d1; }
}
if(k!==i) {
temp = Ax[i]; Ax[i] = Ax[k]; Ax[k] = temp;
temp = Ay[i]; Ay[i] = Ay[k]; Ay[k] = temp;
temp = Rx[i]; Rx[i] = Rx[k]; Rx[k] = temp;
temp = Ry[i]; Ry[i] = Ry[k]; Ry[k] = temp;
}
Aix = Ax[i]; Aiy = Ay[i];
Rix = Rx[i]; Riy = Ry[i];
ax = Aix[i]; ay = Aiy[i];
for(j=i+1;j<n;j++) {
bx = Aix[j]; by = Aiy[j];
Aix[j] = (bx*ax+by*ay)/d;
Aiy[j] = (by*ax-bx*ay)/d;
}
for(j=0;j<n;j++) {
bx = Rix[j]; by = Riy[j];
Rix[j] = (bx*ax+by*ay)/d;
Riy[j] = (by*ax-bx*ay)/d;
}
for(j=i+1;j<n;j++) {
Ajx = Ax[j]; Ajy = Ay[j];
Rjx = Rx[j]; Rjy = Ry[j];
ax = Ajx[i]; ay = Ajy[i];
for(k=i+1;k<n;k++) {
bx = Aix[k]; by = Aiy[k];
Ajx[k] -= bx*ax-by*ay;
Ajy[k] -= by*ax+bx*ay;
}
for(k=0;k<n;k++) {
bx = Rix[k]; by = Riy[k];
Rjx[k] -= bx*ax-by*ay;
Rjy[k] -= by*ax+bx*ay;
}
}
}
for(i=n-1;i>0;i--) {
Rix = Rx[i]; Riy = Ry[i];
for(j=i-1;j>=0;j--) {
Rjx = Rx[j]; Rjy = Ry[j];
ax = Ax[j][i]; ay = Ay[j][i];
for(k=n-1;k>=0;k--) {
bx = Rix[k]; by = Riy[k];
Rjx[k] -= ax*bx - ay*by;
Rjy[k] -= ax*by + ay*bx;
}
}
}
return new numeric.T(Rx,Ry);
};
numeric.T.prototype.get = function get(i) {
var x = this.x, y = this.y, k = 0, ik, n = i.length;
if(y) {
while(k<n) {
ik = i[k];
x = x[ik];
y = y[ik];
k++;
}
return new numeric.T(x,y);
}
while(k<n) {
ik = i[k];
x = x[ik];
k++;
}
return new numeric.T(x);
};
numeric.T.prototype.set = function set(i,v) {
var x = this.x, y = this.y, k = 0, ik, n = i.length, vx = v.x, vy = v.y;
if(n===0) {
if(vy) { this.y = vy; }
else if(y) { this.y = undefined; }
this.x = x;
return this;
}
if(vy) {
if(y) { /* ok */ }
else {
y = numeric.rep(numeric.dim(x),0);
this.y = y;
}
while(k<n-1) {
ik = i[k];
x = x[ik];
y = y[ik];
k++;
}
ik = i[k];
x[ik] = vx;
y[ik] = vy;
return this;
}
if(y) {
while(k<n-1) {
ik = i[k];
x = x[ik];
y = y[ik];
k++;
}
ik = i[k];
x[ik] = vx;
if(vx instanceof Array) y[ik] = numeric.rep(numeric.dim(vx),0);
else y[ik] = 0;
return this;
}
while(k<n-1) {
ik = i[k];
x = x[ik];
k++;
}
ik = i[k];
x[ik] = vx;
return this;
};
numeric.T.prototype.getRows = function getRows(i0,i1) {
var n = i1-i0+1, j;
var rx = Array(n), ry, x = this.x, y = this.y;
for(j=i0;j<=i1;j++) { rx[j-i0] = x[j]; }
if(y) {
ry = Array(n);
for(j=i0;j<=i1;j++) { ry[j-i0] = y[j]; }
return new numeric.T(rx,ry);
}
return new numeric.T(rx);
};
numeric.T.prototype.setRows = function setRows(i0,i1,A) {
var j;
var rx = this.x, ry = this.y, x = A.x, y = A.y;
for(j=i0;j<=i1;j++) { rx[j] = x[j-i0]; }
if(y) {
if(!ry) { ry = numeric.rep(numeric.dim(rx),0); this.y = ry; }
for(j=i0;j<=i1;j++) { ry[j] = y[j-i0]; }
} else if(ry) {
for(j=i0;j<=i1;j++) { ry[j] = numeric.rep([x[j-i0].length],0); }
}
return this;
};
numeric.T.prototype.getRow = function getRow(k) {
var x = this.x, y = this.y;
if(y) { return new numeric.T(x[k],y[k]); }
return new numeric.T(x[k]);
};
numeric.T.prototype.setRow = function setRow(i,v) {
var rx = this.x, ry = this.y, x = v.x, y = v.y;
rx[i] = x;
if(y) {
if(!ry) { ry = numeric.rep(numeric.dim(rx),0); this.y = ry; }
ry[i] = y;
} else if(ry) {
ry = numeric.rep([x.length],0);
}
return this;
};
numeric.T.prototype.getBlock = function getBlock(from,to) {
var x = this.x, y = this.y, b = numeric.getBlock;
if(y) { return new numeric.T(b(x,from,to),b(y,from,to)); }
return new numeric.T(b(x,from,to));
};
numeric.T.prototype.setBlock = function setBlock(from,to,A) {
if(!(A instanceof numeric.T)) A = new numeric.T(A);
var x = this.x, y = this.y, b = numeric.setBlock, Ax = A.x, Ay = A.y;
if(Ay) {
if(!y) { this.y = numeric.rep(numeric.dim(this),0); y = this.y; }
b(x,from,to,Ax);
b(y,from,to,Ay);
return this;
}
b(x,from,to,Ax);
if(y) b(y,from,to,numeric.rep(numeric.dim(Ax),0));
};
numeric.T.rep = function rep(s,v) {
var T = numeric.T;
if(!(v instanceof T)) v = new T(v);
var x = v.x, y = v.y, r = numeric.rep;
if(y) return new T(r(s,x),r(s,y));
return new T(r(s,x));
};
numeric.T.diag = function diag(d) {
if(!(d instanceof numeric.T)) d = new numeric.T(d);
var x = d.x, y = d.y, diag = numeric.diag;
if(y) return new numeric.T(diag(x),diag(y));
return new numeric.T(diag(x));
};
numeric.T.eig = function eig() {
if(this.y) { throw new Error('eig: not implemented for complex matrices.'); }
return numeric.eig(this.x);
};
numeric.T.identity = function identity(n) { return new numeric.T(numeric.identity(n)); };
numeric.T.prototype.getDiag = function getDiag() {
var n = numeric;
var x = this.x, y = this.y;
if(y) { return new n.T(n.getDiag(x),n.getDiag(y)); }
return new n.T(n.getDiag(x));
};
// 4. Eigenvalues of real matrices
numeric.house = function house(x) {
var v = numeric.clone(x);
var s = x[0] >= 0 ? 1 : -1;
var alpha = s*numeric.norm2(x);
v[0] += alpha;
var foo = numeric.norm2(v);
if(foo === 0) { /* this should not happen */ throw new Error('eig: internal error'); }
return numeric.div(v,foo);
};
numeric.toUpperHessenberg = function toUpperHessenberg(me) {
var s = numeric.dim(me);
if(s.length !== 2 || s[0] !== s[1]) { throw new Error('numeric: toUpperHessenberg() only works on square matrices'); }
var m = s[0], i,j,k,x,v,A = numeric.clone(me),B,C,Ai,Ci,Q = numeric.identity(m),Qi;
for(j=0;j<m-2;j++) {
x = Array(m-j-1);
for(i=j+1;i<m;i++) { x[i-j-1] = A[i][j]; }
if(numeric.norm2(x)>0) {
v = numeric.house(x);
B = numeric.getBlock(A,[j+1,j],[m-1,m-1]);
C = numeric.tensor(v,numeric.dot(v,B));
for(i=j+1;i<m;i++) { Ai = A[i]; Ci = C[i-j-1]; for(k=j;k<m;k++) Ai[k] -= 2*Ci[k-j]; }
B = numeric.getBlock(A,[0,j+1],[m-1,m-1]);
C = numeric.tensor(numeric.dot(B,v),v);
for(i=0;i<m;i++) { Ai = A[i]; Ci = C[i]; for(k=j+1;k<m;k++) Ai[k] -= 2*Ci[k-j-1]; }
B = Array(m-j-1);
for(i=j+1;i<m;i++) B[i-j-1] = Q[i];
C = numeric.tensor(v,numeric.dot(v,B));
for(i=j+1;i<m;i++) { Qi = Q[i]; Ci = C[i-j-1]; for(k=0;k<m;k++) Qi[k] -= 2*Ci[k]; }
}
}
return {H:A, Q:Q};
};
numeric.epsilon = 2.220446049250313e-16;
numeric.QRFrancis = function(H,maxiter) {
if(typeof maxiter === "undefined") { maxiter = 10000; }
H = numeric.clone(H);
var H0 = numeric.clone(H);
var s = numeric.dim(H),m=s[0],x,v,a,b,c,d,det,tr, Hloc, Q = numeric.identity(m), Qi, Hi, B, C, Ci,i,j,k,iter;
if(m<3) { return {Q:Q, B:[ [0,m-1] ]}; }
var epsilon = numeric.epsilon;
for(iter=0;iter<maxiter;iter++) {
for(j=0;j<m-1;j++) {
if(Math.abs(H[j+1][j]) < epsilon*(Math.abs(H[j][j])+Math.abs(H[j+1][j+1]))) {
var QH1 = numeric.QRFrancis(numeric.getBlock(H,[0,0],[j,j]),maxiter);
var QH2 = numeric.QRFrancis(numeric.getBlock(H,[j+1,j+1],[m-1,m-1]),maxiter);
B = Array(j+1);
for(i=0;i<=j;i++) { B[i] = Q[i]; }
C = numeric.dot(QH1.Q,B);
for(i=0;i<=j;i++) { Q[i] = C[i]; }
B = Array(m-j-1);
for(i=j+1;i<m;i++) { B[i-j-1] = Q[i]; }
C = numeric.dot(QH2.Q,B);
for(i=j+1;i<m;i++) { Q[i] = C[i-j-1]; }
return {Q:Q,B:QH1.B.concat(numeric.add(QH2.B,j+1))};
}
}
a = H[m-2][m-2]; b = H[m-2][m-1];
c = H[m-1][m-2]; d = H[m-1][m-1];
tr = a+d;
det = (a*d-b*c);
Hloc = numeric.getBlock(H, [0,0], [2,2]);
if(tr*tr>=4*det) {
var s1,s2;
s1 = 0.5*(tr+Math.sqrt(tr*tr-4*det));
s2 = 0.5*(tr-Math.sqrt(tr*tr-4*det));
Hloc = numeric.add(numeric.sub(numeric.dot(Hloc,Hloc),
numeric.mul(Hloc,s1+s2)),
numeric.diag(numeric.rep([3],s1*s2)));
} else {
Hloc = numeric.add(numeric.sub(numeric.dot(Hloc,Hloc),
numeric.mul(Hloc,tr)),
numeric.diag(numeric.rep([3],det)));
}
x = [Hloc[0][0],Hloc[1][0],Hloc[2][0]];
v = numeric.house(x);
B = [H[0],H[1],H[2]];
C = numeric.tensor(v,numeric.dot(v,B));
for(i=0;i<3;i++) { Hi = H[i]; Ci = C[i]; for(k=0;k<m;k++) Hi[k] -= 2*Ci[k]; }
B = numeric.getBlock(H, [0,0],[m-1,2]);
C = numeric.tensor(numeric.dot(B,v),v);
for(i=0;i<m;i++) { Hi = H[i]; Ci = C[i]; for(k=0;k<3;k++) Hi[k] -= 2*Ci[k]; }
B = [Q[0],Q[1],Q[2]];
C = numeric.tensor(v,numeric.dot(v,B));
for(i=0;i<3;i++) { Qi = Q[i]; Ci = C[i]; for(k=0;k<m;k++) Qi[k] -= 2*Ci[k]; }
var J;
for(j=0;j<m-2;j++) {
for(k=j;k<=j+1;k++) {
if(Math.abs(H[k+1][k]) < epsilon*(Math.abs(H[k][k])+Math.abs(H[k+1][k+1]))) {
var QH1 = numeric.QRFrancis(numeric.getBlock(H,[0,0],[k,k]),maxiter);
var QH2 = numeric.QRFrancis(numeric.getBlock(H,[k+1,k+1],[m-1,m-1]),maxiter);
B = Array(k+1);
for(i=0;i<=k;i++) { B[i] = Q[i]; }
C = numeric.dot(QH1.Q,B);
for(i=0;i<=k;i++) { Q[i] = C[i]; }
B = Array(m-k-1);
for(i=k+1;i<m;i++) { B[i-k-1] = Q[i]; }
C = numeric.dot(QH2.Q,B);
for(i=k+1;i<m;i++) { Q[i] = C[i-k-1]; }
return {Q:Q,B:QH1.B.concat(numeric.add(QH2.B,k+1))};
}
}
J = Math.min(m-1,j+3);
x = Array(J-j);
for(i=j+1;i<=J;i++) { x[i-j-1] = H[i][j]; }
v = numeric.house(x);
B = numeric.getBlock(H, [j+1,j],[J,m-1]);
C = numeric.tensor(v,numeric.dot(v,B));
for(i=j+1;i<=J;i++) { Hi = H[i]; Ci = C[i-j-1]; for(k=j;k<m;k++) Hi[k] -= 2*Ci[k-j]; }
B = numeric.getBlock(H, [0,j+1],[m-1,J]);
C = numeric.tensor(numeric.dot(B,v),v);
for(i=0;i<m;i++) { Hi = H[i]; Ci = C[i]; for(k=j+1;k<=J;k++) Hi[k] -= 2*Ci[k-j-1]; }
B = Array(J-j);
for(i=j+1;i<=J;i++) B[i-j-1] = Q[i];
C = numeric.tensor(v,numeric.dot(v,B));
for(i=j+1;i<=J;i++) { Qi = Q[i]; Ci = C[i-j-1]; for(k=0;k<m;k++) Qi[k] -= 2*Ci[k]; }
}
}
throw new Error('numeric: eigenvalue iteration does not converge -- increase maxiter?');
};
numeric.eig = function eig(A,maxiter) {
var QH = numeric.toUpperHessenberg(A);
var QB = numeric.QRFrancis(QH.H,maxiter);
var T = numeric.T;
var n = A.length,i,k,flag = false,B = QB.B,H = numeric.dot(QB.Q,numeric.dot(QH.H,numeric.transpose(QB.Q)));
var Q = new T(numeric.dot(QB.Q,QH.Q)),Q0;
var m = B.length,j;
var a,b,c,d,p1,p2,disc,x,y,p,q,n1,n2;
var sqrt = Math.sqrt;
for(k=0;k<m;k++) {
i = B[k][0];
if(i === B[k][1]) {
// nothing
} else {
j = i+1;
a = H[i][i];
b = H[i][j];
c = H[j][i];
d = H[j][j];
if(b === 0 && c === 0) continue;
p1 = -a-d;
p2 = a*d-b*c;
disc = p1*p1-4*p2;
if(disc>=0) {
if(p1<0) x = -0.5*(p1-sqrt(disc));
else x = -0.5*(p1+sqrt(disc));
n1 = (a-x)*(a-x)+b*b;
n2 = c*c+(d-x)*(d-x);
if(n1>n2) {
n1 = sqrt(n1);
p = (a-x)/n1;
q = b/n1;
} else {
n2 = sqrt(n2);
p = c/n2;
q = (d-x)/n2;
}
Q0 = new T([[q,-p],[p,q]]);
Q.setRows(i,j,Q0.dot(Q.getRows(i,j)));
} else {
x = -0.5*p1;
y = 0.5*sqrt(-disc);
n1 = (a-x)*(a-x)+b*b;
n2 = c*c+(d-x)*(d-x);
if(n1>n2) {
n1 = sqrt(n1+y*y);
p = (a-x)/n1;
q = b/n1;
x = 0;
y /= n1;
} else {
n2 = sqrt(n2+y*y);
p = c/n2;
q = (d-x)/n2;
x = y/n2;
y = 0;
}
Q0 = new T([[q,-p],[p,q]],[[x,y],[y,-x]]);
Q.setRows(i,j,Q0.dot(Q.getRows(i,j)));
}
}
}
var R = Q.dot(A).dot(Q.transjugate()), n = A.length, E = numeric.T.identity(n);
for(j=0;j<n;j++) {
if(j>0) {
for(k=j-1;k>=0;k--) {
var Rk = R.get([k,k]), Rj = R.get([j,j]);
if(numeric.neq(Rk.x,Rj.x) || numeric.neq(Rk.y,Rj.y)) {
x = R.getRow(k).getBlock([k],[j-1]);
y = E.getRow(j).getBlock([k],[j-1]);
E.set([j,k],(R.get([k,j]).neg().sub(x.dot(y))).div(Rk.sub(Rj)));
} else {
E.setRow(j,E.getRow(k));
continue;
}
}
}
}
for(j=0;j<n;j++) {
x = E.getRow(j);
E.setRow(j,x.div(x.norm2()));
}
E = E.transpose();
E = Q.transjugate().dot(E);
return { lambda:R.getDiag(), E:E };
};
// 5. Compressed Column Storage matrices
numeric.ccsSparse = function ccsSparse(A) {
var m = A.length,n,foo, i,j, counts = [];
for(i=m-1;i!==-1;--i) {
foo = A[i];
for(j in foo) {
j = parseInt(j);
while(j>=counts.length) counts[counts.length] = 0;
if(foo[j]!==0) counts[j]++;
}
}
var n = counts.length;
var Ai = Array(n+1);
Ai[0] = 0;
for(i=0;i<n;++i) Ai[i+1] = Ai[i] + counts[i];
var Aj = Array(Ai[n]), Av = Array(Ai[n]);
for(i=m-1;i!==-1;--i) {
foo = A[i];
for(j in foo) {
if(foo[j]!==0) {
counts[j]--;
Aj[Ai[j]+counts[j]] = i;
Av[Ai[j]+counts[j]] = foo[j];
}
}
}
return [Ai,Aj,Av];
};
numeric.ccsFull = function ccsFull(A) {
var Ai = A[0], Aj = A[1], Av = A[2], s = numeric.ccsDim(A), m = s[0], n = s[1], i,j,j0,j1,k;
var B = numeric.rep([m,n],0);
for(i=0;i<n;i++) {
j0 = Ai[i];
j1 = Ai[i+1];
for(j=j0;j<j1;++j) { B[Aj[j]][i] = Av[j]; }
}
return B;
};
numeric.ccsTSolve = function ccsTSolve(A,b,x,bj,xj) {
var Ai = A[0], Aj = A[1], Av = A[2],m = Ai.length-1, max = Math.max,n=0;
if(typeof bj === "undefined") x = numeric.rep([m],0);
if(typeof bj === "undefined") bj = numeric.linspace(0,x.length-1);
if(typeof xj === "undefined") xj = [];
function dfs(j) {
var k;
if(x[j] !== 0) return;
x[j] = 1;
for(k=Ai[j];k<Ai[j+1];++k) dfs(Aj[k]);
xj[n] = j;
++n;
}
var i,j,j0,j1,k,l,l0,l1,a;
for(i=bj.length-1;i!==-1;--i) { dfs(bj[i]); }
xj.length = n;
for(i=xj.length-1;i!==-1;--i) { x[xj[i]] = 0; }
for(i=bj.length-1;i!==-1;--i) { j = bj[i]; x[j] = b[j]; }
for(i=xj.length-1;i!==-1;--i) {
j = xj[i];
j0 = Ai[j];
j1 = max(Ai[j+1],j0);
for(k=j0;k!==j1;++k) { if(Aj[k] === j) { x[j] /= Av[k]; break; } }
a = x[j];
for(k=j0;k!==j1;++k) {
l = Aj[k];
if(l !== j) x[l] -= a*Av[k];
}
}
return x;
};
numeric.ccsDFS = function ccsDFS(n) {
this.k = Array(n);
this.k1 = Array(n);
this.j = Array(n);
};
numeric.ccsDFS.prototype.dfs = function dfs(J,Ai,Aj,x,xj,Pinv) {
var m = 0,foo,n=xj.length;
var k = this.k, k1 = this.k1, j = this.j,km,k11;
if(x[J]!==0) return;
x[J] = 1;
j[0] = J;
k[0] = km = Ai[J];
k1[0] = k11 = Ai[J+1];
while(1) {
if(km >= k11) {
xj[n] = j[m];
if(m===0) return;
++n;
--m;
km = k[m];
k11 = k1[m];
} else {
foo = Pinv[Aj[km]];
if(x[foo] === 0) {
x[foo] = 1;
k[m] = km;
++m;
j[m] = foo;
km = Ai[foo];
k1[m] = k11 = Ai[foo+1];
} else ++km;
}
}
};
numeric.ccsLPSolve = function ccsLPSolve(A,B,x,xj,I,Pinv,dfs) {
var Ai = A[0], Aj = A[1], Av = A[2],m = Ai.length-1, n=0;
var Bi = B[0], Bj = B[1], Bv = B[2];
var i,i0,i1,j,J,j0,j1,k,l,l0,l1,a;
i0 = Bi[I];
i1 = Bi[I+1];
xj.length = 0;
for(i=i0;i<i1;++i) { dfs.dfs(Pinv[Bj[i]],Ai,Aj,x,xj,Pinv); }
for(i=xj.length-1;i!==-1;--i) { x[xj[i]] = 0; }
for(i=i0;i!==i1;++i) { j = Pinv[Bj[i]]; x[j] = Bv[i]; }
for(i=xj.length-1;i!==-1;--i) {
j = xj[i];
j0 = Ai[j];
j1 = Ai[j+1];
for(k=j0;k<j1;++k) { if(Pinv[Aj[k]] === j) { x[j] /= Av[k]; break; } }
a = x[j];
for(k=j0;k<j1;++k) {
l = Pinv[Aj[k]];
if(l !== j) x[l] -= a*Av[k];
}
}
return x;
};
numeric.ccsLUP1 = function ccsLUP1(A,threshold) {
var m = A[0].length-1;
var L = [numeric.rep([m+1],0),[],[]], U = [numeric.rep([m+1], 0),[],[]];
var Li = L[0], Lj = L[1], Lv = L[2], Ui = U[0], Uj = U[1], Uv = U[2];
var x = numeric.rep([m],0), xj = numeric.rep([m],0);
var i,j,k,j0,j1,a,e,c,d,K;
var sol = numeric.ccsLPSolve, max = Math.max, abs = Math.abs;
var P = numeric.linspace(0,m-1),Pinv = numeric.linspace(0,m-1);
var dfs = new numeric.ccsDFS(m);
if(typeof threshold === "undefined") { threshold = 1; }
for(i=0;i<m;++i) {
sol(L,A,x,xj,i,Pinv,dfs);
a = -1;
e = -1;
for(j=xj.length-1;j!==-1;--j) {
k = xj[j];
if(k <= i) continue;
c = abs(x[k]);
if(c > a) { e = k; a = c; }
}
if(abs(x[i])<threshold*a) {
j = P[i];
a = P[e];
P[i] = a; Pinv[a] = i;
P[e] = j; Pinv[j] = e;
a = x[i]; x[i] = x[e]; x[e] = a;
}
a = Li[i];
e = Ui[i];
d = x[i];
Lj[a] = P[i];
Lv[a] = 1;
++a;
for(j=xj.length-1;j!==-1;--j) {
k = xj[j];
c = x[k];
xj[j] = 0;
x[k] = 0;
if(k<=i) { Uj[e] = k; Uv[e] = c; ++e; }
else { Lj[a] = P[k]; Lv[a] = c/d; ++a; }
}
Li[i+1] = a;
Ui[i+1] = e;
}
for(j=Lj.length-1;j!==-1;--j) { Lj[j] = Pinv[Lj[j]]; }
return {L:L, U:U, P:P, Pinv:Pinv};
};
numeric.ccsDFS0 = function ccsDFS0(n) {
this.k = Array(n);
this.k1 = Array(n);
this.j = Array(n);
};
numeric.ccsDFS0.prototype.dfs = function dfs(J,Ai,Aj,x,xj,Pinv,P) {
var m = 0,foo,n=xj.length;
var k = this.k, k1 = this.k1, j = this.j,km,k11;
if(x[J]!==0) return;
x[J] = 1;
j[0] = J;
k[0] = km = Ai[Pinv[J]];
k1[0] = k11 = Ai[Pinv[J]+1];
while(1) {
if(isNaN(km)) throw new Error("Ow!");
if(km >= k11) {
xj[n] = Pinv[j[m]];
if(m===0) return;
++n;
--m;
km = k[m];
k11 = k1[m];
} else {
foo = Aj[km];
if(x[foo] === 0) {
x[foo] = 1;
k[m] = km;
++m;
j[m] = foo;
foo = Pinv[foo];
km = Ai[foo];
k1[m] = k11 = Ai[foo+1];
} else ++km;
}
}
};
numeric.ccsLPSolve0 = function ccsLPSolve0(A,B,y,xj,I,Pinv,P,dfs) {
var Ai = A[0], Aj = A[1], Av = A[2],m = Ai.length-1, n=0;
var Bi = B[0], Bj = B[1], Bv = B[2];
var i,i0,i1,j,J,j0,j1,k,l,l0,l1,a;
i0 = Bi[I];
i1 = Bi[I+1];
xj.length = 0;
for(i=i0;i<i1;++i) { dfs.dfs(Bj[i],Ai,Aj,y,xj,Pinv,P); }
for(i=xj.length-1;i!==-1;--i) { j = xj[i]; y[P[j]] = 0; }
for(i=i0;i!==i1;++i) { j = Bj[i]; y[j] = Bv[i]; }
for(i=xj.length-1;i!==-1;--i) {
j = xj[i];
l = P[j];
j0 = Ai[j];
j1 = Ai[j+1];
for(k=j0;k<j1;++k) { if(Aj[k] === l) { y[l] /= Av[k]; break; } }
a = y[l];
for(k=j0;k<j1;++k) y[Aj[k]] -= a*Av[k];
y[l] = a;
}
};
numeric.ccsLUP0 = function ccsLUP0(A,threshold) {
var m = A[0].length-1;
var L = [numeric.rep([m+1],0),[],[]], U = [numeric.rep([m+1], 0),[],[]];
var Li = L[0], Lj = L[1], Lv = L[2], Ui = U[0], Uj = U[1], Uv = U[2];
var y = numeric.rep([m],0), xj = numeric.rep([m],0);
var i,j,k,j0,j1,a,e,c,d,K;
var sol = numeric.ccsLPSolve0, max = Math.max, abs = Math.abs;
var P = numeric.linspace(0,m-1),Pinv = numeric.linspace(0,m-1);
var dfs = new numeric.ccsDFS0(m);
if(typeof threshold === "undefined") { threshold = 1; }
for(i=0;i<m;++i) {
sol(L,A,y,xj,i,Pinv,P,dfs);
a = -1;
e = -1;
for(j=xj.length-1;j!==-1;--j) {
k = xj[j];
if(k <= i) continue;
c = abs(y[P[k]]);
if(c > a) { e = k; a = c; }
}
if(abs(y[P[i]])<threshold*a) {
j = P[i];
a = P[e];
P[i] = a; Pinv[a] = i;
P[e] = j; Pinv[j] = e;
}
a = Li[i];
e = Ui[i];
d = y[P[i]];
Lj[a] = P[i];
Lv[a] = 1;
++a;
for(j=xj.length-1;j!==-1;--j) {
k = xj[j];
c = y[P[k]];
xj[j] = 0;
y[P[k]] = 0;
if(k<=i) { Uj[e] = k; Uv[e] = c; ++e; }
else { Lj[a] = P[k]; Lv[a] = c/d; ++a; }
}
Li[i+1] = a;
Ui[i+1] = e;
}
for(j=Lj.length-1;j!==-1;--j) { Lj[j] = Pinv[Lj[j]]; }
return {L:L, U:U, P:P, Pinv:Pinv};
};
numeric.ccsLUP = numeric.ccsLUP0;
numeric.ccsDim = function ccsDim(A) { return [numeric.sup(A[1])+1,A[0].length-1]; };
numeric.ccsGetBlock = function ccsGetBlock(A,i,j) {
var s = numeric.ccsDim(A),m=s[0],n=s[1];
if(typeof i === "undefined") { i = numeric.linspace(0,m-1); }
else if(typeof i === "number") { i = [i]; }
if(typeof j === "undefined") { j = numeric.linspace(0,n-1); }
else if(typeof j === "number") { j = [j]; }
var p,p0,p1,P = i.length,q,Q = j.length,r,jq,ip;
var Bi = numeric.rep([n],0), Bj=[], Bv=[], B = [Bi,Bj,Bv];
var Ai = A[0], Aj = A[1], Av = A[2];
var x = numeric.rep([m],0),count=0,flags = numeric.rep([m],0);
for(q=0;q<Q;++q) {
jq = j[q];
var q0 = Ai[jq];
var q1 = Ai[jq+1];
for(p=q0;p<q1;++p) {
r = Aj[p];
flags[r] = 1;
x[r] = Av[p];
}
for(p=0;p<P;++p) {
ip = i[p];
if(flags[ip]) {
Bj[count] = p;
Bv[count] = x[i[p]];
++count;
}
}
for(p=q0;p<q1;++p) {
r = Aj[p];
flags[r] = 0;
}
Bi[q+1] = count;
}
return B;
};
numeric.ccsDot = function ccsDot(A,B) {
var Ai = A[0], Aj = A[1], Av = A[2];
var Bi = B[0], Bj = B[1], Bv = B[2];
var sA = numeric.ccsDim(A), sB = numeric.ccsDim(B);
var m = sA[0], n = sA[1], o = sB[1];
var x = numeric.rep([m],0), flags = numeric.rep([m],0), xj = Array(m);
var Ci = numeric.rep([o],0), Cj = [], Cv = [], C = [Ci,Cj,Cv];
var i,j,k,j0,j1,i0,i1,l,p,a,b;
for(k=0;k!==o;++k) {
j0 = Bi[k];
j1 = Bi[k+1];
p = 0;
for(j=j0;j<j1;++j) {
a = Bj[j];
b = Bv[j];
i0 = Ai[a];
i1 = Ai[a+1];
for(i=i0;i<i1;++i) {
l = Aj[i];
if(flags[l]===0) {
xj[p] = l;
flags[l] = 1;
p = p+1;
}
x[l] = x[l] + Av[i]*b;
}
}
j0 = Ci[k];
j1 = j0+p;
Ci[k+1] = j1;
for(j=p-1;j!==-1;--j) {
b = j0+j;
i = xj[j];
Cj[b] = i;
Cv[b] = x[i];
flags[i] = 0;
x[i] = 0;
}
Ci[k+1] = Ci[k]+p;
}
return C;
};
numeric.ccsLUPSolve = function ccsLUPSolve(LUP,B) {
var L = LUP.L, U = LUP.U, P = LUP.P;
var Bi = B[0];
var flag = false;
if(typeof Bi !== "object") { B = [[0,B.length],numeric.linspace(0,B.length-1),B]; Bi = B[0]; flag = true; }
var Bj = B[1], Bv = B[2];
var n = L[0].length-1, m = Bi.length-1;
var x = numeric.rep([n],0), xj = Array(n);
var b = numeric.rep([n],0), bj = Array(n);
var Xi = numeric.rep([m+1],0), Xj = [], Xv = [];
var sol = numeric.ccsTSolve;
var i,j,j0,j1,k,J,N=0;
for(i=0;i<m;++i) {
k = 0;
j0 = Bi[i];
j1 = Bi[i+1];
for(j=j0;j<j1;++j) {
J = LUP.Pinv[Bj[j]];
bj[k] = J;
b[J] = Bv[j];
++k;
}
bj.length = k;
sol(L,b,x,bj,xj);
for(j=bj.length-1;j!==-1;--j) b[bj[j]] = 0;
sol(U,x,b,xj,bj);
if(flag) return b;
for(j=xj.length-1;j!==-1;--j) x[xj[j]] = 0;
for(j=bj.length-1;j!==-1;--j) {
J = bj[j];
Xj[N] = J;
Xv[N] = b[J];
b[J] = 0;
++N;
}
Xi[i+1] = N;
}
return [Xi,Xj,Xv];
};
numeric.ccsbinop = function ccsbinop(body,setup) {
if(typeof setup === "undefined") setup='';
return Function('X','Y',
'var Xi = X[0], Xj = X[1], Xv = X[2];\n'+
'var Yi = Y[0], Yj = Y[1], Yv = Y[2];\n'+
'var n = Xi.length-1,m = Math.max(numeric.sup(Xj),numeric.sup(Yj))+1;\n'+
'var Zi = numeric.rep([n+1],0), Zj = [], Zv = [];\n'+
'var x = numeric.rep([m],0),y = numeric.rep([m],0);\n'+
'var xk,yk,zk;\n'+
'var i,j,j0,j1,k,p=0;\n'+
setup+
'for(i=0;i<n;++i) {\n'+
' j0 = Xi[i]; j1 = Xi[i+1];\n'+
' for(j=j0;j!==j1;++j) {\n'+
' k = Xj[j];\n'+
' x[k] = 1;\n'+
' Zj[p] = k;\n'+
' ++p;\n'+
' }\n'+
' j0 = Yi[i]; j1 = Yi[i+1];\n'+
' for(j=j0;j!==j1;++j) {\n'+
' k = Yj[j];\n'+
' y[k] = Yv[j];\n'+
' if(x[k] === 0) {\n'+
' Zj[p] = k;\n'+
' ++p;\n'+
' }\n'+
' }\n'+
' Zi[i+1] = p;\n'+
' j0 = Xi[i]; j1 = Xi[i+1];\n'+
' for(j=j0;j!==j1;++j) x[Xj[j]] = Xv[j];\n'+
' j0 = Zi[i]; j1 = Zi[i+1];\n'+
' for(j=j0;j!==j1;++j) {\n'+
' k = Zj[j];\n'+
' xk = x[k];\n'+
' yk = y[k];\n'+
body+'\n'+
' Zv[j] = zk;\n'+
' }\n'+
' j0 = Xi[i]; j1 = Xi[i+1];\n'+
' for(j=j0;j!==j1;++j) x[Xj[j]] = 0;\n'+
' j0 = Yi[i]; j1 = Yi[i+1];\n'+
' for(j=j0;j!==j1;++j) y[Yj[j]] = 0;\n'+
'}\n'+
'return [Zi,Zj,Zv];'
);
};
(function() {
var k,A,B,C;
for(k in numeric.ops2) {
if(isFinite(eval('1'+numeric.ops2[k]+'0'))) A = '[Y[0],Y[1],numeric.'+k+'(X,Y[2])]';
else A = 'NaN';
if(isFinite(eval('0'+numeric.ops2[k]+'1'))) B = '[X[0],X[1],numeric.'+k+'(X[2],Y)]';
else B = 'NaN';
if(isFinite(eval('1'+numeric.ops2[k]+'0')) && isFinite(eval('0'+numeric.ops2[k]+'1'))) C = 'numeric.ccs'+k+'MM(X,Y)';
else C = 'NaN';
numeric['ccs'+k+'MM'] = numeric.ccsbinop('zk = xk '+numeric.ops2[k]+'yk;');
numeric['ccs'+k] = Function('X','Y',
'if(typeof X === "number") return '+A+';\n'+
'if(typeof Y === "number") return '+B+';\n'+
'return '+C+';\n'
);
}
}());
numeric.ccsScatter = function ccsScatter(A) {
var Ai = A[0], Aj = A[1], Av = A[2];
var n = numeric.sup(Aj)+1,m=Ai.length;
var Ri = numeric.rep([n],0),Rj=Array(m), Rv = Array(m);
var counts = numeric.rep([n],0),i;
for(i=0;i<m;++i) counts[Aj[i]]++;
for(i=0;i<n;++i) Ri[i+1] = Ri[i] + counts[i];
var ptr = Ri.slice(0),k,Aii;
for(i=0;i<m;++i) {
Aii = Aj[i];
k = ptr[Aii];
Rj[k] = Ai[i];
Rv[k] = Av[i];
ptr[Aii]=ptr[Aii]+1;
}
return [Ri,Rj,Rv];
};
numeric.ccsGather = function ccsGather(A) {
var Ai = A[0], Aj = A[1], Av = A[2];
var n = Ai.length-1,m = Aj.length;
var Ri = Array(m), Rj = Array(m), Rv = Array(m);
var i,j,j0,j1,p;
p=0;
for(i=0;i<n;++i) {
j0 = Ai[i];
j1 = Ai[i+1];
for(j=j0;j!==j1;++j) {
Rj[p] = i;
Ri[p] = Aj[j];
Rv[p] = Av[j];
++p;
}
}
return [Ri,Rj,Rv];
};
// The following sparse linear algebra routines are deprecated.
numeric.sdim = function dim(A,ret,k) {
if(typeof ret === "undefined") { ret = []; }
if(typeof A !== "object") return ret;
if(typeof k === "undefined") { k=0; }
if(!(k in ret)) { ret[k] = 0; }
if(A.length > ret[k]) ret[k] = A.length;
var i;
for(i in A) {
if(A.hasOwnProperty(i)) dim(A[i],ret,k+1);
}
return ret;
};
numeric.sclone = function clone(A,k,n) {
if(typeof k === "undefined") { k=0; }
if(typeof n === "undefined") { n = numeric.sdim(A).length; }
var i,ret = Array(A.length);
if(k === n-1) {
for(i in A) { if(A.hasOwnProperty(i)) ret[i] = A[i]; }
return ret;
}
for(i in A) {
if(A.hasOwnProperty(i)) ret[i] = clone(A[i],k+1,n);
}
return ret;
};
numeric.sdiag = function diag(d) {
var n = d.length,i,ret = Array(n),i1,i2,i3;
for(i=n-1;i>=1;i-=2) {
i1 = i-1;
ret[i] = []; ret[i][i] = d[i];
ret[i1] = []; ret[i1][i1] = d[i1];
}
if(i===0) { ret[0] = []; ret[0][0] = d[i]; }
return ret;
};
numeric.sidentity = function identity(n) { return numeric.sdiag(numeric.rep([n],1)); };
numeric.stranspose = function transpose(A) {
var ret = [], n = A.length, i,j,Ai;
for(i in A) {
if(!(A.hasOwnProperty(i))) continue;
Ai = A[i];
for(j in Ai) {
if(!(Ai.hasOwnProperty(j))) continue;
if(typeof ret[j] !== "object") { ret[j] = []; }
ret[j][i] = Ai[j];
}
}
return ret;
};
numeric.sLUP = function LUP(A,tol) {
throw new Error("The function numeric.sLUP had a bug in it and has been removed. Please use the new numeric.ccsLUP function instead.");
};
numeric.sdotMM = function dotMM(A,B) {
var p = A.length, q = B.length, BT = numeric.stranspose(B), r = BT.length, Ai, BTk;
var i,j,k,accum;
var ret = Array(p),reti;
for(i=p-1;i>=0;i--) {
reti = [];
Ai = A[i];
for(k=r-1;k>=0;k--) {
accum = 0;
BTk = BT[k];
for(j in Ai) {
if(!(Ai.hasOwnProperty(j))) continue;
if(j in BTk) { accum += Ai[j]*BTk[j]; }
}
if(accum) reti[k] = accum;
}
ret[i] = reti;
}
return ret;
};
numeric.sdotMV = function dotMV(A,x) {
var p = A.length, Ai, i,j;
var ret = Array(p), accum;
for(i=p-1;i>=0;i--) {
Ai = A[i];
accum = 0;
for(j in Ai) {
if(!(Ai.hasOwnProperty(j))) continue;
if(x[j]) accum += Ai[j]*x[j];
}
if(accum) ret[i] = accum;
}
return ret;
};
numeric.sdotVM = function dotMV(x,A) {
var i,j,Ai,alpha;
var ret = [], accum;
for(i in x) {
if(!x.hasOwnProperty(i)) continue;
Ai = A[i];
alpha = x[i];
for(j in Ai) {
if(!Ai.hasOwnProperty(j)) continue;
if(!ret[j]) { ret[j] = 0; }
ret[j] += alpha*Ai[j];
}
}
return ret;
};
numeric.sdotVV = function dotVV(x,y) {
var i,ret=0;
for(i in x) { if(x[i] && y[i]) ret+= x[i]*y[i]; }
return ret;
};
numeric.sdot = function dot(A,B) {
var m = numeric.sdim(A).length, n = numeric.sdim(B).length;
var k = m*1000+n;
switch(k) {
case 0: return A*B;
case 1001: return numeric.sdotVV(A,B);
case 2001: return numeric.sdotMV(A,B);
case 1002: return numeric.sdotVM(A,B);
case 2002: return numeric.sdotMM(A,B);
default: throw new Error('numeric.sdot not implemented for tensors of order '+m+' and '+n);
}
};
numeric.sscatter = function scatter(V) {
var n = V[0].length, Vij, i, j, m = V.length, A = [], Aj;
for(i=n-1;i>=0;--i) {
if(!V[m-1][i]) continue;
Aj = A;
for(j=0;j<m-2;j++) {
Vij = V[j][i];
if(!Aj[Vij]) Aj[Vij] = [];
Aj = Aj[Vij];
}
Aj[V[j][i]] = V[j+1][i];
}
return A;
};
numeric.sgather = function gather(A,ret,k) {
if(typeof ret === "undefined") ret = [];
if(typeof k === "undefined") k = [];
var n,i,Ai;
n = k.length;
for(i in A) {
if(A.hasOwnProperty(i)) {
k[n] = parseInt(i);
Ai = A[i];
if(typeof Ai === "number") {
if(Ai) {
if(ret.length === 0) {
for(i=n+1;i>=0;--i) ret[i] = [];
}
for(i=n;i>=0;--i) ret[i].push(k[i]);
ret[n+1].push(Ai);
}
} else gather(Ai,ret,k);
}
}
if(k.length>n) k.pop();
return ret;
};
// 6. Coordinate matrices
numeric.cLU = function LU(A) {
var I = A[0], J = A[1], V = A[2];
var p = I.length, m=0, i,j,k,a,b,c;
for(i=0;i<p;i++) if(I[i]>m) m=I[i];
m++;
var L = Array(m), U = Array(m), left = numeric.rep([m],Infinity), right = numeric.rep([m],-Infinity);
var Ui, Uj,alpha;
for(k=0;k<p;k++) {
i = I[k];
j = J[k];
if(j<left[i]) left[i] = j;
if(j>right[i]) right[i] = j;
}
for(i=0;i<m-1;i++) { if(right[i] > right[i+1]) right[i+1] = right[i]; }
for(i=m-1;i>=1;i--) { if(left[i]<left[i-1]) left[i-1] = left[i]; }
var countL = 0, countU = 0;
for(i=0;i<m;i++) {
U[i] = numeric.rep([right[i]-left[i]+1],0);
L[i] = numeric.rep([i-left[i]],0);
countL += i-left[i]+1;
countU += right[i]-i+1;
}
for(k=0;k<p;k++) { i = I[k]; U[i][J[k]-left[i]] = V[k]; }
for(i=0;i<m-1;i++) {
a = i-left[i];
Ui = U[i];
for(j=i+1;left[j]<=i && j<m;j++) {
b = i-left[j];
c = right[i]-i;
Uj = U[j];
alpha = Uj[b]/Ui[a];
if(alpha) {
for(k=1;k<=c;k++) { Uj[k+b] -= alpha*Ui[k+a]; }
L[j][i-left[j]] = alpha;
}
}
}
var Ui = [], Uj = [], Uv = [], Li = [], Lj = [], Lv = [];
var p,q,foo;
p=0; q=0;
for(i=0;i<m;i++) {
a = left[i];
b = right[i];
foo = U[i];
for(j=i;j<=b;j++) {
if(foo[j-a]) {
Ui[p] = i;
Uj[p] = j;
Uv[p] = foo[j-a];
p++;
}
}
foo = L[i];
for(j=a;j<i;j++) {
if(foo[j-a]) {
Li[q] = i;
Lj[q] = j;
Lv[q] = foo[j-a];
q++;
}
}
Li[q] = i;
Lj[q] = i;
Lv[q] = 1;
q++;
}
return {U:[Ui,Uj,Uv], L:[Li,Lj,Lv]};
};
numeric.cLUsolve = function LUsolve(lu,b) {
var L = lu.L, U = lu.U, ret = numeric.clone(b);
var Li = L[0], Lj = L[1], Lv = L[2];
var Ui = U[0], Uj = U[1], Uv = U[2];
var p = Ui.length, q = Li.length;
var m = ret.length,i,j,k;
k = 0;
for(i=0;i<m;i++) {
while(Lj[k] < i) {
ret[i] -= Lv[k]*ret[Lj[k]];
k++;
}
k++;
}
k = p-1;
for(i=m-1;i>=0;i--) {
while(Uj[k] > i) {
ret[i] -= Uv[k]*ret[Uj[k]];
k--;
}
ret[i] /= Uv[k];
k--;
}
return ret;
};
numeric.cgrid = function grid(n,shape) {
if(typeof n === "number") n = [n,n];
var ret = numeric.rep(n,-1);
var i,j,count;
if(typeof shape !== "function") {
switch(shape) {
case 'L':
shape = function(i,j) { return (i>=n[0]/2 || j<n[1]/2); };
break;
default:
shape = function(i,j) { return true; };
break;
}
}
count=0;
for(i=1;i<n[0]-1;i++) for(j=1;j<n[1]-1;j++)
if(shape(i,j)) {
ret[i][j] = count;
count++;
}
return ret;
};
numeric.cdelsq = function delsq(g) {
var dir = [[-1,0],[0,-1],[0,1],[1,0]];
var s = numeric.dim(g), m = s[0], n = s[1], i,j,k,p,q;
var Li = [], Lj = [], Lv = [];
for(i=1;i<m-1;i++) for(j=1;j<n-1;j++) {
if(g[i][j]<0) continue;
for(k=0;k<4;k++) {
p = i+dir[k][0];
q = j+dir[k][1];
if(g[p][q]<0) continue;
Li.push(g[i][j]);
Lj.push(g[p][q]);
Lv.push(-1);
}
Li.push(g[i][j]);
Lj.push(g[i][j]);
Lv.push(4);
}
return [Li,Lj,Lv];
};
numeric.cdotMV = function dotMV(A,x) {
var ret, Ai = A[0], Aj = A[1], Av = A[2],k,p=Ai.length,N;
N=0;
for(k=0;k<p;k++) { if(Ai[k]>N) N = Ai[k]; }
N++;
ret = numeric.rep([N],0);
for(k=0;k<p;k++) { ret[Ai[k]]+=Av[k]*x[Aj[k]]; }
return ret;
};
// 7. Splines
numeric.Spline = function Spline(x,yl,yr,kl,kr) { this.x = x; this.yl = yl; this.yr = yr; this.kl = kl; this.kr = kr; };
numeric.Spline.prototype._at = function _at(x1,p) {
var x = this.x;
var yl = this.yl;
var yr = this.yr;
var kl = this.kl;
var kr = this.kr;
var x1,a,b,t;
var add = numeric.add, sub = numeric.sub, mul = numeric.mul;
a = sub(mul(kl[p],x[p+1]-x[p]),sub(yr[p+1],yl[p]));
b = add(mul(kr[p+1],x[p]-x[p+1]),sub(yr[p+1],yl[p]));
t = (x1-x[p])/(x[p+1]-x[p]);
var s = t*(1-t);
return add(add(add(mul(1-t,yl[p]),mul(t,yr[p+1])),mul(a,s*(1-t))),mul(b,s*t));
};
numeric.Spline.prototype.at = function at(x0) {
if(typeof x0 === "number") {
var x = this.x;
var n = x.length;
var p,q,mid,floor = Math.floor,a,b,t;
p = 0;
q = n-1;
while(q-p>1) {
mid = floor((p+q)/2);
if(x[mid] <= x0) p = mid;
else q = mid;
}
return this._at(x0,p);
}
var n = x0.length, i, ret = Array(n);
for(i=n-1;i!==-1;--i) ret[i] = this.at(x0[i]);
return ret;
};
numeric.Spline.prototype.diff = function diff() {
var x = this.x;
var yl = this.yl;
var yr = this.yr;
var kl = this.kl;
var kr = this.kr;
var n = yl.length;
var i,dx,dy;
var zl = kl, zr = kr, pl = Array(n), pr = Array(n);
var add = numeric.add, mul = numeric.mul, div = numeric.div, sub = numeric.sub;
for(i=n-1;i!==-1;--i) {
dx = x[i+1]-x[i];
dy = sub(yr[i+1],yl[i]);
pl[i] = div(add(mul(dy, 6),mul(kl[i],-4*dx),mul(kr[i+1],-2*dx)),dx*dx);
pr[i+1] = div(add(mul(dy,-6),mul(kl[i], 2*dx),mul(kr[i+1], 4*dx)),dx*dx);
}
return new numeric.Spline(x,zl,zr,pl,pr);
};
numeric.Spline.prototype.roots = function roots() {
function sqr(x) { return x*x; }
var ret = [];
var x = this.x, yl = this.yl, yr = this.yr, kl = this.kl, kr = this.kr;
if(typeof yl[0] === "number") {
yl = [yl];
yr = [yr];
kl = [kl];
kr = [kr];
}
var m = yl.length,n=x.length-1,i,j,k,y,s,t;
var ai,bi,ci,di, ret = Array(m),ri,k0,k1,y0,y1,A,B,D,dx,cx,stops,z0,z1,zm,t0,t1,tm;
var sqrt = Math.sqrt;
for(i=0;i!==m;++i) {
ai = yl[i];
bi = yr[i];
ci = kl[i];
di = kr[i];
ri = [];
for(j=0;j!==n;j++) {
if(j>0 && bi[j]*ai[j]<0) ri.push(x[j]);
dx = (x[j+1]-x[j]);
cx = x[j];
y0 = ai[j];
y1 = bi[j+1];
k0 = ci[j]/dx;
k1 = di[j+1]/dx;
D = sqr(k0-k1+3*(y0-y1)) + 12*k1*y0;
A = k1+3*y0+2*k0-3*y1;
B = 3*(k1+k0+2*(y0-y1));
if(D<=0) {
z0 = A/B;
if(z0>x[j] && z0<x[j+1]) stops = [x[j],z0,x[j+1]];
else stops = [x[j],x[j+1]];
} else {
z0 = (A-sqrt(D))/B;
z1 = (A+sqrt(D))/B;
stops = [x[j]];
if(z0>x[j] && z0<x[j+1]) stops.push(z0);
if(z1>x[j] && z1<x[j+1]) stops.push(z1);
stops.push(x[j+1]);
}
t0 = stops[0];
z0 = this._at(t0,j);
for(k=0;k<stops.length-1;k++) {
t1 = stops[k+1];
z1 = this._at(t1,j);
if(z0 === 0) {
ri.push(t0);
t0 = t1;
z0 = z1;
continue;
}
if(z1 === 0 || z0*z1>0) {
t0 = t1;
z0 = z1;
continue;
}
var side = 0;
while(1) {
tm = (z0*t1-z1*t0)/(z0-z1);
if(tm <= t0 || tm >= t1) { break; }
zm = this._at(tm,j);
if(zm*z1>0) {
t1 = tm;
z1 = zm;
if(side === -1) z0*=0.5;
side = -1;
} else if(zm*z0>0) {
t0 = tm;
z0 = zm;
if(side === 1) z1*=0.5;
side = 1;
} else break;
}
ri.push(tm);
t0 = stops[k+1];
z0 = this._at(t0, j);
}
if(z1 === 0) ri.push(t1);
}
ret[i] = ri;
}
if(typeof this.yl[0] === "number") return ret[0];
return ret;
};
numeric.spline = function spline(x,y,k1,kn) {
var n = x.length, b = [], dx = [], dy = [];
var i;
var sub = numeric.sub,mul = numeric.mul,add = numeric.add;
for(i=n-2;i>=0;i--) { dx[i] = x[i+1]-x[i]; dy[i] = sub(y[i+1],y[i]); }
if(typeof k1 === "string" || typeof kn === "string") {
k1 = kn = "periodic";
}
// Build sparse tridiagonal system
var T = [[],[],[]];
switch(typeof k1) {
case "undefined":
b[0] = mul(3/(dx[0]*dx[0]),dy[0]);
T[0].push(0,0);
T[1].push(0,1);
T[2].push(2/dx[0],1/dx[0]);
break;
case "string":
b[0] = add(mul(3/(dx[n-2]*dx[n-2]),dy[n-2]),mul(3/(dx[0]*dx[0]),dy[0]));
T[0].push(0,0,0);
T[1].push(n-2,0,1);
T[2].push(1/dx[n-2],2/dx[n-2]+2/dx[0],1/dx[0]);
break;
default:
b[0] = k1;
T[0].push(0);
T[1].push(0);
T[2].push(1);
break;
}
for(i=1;i<n-1;i++) {
b[i] = add(mul(3/(dx[i-1]*dx[i-1]),dy[i-1]),mul(3/(dx[i]*dx[i]),dy[i]));
T[0].push(i,i,i);
T[1].push(i-1,i,i+1);
T[2].push(1/dx[i-1],2/dx[i-1]+2/dx[i],1/dx[i]);
}
switch(typeof kn) {
case "undefined":
b[n-1] = mul(3/(dx[n-2]*dx[n-2]),dy[n-2]);
T[0].push(n-1,n-1);
T[1].push(n-2,n-1);
T[2].push(1/dx[n-2],2/dx[n-2]);
break;
case "string":
T[1][T[1].length-1] = 0;
break;
default:
b[n-1] = kn;
T[0].push(n-1);
T[1].push(n-1);
T[2].push(1);
break;
}
if(typeof b[0] !== "number") b = numeric.transpose(b);
else b = [b];
var k = Array(b.length);
if(typeof k1 === "string") {
for(i=k.length-1;i!==-1;--i) {
k[i] = numeric.ccsLUPSolve(numeric.ccsLUP(numeric.ccsScatter(T)),b[i]);
k[i][n-1] = k[i][0];
}
} else {
for(i=k.length-1;i!==-1;--i) {
k[i] = numeric.cLUsolve(numeric.cLU(T),b[i]);
}
}
if(typeof y[0] === "number") k = k[0];
else k = numeric.transpose(k);
return new numeric.Spline(x,y,y,k,k);
};
// 8. FFT
numeric.fftpow2 = function fftpow2(x,y) {
var n = x.length;
if(n === 1) return;
var cos = Math.cos, sin = Math.sin, i,j;
var xe = Array(n/2), ye = Array(n/2), xo = Array(n/2), yo = Array(n/2);
j = n/2;
for(i=n-1;i!==-1;--i) {
--j;
xo[j] = x[i];
yo[j] = y[i];
--i;
xe[j] = x[i];
ye[j] = y[i];
}
fftpow2(xe,ye);
fftpow2(xo,yo);
j = n/2;
var t,k = (-6.2831853071795864769252867665590057683943387987502116419/n),ci,si;
for(i=n-1;i!==-1;--i) {
--j;
if(j === -1) j = n/2-1;
t = k*i;
ci = cos(t);
si = sin(t);
x[i] = xe[j] + ci*xo[j] - si*yo[j];
y[i] = ye[j] + ci*yo[j] + si*xo[j];
}
};
numeric._ifftpow2 = function _ifftpow2(x,y) {
var n = x.length;
if(n === 1) return;
var cos = Math.cos, sin = Math.sin, i,j;
var xe = Array(n/2), ye = Array(n/2), xo = Array(n/2), yo = Array(n/2);
j = n/2;
for(i=n-1;i!==-1;--i) {
--j;
xo[j] = x[i];
yo[j] = y[i];
--i;
xe[j] = x[i];
ye[j] = y[i];
}
_ifftpow2(xe,ye);
_ifftpow2(xo,yo);
j = n/2;
var t,k = (6.2831853071795864769252867665590057683943387987502116419/n),ci,si;
for(i=n-1;i!==-1;--i) {
--j;
if(j === -1) j = n/2-1;
t = k*i;
ci = cos(t);
si = sin(t);
x[i] = xe[j] + ci*xo[j] - si*yo[j];
y[i] = ye[j] + ci*yo[j] + si*xo[j];
}
};
numeric.ifftpow2 = function ifftpow2(x,y) {
numeric._ifftpow2(x,y);
numeric.diveq(x,x.length);
numeric.diveq(y,y.length);
};
numeric.convpow2 = function convpow2(ax,ay,bx,by) {
numeric.fftpow2(ax,ay);
numeric.fftpow2(bx,by);
var i,n = ax.length,axi,bxi,ayi,byi;
for(i=n-1;i!==-1;--i) {
axi = ax[i]; ayi = ay[i]; bxi = bx[i]; byi = by[i];
ax[i] = axi*bxi-ayi*byi;
ay[i] = axi*byi+ayi*bxi;
}
numeric.ifftpow2(ax,ay);
};
numeric.T.prototype.fft = function fft() {
var x = this.x, y = this.y;
var n = x.length, log = Math.log, log2 = log(2),
p = Math.ceil(log(2*n-1)/log2), m = Math.pow(2,p);
var cx = numeric.rep([m],0), cy = numeric.rep([m],0), cos = Math.cos, sin = Math.sin;
var k, c = (-3.141592653589793238462643383279502884197169399375105820/n),t;
var a = numeric.rep([m],0), b = numeric.rep([m],0),nhalf = Math.floor(n/2);
for(k=0;k<n;k++) a[k] = x[k];
if(typeof y !== "undefined") for(k=0;k<n;k++) b[k] = y[k];
cx[0] = 1;
for(k=1;k<=m/2;k++) {
t = c*k*k;
cx[k] = cos(t);
cy[k] = sin(t);
cx[m-k] = cos(t);
cy[m-k] = sin(t);
}
var X = new numeric.T(a,b), Y = new numeric.T(cx,cy);
X = X.mul(Y);
numeric.convpow2(X.x,X.y,numeric.clone(Y.x),numeric.neg(Y.y));
X = X.mul(Y);
X.x.length = n;
X.y.length = n;
return X;
};
numeric.T.prototype.ifft = function ifft() {
var x = this.x, y = this.y;
var n = x.length, log = Math.log, log2 = log(2),
p = Math.ceil(log(2*n-1)/log2), m = Math.pow(2,p);
var cx = numeric.rep([m],0), cy = numeric.rep([m],0), cos = Math.cos, sin = Math.sin;
var k, c = (3.141592653589793238462643383279502884197169399375105820/n),t;
var a = numeric.rep([m],0), b = numeric.rep([m],0),nhalf = Math.floor(n/2);
for(k=0;k<n;k++) a[k] = x[k];
if(typeof y !== "undefined") for(k=0;k<n;k++) b[k] = y[k];
cx[0] = 1;
for(k=1;k<=m/2;k++) {
t = c*k*k;
cx[k] = cos(t);
cy[k] = sin(t);
cx[m-k] = cos(t);
cy[m-k] = sin(t);
}
var X = new numeric.T(a,b), Y = new numeric.T(cx,cy);
X = X.mul(Y);
numeric.convpow2(X.x,X.y,numeric.clone(Y.x),numeric.neg(Y.y));
X = X.mul(Y);
X.x.length = n;
X.y.length = n;
return X.div(n);
};
//9. Unconstrained optimization
numeric.gradient = function gradient(f,x) {
var n = x.length;
var f0 = f(x);
if(isNaN(f0)) throw new Error('gradient: f(x) is a NaN!');
var max = Math.max;
var i,x0 = numeric.clone(x),f1,f2, J = Array(n);
var div = numeric.div, sub = numeric.sub,errest,roundoff,max = Math.max,eps = 1e-3,abs = Math.abs, min = Math.min;
var t0,t1,t2,it=0,d1,d2,N;
for(i=0;i<n;i++) {
var h = max(1e-6*f0,1e-8);
while(1) {
++it;
if(it>20) { throw new Error("Numerical gradient fails"); }
x0[i] = x[i]+h;
f1 = f(x0);
x0[i] = x[i]-h;
f2 = f(x0);
x0[i] = x[i];
if(isNaN(f1) || isNaN(f2)) { h/=16; continue; }
J[i] = (f1-f2)/(2*h);
t0 = x[i]-h;
t1 = x[i];
t2 = x[i]+h;
d1 = (f1-f0)/h;
d2 = (f0-f2)/h;
N = max(abs(J[i]),abs(f0),abs(f1),abs(f2),abs(t0),abs(t1),abs(t2),1e-8);
errest = min(max(abs(d1-J[i]),abs(d2-J[i]),abs(d1-d2))/N,h/N);
if(errest>eps) { h/=16; }
else break;
}
}
return J;
};
numeric.uncmin = function uncmin(f,x0,tol,gradient,maxit,callback,options) {
var grad = numeric.gradient;
if(typeof options === "undefined") { options = {}; }
if(typeof tol === "undefined") { tol = 1e-8; }
if(typeof gradient === "undefined") { gradient = function(x) { return grad(f,x); }; }
if(typeof maxit === "undefined") maxit = 1000;
x0 = numeric.clone(x0);
var n = x0.length;
var f0 = f(x0),f1,df0;
if(isNaN(f0)) throw new Error('uncmin: f(x0) is a NaN!');
var max = Math.max, norm2 = numeric.norm2;
tol = max(tol,numeric.epsilon);
var step,g0,g1,H1 = options.Hinv || numeric.identity(n);
var dot = numeric.dot, inv = numeric.inv, sub = numeric.sub, add = numeric.add, ten = numeric.tensor, div = numeric.div, mul = numeric.mul;
var all = numeric.all, isfinite = numeric.isFinite, neg = numeric.neg;
var it=0,i,s,x1,y,Hy,Hs,ys,i0,t,nstep,t1,t2;
var msg = "";
g0 = gradient(x0);
while(it<maxit) {
if(typeof callback === "function") { if(callback(it,x0,f0,g0,H1)) { msg = "Callback returned true"; break; } }
if(!all(isfinite(g0))) { msg = "Gradient has Infinity or NaN"; break; }
step = neg(dot(H1,g0));
if(!all(isfinite(step))) { msg = "Search direction has Infinity or NaN"; break; }
nstep = norm2(step);
if(nstep < tol) { msg="Newton step smaller than tol"; break; }
t = 1;
df0 = dot(g0,step);
// line search
x1 = x0;
while(it < maxit) {
if(t*nstep < tol) { break; }
s = mul(step,t);
x1 = add(x0,s);
f1 = f(x1);
if(f1-f0 >= 0.1*t*df0 || isNaN(f1)) {
t *= 0.5;
++it;
continue;
}
break;
}
if(t*nstep < tol) { msg = "Line search step size smaller than tol"; break; }
if(it === maxit) { msg = "maxit reached during line search"; break; }
g1 = gradient(x1);
y = sub(g1,g0);
ys = dot(y,s);
Hy = dot(H1,y);
H1 = sub(add(H1,
mul(
(ys+dot(y,Hy))/(ys*ys),
ten(s,s) )),
div(add(ten(Hy,s),ten(s,Hy)),ys));
x0 = x1;
f0 = f1;
g0 = g1;
++it;
}
return {solution: x0, f: f0, gradient: g0, invHessian: H1, iterations:it, message: msg};
};
// 10. Ode solver (Dormand-Prince)
numeric.Dopri = function Dopri(x,y,f,ymid,iterations,msg,events) {
this.x = x;
this.y = y;
this.f = f;
this.ymid = ymid;
this.iterations = iterations;
this.events = events;
this.message = msg;
};
numeric.Dopri.prototype._at = function _at(xi,j) {
function sqr(x) { return x*x; }
var sol = this;
var xs = sol.x;
var ys = sol.y;
var k1 = sol.f;
var ymid = sol.ymid;
var n = xs.length;
var x0,x1,xh,y0,y1,yh,xi;
var floor = Math.floor,h;
var c = 0.5;
var add = numeric.add, mul = numeric.mul,sub = numeric.sub, p,q,w;
x0 = xs[j];
x1 = xs[j+1];
y0 = ys[j];
y1 = ys[j+1];
h = x1-x0;
xh = x0+c*h;
yh = ymid[j];
p = sub(k1[j ],mul(y0,1/(x0-xh)+2/(x0-x1)));
q = sub(k1[j+1],mul(y1,1/(x1-xh)+2/(x1-x0)));
w = [sqr(xi - x1) * (xi - xh) / sqr(x0 - x1) / (x0 - xh),
sqr(xi - x0) * sqr(xi - x1) / sqr(x0 - xh) / sqr(x1 - xh),
sqr(xi - x0) * (xi - xh) / sqr(x1 - x0) / (x1 - xh),
(xi - x0) * sqr(xi - x1) * (xi - xh) / sqr(x0-x1) / (x0 - xh),
(xi - x1) * sqr(xi - x0) * (xi - xh) / sqr(x0-x1) / (x1 - xh)];
return add(add(add(add(mul(y0,w[0]),
mul(yh,w[1])),
mul(y1,w[2])),
mul( p,w[3])),
mul( q,w[4]));
};
numeric.Dopri.prototype.at = function at(x) {
var i,j,k,floor = Math.floor;
if(typeof x !== "number") {
var n = x.length, ret = Array(n);
for(i=n-1;i!==-1;--i) {
ret[i] = this.at(x[i]);
}
return ret;
}
var x0 = this.x;
i = 0; j = x0.length-1;
while(j-i>1) {
k = floor(0.5*(i+j));
if(x0[k] <= x) i = k;
else j = k;
}
return this._at(x,i);
};
numeric.dopri = function dopri(x0,x1,y0,f,tol,maxit,event) {
if(typeof tol === "undefined") { tol = 1e-6; }
if(typeof maxit === "undefined") { maxit = 1000; }
var xs = [x0], ys = [y0], k1 = [f(x0,y0)], k2,k3,k4,k5,k6,k7, ymid = [];
var A2 = 1/5;
var A3 = [3/40,9/40];
var A4 = [44/45,-56/15,32/9];
var A5 = [19372/6561,-25360/2187,64448/6561,-212/729];
var A6 = [9017/3168,-355/33,46732/5247,49/176,-5103/18656];
var b = [35/384,0,500/1113,125/192,-2187/6784,11/84];
var bm = [0.5*6025192743/30085553152,
0,
0.5*51252292925/65400821598,
0.5*-2691868925/45128329728,
0.5*187940372067/1594534317056,
0.5*-1776094331/19743644256,
0.5*11237099/235043384];
var c = [1/5,3/10,4/5,8/9,1,1];
var e = [-71/57600,0,71/16695,-71/1920,17253/339200,-22/525,1/40];
var i = 0,er,j;
var h = (x1-x0)/10;
var it = 0;
var add = numeric.add, mul = numeric.mul, y1,erinf;
var max = Math.max, min = Math.min, abs = Math.abs, norminf = numeric.norminf,pow = Math.pow;
var any = numeric.any, lt = numeric.lt, and = numeric.and, sub = numeric.sub;
var e0, e1, ev;
var ret = new numeric.Dopri(xs,ys,k1,ymid,-1,"");
if(typeof event === "function") e0 = event(x0,y0);
while(x0<x1 && it<maxit) {
++it;
if(x0+h>x1) h = x1-x0;
k2 = f(x0+c[0]*h, add(y0,mul( A2*h,k1[i])));
k3 = f(x0+c[1]*h, add(add(y0,mul(A3[0]*h,k1[i])),mul(A3[1]*h,k2)));
k4 = f(x0+c[2]*h, add(add(add(y0,mul(A4[0]*h,k1[i])),mul(A4[1]*h,k2)),mul(A4[2]*h,k3)));
k5 = f(x0+c[3]*h, add(add(add(add(y0,mul(A5[0]*h,k1[i])),mul(A5[1]*h,k2)),mul(A5[2]*h,k3)),mul(A5[3]*h,k4)));
k6 = f(x0+c[4]*h,add(add(add(add(add(y0,mul(A6[0]*h,k1[i])),mul(A6[1]*h,k2)),mul(A6[2]*h,k3)),mul(A6[3]*h,k4)),mul(A6[4]*h,k5)));
y1 = add(add(add(add(add(y0,mul(k1[i],h*b[0])),mul(k3,h*b[2])),mul(k4,h*b[3])),mul(k5,h*b[4])),mul(k6,h*b[5]));
k7 = f(x0+h,y1);
er = add(add(add(add(add(mul(k1[i],h*e[0]),mul(k3,h*e[2])),mul(k4,h*e[3])),mul(k5,h*e[4])),mul(k6,h*e[5])),mul(k7,h*e[6]));
if(typeof er === "number") erinf = abs(er);
else erinf = norminf(er);
if(erinf > tol) { // reject
h = 0.2*h*pow(tol/erinf,0.25);
if(x0+h === x0) {
ret.msg = "Step size became too small";
break;
}
continue;
}
ymid[i] = add(add(add(add(add(add(y0,
mul(k1[i],h*bm[0])),
mul(k3 ,h*bm[2])),
mul(k4 ,h*bm[3])),
mul(k5 ,h*bm[4])),
mul(k6 ,h*bm[5])),
mul(k7 ,h*bm[6]));
++i;
xs[i] = x0+h;
ys[i] = y1;
k1[i] = k7;
if(typeof event === "function") {
var yi,xl = x0,xr = x0+0.5*h,xi;
e1 = event(xr,ymid[i-1]);
ev = and(lt(e0,0),lt(0,e1));
if(!any(ev)) { xl = xr; xr = x0+h; e0 = e1; e1 = event(xr,y1); ev = and(lt(e0,0),lt(0,e1)); }
if(any(ev)) {
var xc, yc, en,ei;
var side=0, sl = 1.0, sr = 1.0;
while(1) {
if(typeof e0 === "number") xi = (sr*e1*xl-sl*e0*xr)/(sr*e1-sl*e0);
else {
xi = xr;
for(j=e0.length-1;j!==-1;--j) {
if(e0[j]<0 && e1[j]>0) xi = min(xi,(sr*e1[j]*xl-sl*e0[j]*xr)/(sr*e1[j]-sl*e0[j]));
}
}
if(xi <= xl || xi >= xr) break;
yi = ret._at(xi, i-1);
ei = event(xi,yi);
en = and(lt(e0,0),lt(0,ei));
if(any(en)) {
xr = xi;
e1 = ei;
ev = en;
sr = 1.0;
if(side === -1) sl *= 0.5;
else sl = 1.0;
side = -1;
} else {
xl = xi;
e0 = ei;
sl = 1.0;
if(side === 1) sr *= 0.5;
else sr = 1.0;
side = 1;
}
}
y1 = ret._at(0.5*(x0+xi),i-1);
ret.f[i] = f(xi,yi);
ret.x[i] = xi;
ret.y[i] = yi;
ret.ymid[i-1] = y1;
ret.events = ev;
ret.iterations = it;
return ret;
}
}
x0 += h;
y0 = y1;
e0 = e1;
h = min(0.8*h*pow(tol/erinf,0.25),4*h);
}
ret.iterations = it;
return ret;
};
// 11. Ax = b
numeric.LU = function(A, fast) {
fast = fast || false;
var abs = Math.abs;
var i, j, k, absAjk, Akk, Ak, Pk, Ai;
var max;
var n = A.length, n1 = n-1;
var P = new Array(n);
if(!fast) A = numeric.clone(A);
for (k = 0; k < n; ++k) {
Pk = k;
Ak = A[k];
max = abs(Ak[k]);
for (j = k + 1; j < n; ++j) {
absAjk = abs(A[j][k]);
if (max < absAjk) {
max = absAjk;
Pk = j;
}
}
P[k] = Pk;
if (Pk != k) {
A[k] = A[Pk];
A[Pk] = Ak;
Ak = A[k];
}
Akk = Ak[k];
for (i = k + 1; i < n; ++i) {
A[i][k] /= Akk;
}
for (i = k + 1; i < n; ++i) {
Ai = A[i];
for (j = k + 1; j < n1; ++j) {
Ai[j] -= Ai[k] * Ak[j];
++j;
Ai[j] -= Ai[k] * Ak[j];
}
if(j===n1) Ai[j] -= Ai[k] * Ak[j];
}
}
return {
LU: A,
P: P
};
};
numeric.LUsolve = function LUsolve(LUP, b) {
var i, j;
var LU = LUP.LU;
var n = LU.length;
var x = numeric.clone(b);
var P = LUP.P;
var Pi, LUi, LUii, tmp;
for (i=n-1;i!==-1;--i) x[i] = b[i];
for (i = 0; i < n; ++i) {
Pi = P[i];
if (P[i] !== i) {
tmp = x[i];
x[i] = x[Pi];
x[Pi] = tmp;
}
LUi = LU[i];
for (j = 0; j < i; ++j) {
x[i] -= x[j] * LUi[j];
}
}
for (i = n - 1; i >= 0; --i) {
LUi = LU[i];
for (j = i + 1; j < n; ++j) {
x[i] -= x[j] * LUi[j];
}
x[i] /= LUi[i];
}
return x;
};
numeric.solve = function solve(A,b,fast) { return numeric.LUsolve(numeric.LU(A,fast), b); };
// 12. Linear programming
numeric.echelonize = function echelonize(A) {
var s = numeric.dim(A), m = s[0], n = s[1];
var I = numeric.identity(m);
var P = Array(m);
var i,j,k,l,Ai,Ii,Z,a;
var abs = Math.abs;
var diveq = numeric.diveq;
A = numeric.clone(A);
for(i=0;i<m;++i) {
k = 0;
Ai = A[i];
Ii = I[i];
for(j=1;j<n;++j) if(abs(Ai[k])<abs(Ai[j])) k=j;
P[i] = k;
diveq(Ii,Ai[k]);
diveq(Ai,Ai[k]);
for(j=0;j<m;++j) if(j!==i) {
Z = A[j]; a = Z[k];
for(l=n-1;l!==-1;--l) Z[l] -= Ai[l]*a;
Z = I[j];
for(l=m-1;l!==-1;--l) Z[l] -= Ii[l]*a;
}
}
return {I:I, A:A, P:P};
};
numeric.__solveLP = function __solveLP(c,A,b,tol,maxit,x,flag) {
var sum = numeric.sum, log = numeric.log, mul = numeric.mul, sub = numeric.sub, dot = numeric.dot, div = numeric.div, add = numeric.add;
var m = c.length, n = b.length,y;
var unbounded = false, cb,i0=0;
var alpha = 1.0;
var f0,df0,AT = numeric.transpose(A), svd = numeric.svd,transpose = numeric.transpose,leq = numeric.leq, sqrt = Math.sqrt, abs = Math.abs;
var muleq = numeric.muleq;
var norm = numeric.norminf, any = numeric.any,min = Math.min;
var all = numeric.all, gt = numeric.gt;
var p = Array(m), A0 = Array(n),e=numeric.rep([n],1), H;
var solve = numeric.solve, z = sub(b,dot(A,x)),count;
var dotcc = dot(c,c);
var g;
for(count=i0;count<maxit;++count) {
var i,j,d;
for(i=n-1;i!==-1;--i) A0[i] = div(A[i],z[i]);
var A1 = transpose(A0);
for(i=m-1;i!==-1;--i) p[i] = (/*x[i]+*/sum(A1[i]));
alpha = 0.25*abs(dotcc/dot(c,p));
var a1 = 100*sqrt(dotcc/dot(p,p));
if(!isFinite(alpha) || alpha>a1) alpha = a1;
g = add(c,mul(alpha,p));
H = dot(A1,A0);
for(i=m-1;i!==-1;--i) H[i][i] += 1;
d = solve(H,div(g,alpha),true);
var t0 = div(z,dot(A,d));
var t = 1.0;
for(i=n-1;i!==-1;--i) if(t0[i]<0) t = min(t,-0.999*t0[i]);
y = sub(x,mul(d,t));
z = sub(b,dot(A,y));
if(!all(gt(z,0))) return { solution: x, message: "", iterations: count };
x = y;
if(alpha<tol) return { solution: y, message: "", iterations: count };
if(flag) {
var s = dot(c,g), Ag = dot(A,g);
unbounded = true;
for(i=n-1;i!==-1;--i) if(s*Ag[i]<0) { unbounded = false; break; }
} else {
if(x[m-1]>=0) unbounded = false;
else unbounded = true;
}
if(unbounded) return { solution: y, message: "Unbounded", iterations: count };
}
return { solution: x, message: "maximum iteration count exceeded", iterations:count };
};
numeric._solveLP = function _solveLP(c,A,b,tol,maxit) {
var m = c.length, n = b.length,y;
var sum = numeric.sum, log = numeric.log, mul = numeric.mul, sub = numeric.sub, dot = numeric.dot, div = numeric.div, add = numeric.add;
var c0 = numeric.rep([m],0).concat([1]);
var J = numeric.rep([n,1],-1);
var A0 = numeric.blockMatrix([[A , J ]]);
var b0 = b;
var y = numeric.rep([m],0).concat(Math.max(0,numeric.sup(numeric.neg(b)))+1);
var x0 = numeric.__solveLP(c0,A0,b0,tol,maxit,y,false);
var x = numeric.clone(x0.solution);
x.length = m;
var foo = numeric.inf(sub(b,dot(A,x)));
if(foo<0) { return { solution: NaN, message: "Infeasible", iterations: x0.iterations }; }
var ret = numeric.__solveLP(c, A, b, tol, maxit-x0.iterations, x, true);
ret.iterations += x0.iterations;
return ret;
};
numeric.solveLP = function solveLP(c,A,b,Aeq,beq,tol,maxit) {
if(typeof maxit === "undefined") maxit = 1000;
if(typeof tol === "undefined") tol = numeric.epsilon;
if(typeof Aeq === "undefined") return numeric._solveLP(c,A,b,tol,maxit);
var m = Aeq.length, n = Aeq[0].length, o = A.length;
var B = numeric.echelonize(Aeq);
var flags = numeric.rep([n],0);
var P = B.P;
var Q = [];
var i;
for(i=P.length-1;i!==-1;--i) flags[P[i]] = 1;
for(i=n-1;i!==-1;--i) if(flags[i]===0) Q.push(i);
var g = numeric.getRange;
var I = numeric.linspace(0,m-1), J = numeric.linspace(0,o-1);
var Aeq2 = g(Aeq,I,Q), A1 = g(A,J,P), A2 = g(A,J,Q), dot = numeric.dot, sub = numeric.sub;
var A3 = dot(A1,B.I);
var A4 = sub(A2,dot(A3,Aeq2)), b4 = sub(b,dot(A3,beq));
var c1 = Array(P.length), c2 = Array(Q.length);
for(i=P.length-1;i!==-1;--i) c1[i] = c[P[i]];
for(i=Q.length-1;i!==-1;--i) c2[i] = c[Q[i]];
var c4 = sub(c2,dot(c1,dot(B.I,Aeq2)));
var S = numeric._solveLP(c4,A4,b4,tol,maxit);
var x2 = S.solution;
if(x2!==x2) return S;
var x1 = dot(B.I,sub(beq,dot(Aeq2,x2)));
var x = Array(c.length);
for(i=P.length-1;i!==-1;--i) x[P[i]] = x1[i];
for(i=Q.length-1;i!==-1;--i) x[Q[i]] = x2[i];
return { solution: x, message:S.message, iterations: S.iterations };
};
numeric.MPStoLP = function MPStoLP(MPS) {
if(MPS instanceof String) { MPS.split('\n'); }
var state = 0;
var states = ['Initial state','NAME','ROWS','COLUMNS','RHS','BOUNDS','ENDATA'];
var n = MPS.length;
var i,j,z,N=0,rows = {}, sign = [], rl = 0, vars = {}, nv = 0;
var name;
var c = [], A = [], b = [];
function err(e) { throw new Error('MPStoLP: '+e+'\nLine '+i+': '+MPS[i]+'\nCurrent state: '+states[state]+'\n'); }
for(i=0;i<n;++i) {
z = MPS[i];
var w0 = z.match(/\S*/g);
var w = [];
for(j=0;j<w0.length;++j) if(w0[j]!=="") w.push(w0[j]);
if(w.length === 0) continue;
for(j=0;j<states.length;++j) if(z.substr(0,states[j].length) === states[j]) break;
if(j<states.length) {
state = j;
if(j===1) { name = w[1]; }
if(j===6) return { name:name, c:c, A:numeric.transpose(A), b:b, rows:rows, vars:vars };
continue;
}
switch(state) {
case 0: case 1: err('Unexpected line');
case 2:
switch(w[0]) {
case 'N': if(N===0) N = w[1]; else err('Two or more N rows'); break;
case 'L': rows[w[1]] = rl; sign[rl] = 1; b[rl] = 0; ++rl; break;
case 'G': rows[w[1]] = rl; sign[rl] = -1;b[rl] = 0; ++rl; break;
case 'E': rows[w[1]] = rl; sign[rl] = 0;b[rl] = 0; ++rl; break;
default: err('Parse error '+numeric.prettyPrint(w));
}
break;
case 3:
if(!vars.hasOwnProperty(w[0])) { vars[w[0]] = nv; c[nv] = 0; A[nv] = numeric.rep([rl],0); ++nv; }
var p = vars[w[0]];
for(j=1;j<w.length;j+=2) {
if(w[j] === N) { c[p] = parseFloat(w[j+1]); continue; }
var q = rows[w[j]];
A[p][q] = (sign[q]<0?-1:1)*parseFloat(w[j+1]);
}
break;
case 4:
for(j=1;j<w.length;j+=2) b[rows[w[j]]] = (sign[rows[w[j]]]<0?-1:1)*parseFloat(w[j+1]);
break;
case 5: /*FIXME*/ break;
case 6: err('Internal error');
}
}
err('Reached end of file without ENDATA');
};
// seedrandom.js version 2.0.
// Author: David Bau 4/2/2011
//
// Defines a method Math.seedrandom() that, when called, substitutes
// an explicitly seeded RC4-based algorithm for Math.random(). Also
// supports automatic seeding from local or network sources of entropy.
//
// Usage:
//
// <script src=http://davidbau.com/encode/seedrandom-min.js></script>
//
// Math.seedrandom('yipee'); Sets Math.random to a function that is
// initialized using the given explicit seed.
//
// Math.seedrandom(); Sets Math.random to a function that is
// seeded using the current time, dom state,
// and other accumulated local entropy.
// The generated seed string is returned.
//
// Math.seedrandom('yowza', true);
// Seeds using the given explicit seed mixed
// together with accumulated entropy.
//
// <script src="http://bit.ly/srandom-512"></script>
// Seeds using physical random bits downloaded
// from random.org.
//
// <script src="https://jsonlib.appspot.com/urandom?callback=Math.seedrandom">
// </script> Seeds using urandom bits from call.jsonlib.com,
// which is faster than random.org.
//
// Examples:
//
// Math.seedrandom("hello"); // Use "hello" as the seed.
// document.write(Math.random()); // Always 0.5463663768140734
// document.write(Math.random()); // Always 0.43973793770592234
// var rng1 = Math.random; // Remember the current prng.
//
// var autoseed = Math.seedrandom(); // New prng with an automatic seed.
// document.write(Math.random()); // Pretty much unpredictable.
//
// Math.random = rng1; // Continue "hello" prng sequence.
// document.write(Math.random()); // Always 0.554769432473455
//
// Math.seedrandom(autoseed); // Restart at the previous seed.
// document.write(Math.random()); // Repeat the 'unpredictable' value.
//
// Notes:
//
// Each time seedrandom('arg') is called, entropy from the passed seed
// is accumulated in a pool to help generate future seeds for the
// zero-argument form of Math.seedrandom, so entropy can be injected over
// time by calling seedrandom with explicit data repeatedly.
//
// On speed - This javascript implementation of Math.random() is about
// 3-10x slower than the built-in Math.random() because it is not native
// code, but this is typically fast enough anyway. Seeding is more expensive,
// especially if you use auto-seeding. Some details (timings on Chrome 4):
//
// Our Math.random() - avg less than 0.002 milliseconds per call
// seedrandom('explicit') - avg less than 0.5 milliseconds per call
// seedrandom('explicit', true) - avg less than 2 milliseconds per call
// seedrandom() - avg about 38 milliseconds per call
//
// LICENSE (BSD):
//
// Copyright 2010 David Bau, all rights reserved.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are met:
//
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of this module nor the names of its contributors may
// be used to endorse or promote products derived from this software
// without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
// "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
// LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
// A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
// OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
// SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
// LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
// DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
// THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
// (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
// OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
/**
* All code is in an anonymous closure to keep the global namespace clean.
*
* @param {number=} overflow
* @param {number=} startdenom
*/
// Patched by Seb so that seedrandom.js does not pollute the Math object.
// My tests suggest that doing Math.trouble = 1 makes Math lookups about 5%
// slower.
numeric.seedrandom = { pow:Math.pow, random:Math.random };
(function (pool, math, width, chunks, significance, overflow, startdenom) {
//
// seedrandom()
// This is the seedrandom function described above.
//
math['seedrandom'] = function seedrandom(seed, use_entropy) {
var key = [];
var arc4;
// Flatten the seed string or build one from local entropy if needed.
seed = mixkey(flatten(
use_entropy ? [seed, pool] :
arguments.length ? seed :
[new Date().getTime(), pool, window], 3), key);
// Use the seed to initialize an ARC4 generator.
arc4 = new ARC4(key);
// Mix the randomness into accumulated entropy.
mixkey(arc4.S, pool);
// Override Math.random
// This function returns a random double in [0, 1) that contains
// randomness in every bit of the mantissa of the IEEE 754 value.
math['random'] = function random() { // Closure to return a random double:
var n = arc4.g(chunks); // Start with a numerator n < 2 ^ 48
var d = startdenom; // and denominator d = 2 ^ 48.
var x = 0; // and no 'extra last byte'.
while (n < significance) { // Fill up all significant digits by
n = (n + x) * width; // shifting numerator and
d *= width; // denominator and generating a
x = arc4.g(1); // new least-significant-byte.
}
while (n >= overflow) { // To avoid rounding up, before adding
n /= 2; // last byte, shift everything
d /= 2; // right using integer math until
x >>>= 1; // we have exactly the desired bits.
}
return (n + x) / d; // Form the number within [0, 1).
};
// Return the seed that was used
return seed;
};
//
// ARC4
//
// An ARC4 implementation. The constructor takes a key in the form of
// an array of at most (width) integers that should be 0 <= x < (width).
//
// The g(count) method returns a pseudorandom integer that concatenates
// the next (count) outputs from ARC4. Its return value is a number x
// that is in the range 0 <= x < (width ^ count).
//
/** @constructor */
function ARC4(key) {
var t, u, me = this, keylen = key.length;
var i = 0, j = me.i = me.j = me.m = 0;
me.S = [];
me.c = [];
// The empty key [] is treated as [0].
if (!keylen) { key = [keylen++]; }
// Set up S using the standard key scheduling algorithm.
while (i < width) { me.S[i] = i++; }
for (i = 0; i < width; i++) {
t = me.S[i];
j = lowbits(j + t + key[i % keylen]);
u = me.S[j];
me.S[i] = u;
me.S[j] = t;
}
// The "g" method returns the next (count) outputs as one number.
me.g = function getnext(count) {
var s = me.S;
var i = lowbits(me.i + 1); var t = s[i];
var j = lowbits(me.j + t); var u = s[j];
s[i] = u;
s[j] = t;
var r = s[lowbits(t + u)];
while (--count) {
i = lowbits(i + 1); t = s[i];
j = lowbits(j + t); u = s[j];
s[i] = u;
s[j] = t;
r = r * width + s[lowbits(t + u)];
}
me.i = i;
me.j = j;
return r;
};
// For robust unpredictability discard an initial batch of values.
// See http://www.rsa.com/rsalabs/node.asp?id=2009
me.g(width);
}
//
// flatten()
// Converts an object tree to nested arrays of strings.
//
/** @param {Object=} result
* @param {string=} prop
* @param {string=} typ */
function flatten(obj, depth, result, prop, typ) {
result = [];
typ = typeof(obj);
if (depth && typ == 'object') {
for (prop in obj) {
if (prop.indexOf('S') < 5) { // Avoid FF3 bug (local/sessionStorage)
try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}
}
}
}
return (result.length ? result : obj + (typ != 'string' ? '\0' : ''));
}
//
// mixkey()
// Mixes a string seed into a key that is an array of integers, and
// returns a shortened string seed that is equivalent to the result key.
//
/** @param {number=} smear
* @param {number=} j */
function mixkey(seed, key, smear, j) {
seed += ''; // Ensure the seed is a string
smear = 0;
for (j = 0; j < seed.length; j++) {
key[lowbits(j)] =
lowbits((smear ^= key[lowbits(j)] * 19) + seed.charCodeAt(j));
}
seed = '';
for (j in key) { seed += String.fromCharCode(key[j]); }
return seed;
}
//
// lowbits()
// A quick "n mod width" for width a power of 2.
//
function lowbits(n) { return n & (width - 1); }
//
// The following constants are related to IEEE 754 limits.
//
startdenom = math.pow(width, chunks);
significance = math.pow(2, significance);
overflow = significance * 2;
//
// When seedrandom.js is loaded, we immediately mix a few bits
// from the built-in RNG into the entropy pool. Because we do
// not want to intefere with determinstic PRNG state later,
// seedrandom will not call math.random on its own again after
// initialization.
//
mixkey(math.random(), pool);
// End anonymous scope, and pass initial values.
}(
[], // pool: entropy pool starts empty
numeric.seedrandom, // math: package containing random, pow, and seedrandom
256, // width: each RC4 output is 0 <= x < 256
6, // chunks: at least six RC4 outputs for each double
52 // significance: there are 52 significant digits in a double
));
/* This file is a slightly modified version of quadprog.js from Alberto Santini.
* It has been slightly modified by Sébastien Loisel to make sure that it handles
* 0-based Arrays instead of 1-based Arrays.
* License is in resources/LICENSE.quadprog */
(function(exports) {
function base0to1(A) {
if(typeof A !== "object") { return A; }
var ret = [], i,n=A.length;
for(i=0;i<n;i++) ret[i+1] = base0to1(A[i]);
return ret;
}
function base1to0(A) {
if(typeof A !== "object") { return A; }
var ret = [], i,n=A.length;
for(i=1;i<n;i++) ret[i-1] = base1to0(A[i]);
return ret;
}
function dpori(a, lda, n) {
var i, j, k, kp1, t;
for (k = 1; k <= n; k = k + 1) {
a[k][k] = 1 / a[k][k];
t = -a[k][k];
//~ dscal(k - 1, t, a[1][k], 1);
for (i = 1; i < k; i = i + 1) {
a[i][k] = t * a[i][k];
}
kp1 = k + 1;
if (n < kp1) {
break;
}
for (j = kp1; j <= n; j = j + 1) {
t = a[k][j];
a[k][j] = 0;
//~ daxpy(k, t, a[1][k], 1, a[1][j], 1);
for (i = 1; i <= k; i = i + 1) {
a[i][j] = a[i][j] + (t * a[i][k]);
}
}
}
}
function dposl(a, lda, n, b) {
var i, k, kb, t;
for (k = 1; k <= n; k = k + 1) {
//~ t = ddot(k - 1, a[1][k], 1, b[1], 1);
t = 0;
for (i = 1; i < k; i = i + 1) {
t = t + (a[i][k] * b[i]);
}
b[k] = (b[k] - t) / a[k][k];
}
for (kb = 1; kb <= n; kb = kb + 1) {
k = n + 1 - kb;
b[k] = b[k] / a[k][k];
t = -b[k];
//~ daxpy(k - 1, t, a[1][k], 1, b[1], 1);
for (i = 1; i < k; i = i + 1) {
b[i] = b[i] + (t * a[i][k]);
}
}
}
function dpofa(a, lda, n, info) {
var i, j, jm1, k, t, s;
for (j = 1; j <= n; j = j + 1) {
info[1] = j;
s = 0;
jm1 = j - 1;
if (jm1 < 1) {
s = a[j][j] - s;
if (s <= 0) {
break;
}
a[j][j] = Math.sqrt(s);
} else {
for (k = 1; k <= jm1; k = k + 1) {
//~ t = a[k][j] - ddot(k - 1, a[1][k], 1, a[1][j], 1);
t = a[k][j];
for (i = 1; i < k; i = i + 1) {
t = t - (a[i][j] * a[i][k]);
}
t = t / a[k][k];
a[k][j] = t;
s = s + t * t;
}
s = a[j][j] - s;
if (s <= 0) {
break;
}
a[j][j] = Math.sqrt(s);
}
info[1] = 0;
}
}
function qpgen2(dmat, dvec, fddmat, n, sol, crval, amat,
bvec, fdamat, q, meq, iact, nact, iter, work, ierr) {
var i, j, l, l1, info, it1, iwzv, iwrv, iwrm, iwsv, iwuv, nvl, r, iwnbv,
temp, sum, t1, tt, gc, gs, nu,
t1inf, t2min,
vsmall, tmpa, tmpb,
go;
r = Math.min(n, q);
l = 2 * n + (r * (r + 5)) / 2 + 2 * q + 1;
vsmall = 1.0e-60;
do {
vsmall = vsmall + vsmall;
tmpa = 1 + 0.1 * vsmall;
tmpb = 1 + 0.2 * vsmall;
} while (tmpa <= 1 || tmpb <= 1);
for (i = 1; i <= n; i = i + 1) {
work[i] = dvec[i];
}
for (i = n + 1; i <= l; i = i + 1) {
work[i] = 0;
}
for (i = 1; i <= q; i = i + 1) {
iact[i] = 0;
}
info = [];
if (ierr[1] === 0) {
dpofa(dmat, fddmat, n, info);
if (info[1] !== 0) {
ierr[1] = 2;
return;
}
dposl(dmat, fddmat, n, dvec);
dpori(dmat, fddmat, n);
} else {
for (j = 1; j <= n; j = j + 1) {
sol[j] = 0;
for (i = 1; i <= j; i = i + 1) {
sol[j] = sol[j] + dmat[i][j] * dvec[i];
}
}
for (j = 1; j <= n; j = j + 1) {
dvec[j] = 0;
for (i = j; i <= n; i = i + 1) {
dvec[j] = dvec[j] + dmat[j][i] * sol[i];
}
}
}
crval[1] = 0;
for (j = 1; j <= n; j = j + 1) {
sol[j] = dvec[j];
crval[1] = crval[1] + work[j] * sol[j];
work[j] = 0;
for (i = j + 1; i <= n; i = i + 1) {
dmat[i][j] = 0;
}
}
crval[1] = -crval[1] / 2;
ierr[1] = 0;
iwzv = n;
iwrv = iwzv + n;
iwuv = iwrv + r;
iwrm = iwuv + r + 1;
iwsv = iwrm + (r * (r + 1)) / 2;
iwnbv = iwsv + q;
for (i = 1; i <= q; i = i + 1) {
sum = 0;
for (j = 1; j <= n; j = j + 1) {
sum = sum + amat[j][i] * amat[j][i];
}
work[iwnbv + i] = Math.sqrt(sum);
}
nact = 0;
iter[1] = 0;
iter[2] = 0;
function fn_goto_50() {
iter[1] = iter[1] + 1;
l = iwsv;
for (i = 1; i <= q; i = i + 1) {
l = l + 1;
sum = -bvec[i];
for (j = 1; j <= n; j = j + 1) {
sum = sum + amat[j][i] * sol[j];
}
if (Math.abs(sum) < vsmall) {
sum = 0;
}
if (i > meq) {
work[l] = sum;
} else {
work[l] = -Math.abs(sum);
if (sum > 0) {
for (j = 1; j <= n; j = j + 1) {
amat[j][i] = -amat[j][i];
}
bvec[i] = -bvec[i];
}
}
}
for (i = 1; i <= nact; i = i + 1) {
work[iwsv + iact[i]] = 0;
}
nvl = 0;
temp = 0;
for (i = 1; i <= q; i = i + 1) {
if (work[iwsv + i] < temp * work[iwnbv + i]) {
nvl = i;
temp = work[iwsv + i] / work[iwnbv + i];
}
}
if (nvl === 0) {
return 999;
}
return 0;
}
function fn_goto_55() {
for (i = 1; i <= n; i = i + 1) {
sum = 0;
for (j = 1; j <= n; j = j + 1) {
sum = sum + dmat[j][i] * amat[j][nvl];
}
work[i] = sum;
}
l1 = iwzv;
for (i = 1; i <= n; i = i + 1) {
work[l1 + i] = 0;
}
for (j = nact + 1; j <= n; j = j + 1) {
for (i = 1; i <= n; i = i + 1) {
work[l1 + i] = work[l1 + i] + dmat[i][j] * work[j];
}
}
t1inf = true;
for (i = nact; i >= 1; i = i - 1) {
sum = work[i];
l = iwrm + (i * (i + 3)) / 2;
l1 = l - i;
for (j = i + 1; j <= nact; j = j + 1) {
sum = sum - work[l] * work[iwrv + j];
l = l + j;
}
sum = sum / work[l1];
work[iwrv + i] = sum;
if (iact[i] < meq) {
// continue;
break;
}
if (sum < 0) {
// continue;
break;
}
t1inf = false;
it1 = i;
}
if (!t1inf) {
t1 = work[iwuv + it1] / work[iwrv + it1];
for (i = 1; i <= nact; i = i + 1) {
if (iact[i] < meq) {
// continue;
break;
}
if (work[iwrv + i] < 0) {
// continue;
break;
}
temp = work[iwuv + i] / work[iwrv + i];
if (temp < t1) {
t1 = temp;
it1 = i;
}
}
}
sum = 0;
for (i = iwzv + 1; i <= iwzv + n; i = i + 1) {
sum = sum + work[i] * work[i];
}
if (Math.abs(sum) <= vsmall) {
if (t1inf) {
ierr[1] = 1;
// GOTO 999
return 999;
} else {
for (i = 1; i <= nact; i = i + 1) {
work[iwuv + i] = work[iwuv + i] - t1 * work[iwrv + i];
}
work[iwuv + nact + 1] = work[iwuv + nact + 1] + t1;
// GOTO 700
return 700;
}
} else {
sum = 0;
for (i = 1; i <= n; i = i + 1) {
sum = sum + work[iwzv + i] * amat[i][nvl];
}
tt = -work[iwsv + nvl] / sum;
t2min = true;
if (!t1inf) {
if (t1 < tt) {
tt = t1;
t2min = false;
}
}
for (i = 1; i <= n; i = i + 1) {
sol[i] = sol[i] + tt * work[iwzv + i];
if (Math.abs(sol[i]) < vsmall) {
sol[i] = 0;
}
}
crval[1] = crval[1] + tt * sum * (tt / 2 + work[iwuv + nact + 1]);
for (i = 1; i <= nact; i = i + 1) {
work[iwuv + i] = work[iwuv + i] - tt * work[iwrv + i];
}
work[iwuv + nact + 1] = work[iwuv + nact + 1] + tt;
if (t2min) {
nact = nact + 1;
iact[nact] = nvl;
l = iwrm + ((nact - 1) * nact) / 2 + 1;
for (i = 1; i <= nact - 1; i = i + 1) {
work[l] = work[i];
l = l + 1;
}
if (nact === n) {
work[l] = work[n];
} else {
for (i = n; i >= nact + 1; i = i - 1) {
if (work[i] === 0) {
// continue;
break;
}
gc = Math.max(Math.abs(work[i - 1]), Math.abs(work[i]));
gs = Math.min(Math.abs(work[i - 1]), Math.abs(work[i]));
if (work[i - 1] >= 0) {
temp = Math.abs(gc * Math.sqrt(1 + gs * gs / (gc * gc)));
} else {
temp = -Math.abs(gc * Math.sqrt(1 + gs * gs / (gc * gc)));
}
gc = work[i - 1] / temp;
gs = work[i] / temp;
if (gc === 1) {
// continue;
break;
}
if (gc === 0) {
work[i - 1] = gs * temp;
for (j = 1; j <= n; j = j + 1) {
temp = dmat[j][i - 1];
dmat[j][i - 1] = dmat[j][i];
dmat[j][i] = temp;
}
} else {
work[i - 1] = temp;
nu = gs / (1 + gc);
for (j = 1; j <= n; j = j + 1) {
temp = gc * dmat[j][i - 1] + gs * dmat[j][i];
dmat[j][i] = nu * (dmat[j][i - 1] + temp) - dmat[j][i];
dmat[j][i - 1] = temp;
}
}
}
work[l] = work[nact];
}
} else {
sum = -bvec[nvl];
for (j = 1; j <= n; j = j + 1) {
sum = sum + sol[j] * amat[j][nvl];
}
if (nvl > meq) {
work[iwsv + nvl] = sum;
} else {
work[iwsv + nvl] = -Math.abs(sum);
if (sum > 0) {
for (j = 1; j <= n; j = j + 1) {
amat[j][nvl] = -amat[j][nvl];
}
bvec[nvl] = -bvec[nvl];
}
}
// GOTO 700
return 700;
}
}
return 0;
}
function fn_goto_797() {
l = iwrm + (it1 * (it1 + 1)) / 2 + 1;
l1 = l + it1;
if (work[l1] === 0) {
// GOTO 798
return 798;
}
gc = Math.max(Math.abs(work[l1 - 1]), Math.abs(work[l1]));
gs = Math.min(Math.abs(work[l1 - 1]), Math.abs(work[l1]));
if (work[l1 - 1] >= 0) {
temp = Math.abs(gc * Math.sqrt(1 + gs * gs / (gc * gc)));
} else {
temp = -Math.abs(gc * Math.sqrt(1 + gs * gs / (gc * gc)));
}
gc = work[l1 - 1] / temp;
gs = work[l1] / temp;
if (gc === 1) {
// GOTO 798
return 798;
}
if (gc === 0) {
for (i = it1 + 1; i <= nact; i = i + 1) {
temp = work[l1 - 1];
work[l1 - 1] = work[l1];
work[l1] = temp;
l1 = l1 + i;
}
for (i = 1; i <= n; i = i + 1) {
temp = dmat[i][it1];
dmat[i][it1] = dmat[i][it1 + 1];
dmat[i][it1 + 1] = temp;
}
} else {
nu = gs / (1 + gc);
for (i = it1 + 1; i <= nact; i = i + 1) {
temp = gc * work[l1 - 1] + gs * work[l1];
work[l1] = nu * (work[l1 - 1] + temp) - work[l1];
work[l1 - 1] = temp;
l1 = l1 + i;
}
for (i = 1; i <= n; i = i + 1) {
temp = gc * dmat[i][it1] + gs * dmat[i][it1 + 1];
dmat[i][it1 + 1] = nu * (dmat[i][it1] + temp) - dmat[i][it1 + 1];
dmat[i][it1] = temp;
}
}
return 0;
}
function fn_goto_798() {
l1 = l - it1;
for (i = 1; i <= it1; i = i + 1) {
work[l1] = work[l];
l = l + 1;
l1 = l1 + 1;
}
work[iwuv + it1] = work[iwuv + it1 + 1];
iact[it1] = iact[it1 + 1];
it1 = it1 + 1;
if (it1 < nact) {
// GOTO 797
return 797;
}
return 0;
}
function fn_goto_799() {
work[iwuv + nact] = work[iwuv + nact + 1];
work[iwuv + nact + 1] = 0;
iact[nact] = 0;
nact = nact - 1;
iter[2] = iter[2] + 1;
return 0;
}
go = 0;
while (true) {
go = fn_goto_50();
if (go === 999) {
return;
}
while (true) {
go = fn_goto_55();
if (go === 0) {
break;
}
if (go === 999) {
return;
}
if (go === 700) {
if (it1 === nact) {
fn_goto_799();
} else {
while (true) {
fn_goto_797();
go = fn_goto_798();
if (go !== 797) {
break;
}
}
fn_goto_799();
}
}
}
}
}
function solveQP(Dmat, dvec, Amat, bvec, meq, factorized) {
Dmat = base0to1(Dmat);
dvec = base0to1(dvec);
Amat = base0to1(Amat);
var i, n, q,
nact, r,
crval = [], iact = [], sol = [], work = [], iter = [],
message;
meq = meq || 0;
factorized = factorized ? base0to1(factorized) : [undefined, 0];
bvec = bvec ? base0to1(bvec) : [];
// In Fortran the array index starts from 1
n = Dmat.length - 1;
q = Amat[1].length - 1;
if (!bvec) {
for (i = 1; i <= q; i = i + 1) {
bvec[i] = 0;
}
}
for (i = 1; i <= q; i = i + 1) {
iact[i] = 0;
}
nact = 0;
r = Math.min(n, q);
for (i = 1; i <= n; i = i + 1) {
sol[i] = 0;
}
crval[1] = 0;
for (i = 1; i <= (2 * n + (r * (r + 5)) / 2 + 2 * q + 1); i = i + 1) {
work[i] = 0;
}
for (i = 1; i <= 2; i = i + 1) {
iter[i] = 0;
}
qpgen2(Dmat, dvec, n, n, sol, crval, Amat,
bvec, n, q, meq, iact, nact, iter, work, factorized);
message = "";
if (factorized[1] === 1) {
message = "constraints are inconsistent, no solution!";
}
if (factorized[1] === 2) {
message = "matrix D in quadratic function is not positive definite!";
}
return {
solution: base1to0(sol),
value: base1to0(crval),
unconstrained_solution: base1to0(dvec),
iterations: base1to0(iter),
iact: base1to0(iact),
message: message
};
}
exports.solveQP = solveQP;
}(numeric));
/*
Shanti Rao sent me this routine by private email. I had to modify it
slightly to work on Arrays instead of using a Matrix object.
It is apparently translated from http://stitchpanorama.sourceforge.net/Python/svd.py
*/
numeric.svd= function svd(A) {
var temp;
//Compute the thin SVD from G. H. Golub and C. Reinsch, Numer. Math. 14, 403-420 (1970)
var prec= numeric.epsilon; //Math.pow(2,-52) // assumes double prec
var tolerance= 1.e-64/prec;
var itmax= 50;
var c=0;
var i=0;
var j=0;
var k=0;
var l=0;
var u= numeric.clone(A);
var m= u.length;
var n= u[0].length;
if (m < n) throw "Need more rows than columns"
var e = new Array(n);
var q = new Array(n);
for (i=0; i<n; i++) e[i] = q[i] = 0.0;
var v = numeric.rep([n,n],0);
// v.zero();
function pythag(a,b)
{
a = Math.abs(a);
b = Math.abs(b);
if (a > b)
return a*Math.sqrt(1.0+(b*b/a/a))
else if (b == 0.0)
return a
return b*Math.sqrt(1.0+(a*a/b/b))
}
//Householder's reduction to bidiagonal form
var f= 0.0;
var g= 0.0;
var h= 0.0;
var x= 0.0;
var y= 0.0;
var z= 0.0;
var s= 0.0;
for (i=0; i < n; i++)
{
e[i]= g;
s= 0.0;
l= i+1;
for (j=i; j < m; j++)
s += (u[j][i]*u[j][i]);
if (s <= tolerance)
g= 0.0;
else
{
f= u[i][i];
g= Math.sqrt(s);
if (f >= 0.0) g= -g;
h= f*g-s;
u[i][i]=f-g;
for (j=l; j < n; j++)
{
s= 0.0;
for (k=i; k < m; k++)
s += u[k][i]*u[k][j];
f= s/h;
for (k=i; k < m; k++)
u[k][j]+=f*u[k][i];
}
}
q[i]= g;
s= 0.0;
for (j=l; j < n; j++)
s= s + u[i][j]*u[i][j];
if (s <= tolerance)
g= 0.0;
else
{
f= u[i][i+1];
g= Math.sqrt(s);
if (f >= 0.0) g= -g;
h= f*g - s;
u[i][i+1] = f-g;
for (j=l; j < n; j++) e[j]= u[i][j]/h;
for (j=l; j < m; j++)
{
s=0.0;
for (k=l; k < n; k++)
s += (u[j][k]*u[i][k]);
for (k=l; k < n; k++)
u[j][k]+=s*e[k];
}
}
y= Math.abs(q[i])+Math.abs(e[i]);
if (y>x)
x=y;
}
// accumulation of right hand gtransformations
for (i=n-1; i != -1; i+= -1)
{
if (g != 0.0)
{
h= g*u[i][i+1];
for (j=l; j < n; j++)
v[j][i]=u[i][j]/h;
for (j=l; j < n; j++)
{
s=0.0;
for (k=l; k < n; k++)
s += u[i][k]*v[k][j];
for (k=l; k < n; k++)
v[k][j]+=(s*v[k][i]);
}
}
for (j=l; j < n; j++)
{
v[i][j] = 0;
v[j][i] = 0;
}
v[i][i] = 1;
g= e[i];
l= i;
}
// accumulation of left hand transformations
for (i=n-1; i != -1; i+= -1)
{
l= i+1;
g= q[i];
for (j=l; j < n; j++)
u[i][j] = 0;
if (g != 0.0)
{
h= u[i][i]*g;
for (j=l; j < n; j++)
{
s=0.0;
for (k=l; k < m; k++) s += u[k][i]*u[k][j];
f= s/h;
for (k=i; k < m; k++) u[k][j]+=f*u[k][i];
}
for (j=i; j < m; j++) u[j][i] = u[j][i]/g;
}
else
for (j=i; j < m; j++) u[j][i] = 0;
u[i][i] += 1;
}
// diagonalization of the bidiagonal form
prec= prec*x;
for (k=n-1; k != -1; k+= -1)
{
for (var iteration=0; iteration < itmax; iteration++)
{ // test f splitting
var test_convergence = false;
for (l=k; l != -1; l+= -1)
{
if (Math.abs(e[l]) <= prec)
{ test_convergence= true;
break
}
if (Math.abs(q[l-1]) <= prec)
break
}
if (!test_convergence)
{ // cancellation of e[l] if l>0
c= 0.0;
s= 1.0;
var l1= l-1;
for (i =l; i<k+1; i++)
{
f= s*e[i];
e[i]= c*e[i];
if (Math.abs(f) <= prec)
break
g= q[i];
h= pythag(f,g);
q[i]= h;
c= g/h;
s= -f/h;
for (j=0; j < m; j++)
{
y= u[j][l1];
z= u[j][i];
u[j][l1] = y*c+(z*s);
u[j][i] = -y*s+(z*c);
}
}
}
// test f convergence
z= q[k];
if (l== k)
{ //convergence
if (z<0.0)
{ //q[k] is made non-negative
q[k]= -z;
for (j=0; j < n; j++)
v[j][k] = -v[j][k];
}
break //break out of iteration loop and move on to next k value
}
if (iteration >= itmax-1)
throw 'Error: no convergence.'
// shift from bottom 2x2 minor
x= q[l];
y= q[k-1];
g= e[k-1];
h= e[k];
f= ((y-z)*(y+z)+(g-h)*(g+h))/(2.0*h*y);
g= pythag(f,1.0);
if (f < 0.0)
f= ((x-z)*(x+z)+h*(y/(f-g)-h))/x;
else
f= ((x-z)*(x+z)+h*(y/(f+g)-h))/x;
// next QR transformation
c= 1.0;
s= 1.0;
for (i=l+1; i< k+1; i++)
{
g= e[i];
y= q[i];
h= s*g;
g= c*g;
z= pythag(f,h);
e[i-1]= z;
c= f/z;
s= h/z;
f= x*c+g*s;
g= -x*s+g*c;
h= y*s;
y= y*c;
for (j=0; j < n; j++)
{
x= v[j][i-1];
z= v[j][i];
v[j][i-1] = x*c+z*s;
v[j][i] = -x*s+z*c;
}
z= pythag(f,h);
q[i-1]= z;
c= f/z;
s= h/z;
f= c*g+s*y;
x= -s*g+c*y;
for (j=0; j < m; j++)
{
y= u[j][i-1];
z= u[j][i];
u[j][i-1] = y*c+z*s;
u[j][i] = -y*s+z*c;
}
}
e[l]= 0.0;
e[k]= f;
q[k]= x;
}
}
//vt= transpose(v)
//return (u,q,vt)
for (i=0;i<q.length; i++)
if (q[i] < prec) q[i] = 0;
//sort eigenvalues
for (i=0; i< n; i++)
{
//writeln(q)
for (j=i-1; j >= 0; j--)
{
if (q[j] < q[i])
{
// writeln(i,'-',j)
c = q[j];
q[j] = q[i];
q[i] = c;
for(k=0;k<u.length;k++) { temp = u[k][i]; u[k][i] = u[k][j]; u[k][j] = temp; }
for(k=0;k<v.length;k++) { temp = v[k][i]; v[k][i] = v[k][j]; v[k][j] = temp; }
// u.swapCols(i,j)
// v.swapCols(i,j)
i = j;
}
}
}
return {U:u,S:q,V:v}
};
});
var performanceNow = createCommonjsModule(function (module) {
// Generated by CoffeeScript 1.12.2
(function() {
var getNanoSeconds, hrtime, loadTime, moduleLoadTime, nodeLoadTime, upTime;
if ((typeof performance !== "undefined" && performance !== null) && performance.now) {
module.exports = function() {
return performance.now();
};
} else if ((typeof process !== "undefined" && process !== null) && process.hrtime) {
module.exports = function() {
return (getNanoSeconds() - nodeLoadTime) / 1e6;
};
hrtime = process.hrtime;
getNanoSeconds = function() {
var hr;
hr = hrtime();
return hr[0] * 1e9 + hr[1];
};
moduleLoadTime = getNanoSeconds();
upTime = process.uptime() * 1e9;
nodeLoadTime = moduleLoadTime - upTime;
} else if (Date.now) {
module.exports = function() {
return Date.now() - loadTime;
};
loadTime = Date.now();
} else {
module.exports = function() {
return new Date().getTime() - loadTime;
};
loadTime = new Date().getTime();
}
}).call(commonjsGlobal);
});
var root = typeof window === 'undefined' ? commonjsGlobal : window;
var vendors = ['moz', 'webkit'];
var suffix = 'AnimationFrame';
var raf = root['request' + suffix];
var caf = root['cancel' + suffix] || root['cancelRequest' + suffix];
for(var i = 0; !raf && i < vendors.length; i++) {
raf = root[vendors[i] + 'Request' + suffix];
caf = root[vendors[i] + 'Cancel' + suffix]
|| root[vendors[i] + 'CancelRequest' + suffix];
}
// Some versions of FF have rAF but not cAF
if(!raf || !caf) {
var last = 0
, id = 0
, queue = []
, frameDuration = 1000 / 60;
raf = function(callback) {
if(queue.length === 0) {
var _now = performanceNow()
, next = Math.max(0, frameDuration - (_now - last));
last = next + _now;
setTimeout(function() {
var cp = queue.slice(0);
// Clear queue here to prevent
// callbacks from appending listeners
// to the current frame's queue
queue.length = 0;
for(var i = 0; i < cp.length; i++) {
if(!cp[i].cancelled) {
try{
cp[i].callback(last);
} catch(e) {
setTimeout(function() { throw e }, 0);
}
}
}
}, Math.round(next));
}
queue.push({
handle: ++id,
callback: callback,
cancelled: false
});
return id
};
caf = function(handle) {
for(var i = 0; i < queue.length; i++) {
if(queue[i].handle === handle) {
queue[i].cancelled = true;
}
}
};
}
var raf_1 = function(fn) {
// Wrap in a new function to prevent
// `cancel` potentially being assigned
// to the native rAF function
return raf.call(root, fn)
};
var cancel = function() {
caf.apply(root, arguments);
};
var polyfill = function(object) {
if (!object) {
object = root;
}
object.requestAnimationFrame = raf;
object.cancelAnimationFrame = caf;
};
raf_1.cancel = cancel;
raf_1.polyfill = polyfill;
var promise = createCommonjsModule(function (module) {
(function (root) {
// Store setTimeout reference so promise-polyfill will be unaffected by
// other code modifying setTimeout (like sinon.useFakeTimers())
var setTimeoutFunc = setTimeout;
function noop() {}
// Polyfill for Function.prototype.bind
function bind(fn, thisArg) {
return function () {
fn.apply(thisArg, arguments);
};
}
function Promise(fn) {
if (!(this instanceof Promise)) throw new TypeError('Promises must be constructed via new');
if (typeof fn !== 'function') throw new TypeError('not a function');
this._state = 0;
this._handled = false;
this._value = undefined;
this._deferreds = [];
doResolve(fn, this);
}
function handle(self, deferred) {
while (self._state === 3) {
self = self._value;
}
if (self._state === 0) {
self._deferreds.push(deferred);
return;
}
self._handled = true;
Promise._immediateFn(function () {
var cb = self._state === 1 ? deferred.onFulfilled : deferred.onRejected;
if (cb === null) {
(self._state === 1 ? resolve : reject)(deferred.promise, self._value);
return;
}
var ret;
try {
ret = cb(self._value);
} catch (e) {
reject(deferred.promise, e);
return;
}
resolve(deferred.promise, ret);
});
}
function resolve(self, newValue) {
try {
// Promise Resolution Procedure: https://github.com/promises-aplus/promises-spec#the-promise-resolution-procedure
if (newValue === self) throw new TypeError('A promise cannot be resolved with itself.');
if (newValue && (typeof newValue === 'object' || typeof newValue === 'function')) {
var then = newValue.then;
if (newValue instanceof Promise) {
self._state = 3;
self._value = newValue;
finale(self);
return;
} else if (typeof then === 'function') {
doResolve(bind(then, newValue), self);
return;
}
}
self._state = 1;
self._value = newValue;
finale(self);
} catch (e) {
reject(self, e);
}
}
function reject(self, newValue) {
self._state = 2;
self._value = newValue;
finale(self);
}
function finale(self) {
if (self._state === 2 && self._deferreds.length === 0) {
Promise._immediateFn(function() {
if (!self._handled) {
Promise._unhandledRejectionFn(self._value);
}
});
}
for (var i = 0, len = self._deferreds.length; i < len; i++) {
handle(self, self._deferreds[i]);
}
self._deferreds = null;
}
function Handler(onFulfilled, onRejected, promise) {
this.onFulfilled = typeof onFulfilled === 'function' ? onFulfilled : null;
this.onRejected = typeof onRejected === 'function' ? onRejected : null;
this.promise = promise;
}
/**
* Take a potentially misbehaving resolver function and make sure
* onFulfilled and onRejected are only called once.
*
* Makes no guarantees about asynchrony.
*/
function doResolve(fn, self) {
var done = false;
try {
fn(function (value) {
if (done) return;
done = true;
resolve(self, value);
}, function (reason) {
if (done) return;
done = true;
reject(self, reason);
});
} catch (ex) {
if (done) return;
done = true;
reject(self, ex);
}
}
Promise.prototype['catch'] = function (onRejected) {
return this.then(null, onRejected);
};
Promise.prototype.then = function (onFulfilled, onRejected) {
var prom = new (this.constructor)(noop);
handle(this, new Handler(onFulfilled, onRejected, prom));
return prom;
};
Promise.all = function (arr) {
return new Promise(function (resolve, reject) {
if (!arr || typeof arr.length === 'undefined') throw new TypeError('Promise.all accepts an array');
var args = Array.prototype.slice.call(arr);
if (args.length === 0) return resolve([]);
var remaining = args.length;
function res(i, val) {
try {
if (val && (typeof val === 'object' || typeof val === 'function')) {
var then = val.then;
if (typeof then === 'function') {
then.call(val, function (val) {
res(i, val);
}, reject);
return;
}
}
args[i] = val;
if (--remaining === 0) {
resolve(args);
}
} catch (ex) {
reject(ex);
}
}
for (var i = 0; i < args.length; i++) {
res(i, args[i]);
}
});
};
Promise.resolve = function (value) {
if (value && typeof value === 'object' && value.constructor === Promise) {
return value;
}
return new Promise(function (resolve) {
resolve(value);
});
};
Promise.reject = function (value) {
return new Promise(function (resolve, reject) {
reject(value);
});
};
Promise.race = function (values) {
return new Promise(function (resolve, reject) {
for (var i = 0, len = values.length; i < len; i++) {
values[i].then(resolve, reject);
}
});
};
// Use polyfill for setImmediate for performance gains
Promise._immediateFn = (typeof setImmediate === 'function' && function (fn) { setImmediate(fn); }) ||
function (fn) {
setTimeoutFunc(fn, 0);
};
Promise._unhandledRejectionFn = function _unhandledRejectionFn(err) {
if (typeof console !== 'undefined' && console) {
console.warn('Possible Unhandled Promise Rejection:', err); // eslint-disable-line no-console
}
};
/**
* Set the immediate function to execute callbacks
* @param fn {function} Function to execute
* @deprecated
*/
Promise._setImmediateFn = function _setImmediateFn(fn) {
Promise._immediateFn = fn;
};
/**
* Change the function to execute on unhandled rejection
* @param {function} fn Function to execute on unhandled rejection
* @deprecated
*/
Promise._setUnhandledRejectionFn = function _setUnhandledRejectionFn(fn) {
Promise._unhandledRejectionFn = fn;
};
if ('object' !== 'undefined' && module.exports) {
module.exports = Promise;
} else if (!root.Promise) {
root.Promise = Promise;
}
})(commonjsGlobal);
});
// IE polyfill from MDN
(function () {
if (typeof window.CustomEvent === 'function') return false;
function CustomEvent (event, params) {
params = params || {bubbles : false, cancelable : false, detail: undefined};
var evt = document.createEvent('CustomEvent');
evt.initCustomEvent(event, params.bubbles, params.cancelable, params.detail);
return evt;
}
CustomEvent.prototype = window.Event.prototype;
window.CustomEvent = CustomEvent;
})();
function emitEvent(eventName, dispatcher=document) {
var evt = new CustomEvent(eventName, {'bubbles': true, 'cancelable': true});
dispatcher.dispatchEvent(evt);
}
/**
* Fast Fourier Transform
* 1D-FFT/IFFT, 2D-FFT/IFFT (radix-2)
*
* @author ryo / github.com/wellflat
* Based on https://github.com/wellflat/jslib with some tiny optimizations
*/
function FFT() {
var _n = 0, // order
_bitrev = null, // bit reversal table
_cstb = null; // sin/cos table
var _tre, _tim;
this.init = function (n) {
if(n !== 0 && (n & (n - 1)) === 0) {
_n = n;
_setVariables();
_makeBitReversal();
_makeCosSinTable();
} else {
throw new Error("init: radix-2 required");
}
};
// 1D-FFT
this.fft1d = function (re, im) {
fft(re, im, 1);
};
// 1D-IFFT
this.ifft1d = function (re, im) {
var n = 1/_n;
fft(re, im, -1);
for(var i=0; i<_n; i++) {
re[i] *= n;
im[i] *= n;
}
};
// 2D-FFT
this.fft2d = function (re, im) {
var i = 0;
// x-axis
for(var y=0; y<_n; y++) {
i = y*_n;
for(var x1=0; x1<_n; x1++) {
_tre[x1] = re[x1 + i];
_tim[x1] = im[x1 + i];
}
this.fft1d(_tre, _tim);
for(var x2=0; x2<_n; x2++) {
re[x2 + i] = _tre[x2];
im[x2 + i] = _tim[x2];
}
}
// y-axis
for(var x=0; x<_n; x++) {
for(var y1=0; y1<_n; y1++) {
i = x + y1*_n;
_tre[y1] = re[i];
_tim[y1] = im[i];
}
this.fft1d(_tre, _tim);
for(var y2=0; y2<_n; y2++) {
i = x + y2*_n;
re[i] = _tre[y2];
im[i] = _tim[y2];
}
}
};
// 2D-IFFT
this.ifft2d = function (re, im) {
var i = 0;
// x-axis
for(var y=0; y<_n; y++) {
i = y*_n;
for(var x1=0; x1<_n; x1++) {
_tre[x1] = re[x1 + i];
_tim[x1] = im[x1 + i];
}
this.ifft1d(_tre, _tim);
for(var x2=0; x2<_n; x2++) {
re[x2 + i] = _tre[x2];
im[x2 + i] = _tim[x2];
}
}
// y-axis
for(var x=0; x<_n; x++) {
for(var y1=0; y1<_n; y1++) {
i = x + y1*_n;
_tre[y1] = re[i];
_tim[y1] = im[i];
}
this.ifft1d(_tre, _tim);
for(var y2=0; y2<_n; y2++) {
i = x + y2*_n;
re[i] = _tre[y2];
im[i] = _tim[y2];
}
}
};
// core operation of FFT
function fft(re, im, inv) {
var d, h, ik, m, tmp, wr, wi, xr, xi,
n4 = _n >> 2;
// bit reversal
for(var l=0; l<_n; l++) {
m = _bitrev[l];
if(l < m) {
tmp = re[l];
re[l] = re[m];
re[m] = tmp;
tmp = im[l];
im[l] = im[m];
im[m] = tmp;
}
}
// butterfly operation
for(var k=1; k<_n; k<<=1) {
h = 0;
d = _n/(k << 1);
for(var j=0; j<k; j++) {
wr = _cstb[h + n4];
wi = inv*_cstb[h];
for(var i=j; i<_n; i+=(k<<1)) {
ik = i + k;
xr = wr*re[ik] + wi*im[ik];
xi = wr*im[ik] - wi*re[ik];
re[ik] = re[i] - xr;
re[i] += xr;
im[ik] = im[i] - xi;
im[i] += xi;
}
h += d;
}
}
}
// set variables
function _setVariables() {
if(typeof Uint8Array !== 'undefined') {
_bitrev = new Uint8Array(_n);
} else {
_bitrev = new Array(_n);
}
if(typeof Float64Array !== 'undefined') {
_cstb = new Float64Array(_n*1.25);
_tre = new Float64Array(_n*_n);
_tim = new Float64Array(_n*_n);
} else {
_cstb = new Array(_n*1.25);
_tre = new Array(_n*_n);
_tim = new Array(_n*_n);
}
}
// make bit reversal table
function _makeBitReversal() {
var i = 0,
j = 0,
k = 0;
_bitrev[0] = 0;
while(++i < _n) {
k = _n >> 1;
while(k <= j) {
j -= k;
k >>= 1;
}
j += k;
_bitrev[i] = j;
}
}
// make trigonometric function table
function _makeCosSinTable() {
var n2 = _n >> 1,
n4 = _n >> 2,
n8 = _n >> 3,
n2p4 = n2 + n4,
t = Math.sin(Math.PI/_n),
dc = 2*t*t,
ds = Math.sqrt(dc*(2 - dc)),
c = _cstb[n4] = 1,
s = _cstb[0] = 0;
t = 2*dc;
for(var i=1; i<n8; i++) {
c -= dc;
dc += t*c;
s += ds;
ds -= t*s;
_cstb[i] = s;
_cstb[n4 - i] = c;
}
if(n8 !== 0) {
_cstb[n8] = Math.sqrt(0.5);
}
for(var j=0; j<n4; j++) {
_cstb[n2 - j] = _cstb[j];
}
for(var k=0; k<n2p4; k++) {
_cstb[k + n2] = -_cstb[k];
}
}
}
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var nose_filter = {"real": [3.0408379415611857, 0.37822261363137938, 1.1747173276627942, 0.87791572866957501, 0.27429578524536991, -0.26015038230887205, -0.04589694540462394, 0.18194913988848616, -0.19035992880648842, -0.050064472206627651, -0.016354960260506177, 0.073013903204916478, 0.15053197342937383, -0.47378158951033317, -0.33333577915227425, -0.30434085338299055, 0.26372284406307878, -0.30434085338299449, -0.33333577915227836, -0.47378158951033028, 0.15053197342937505, 0.073013903204915576, -0.016354960260505706, -0.050064472206628768, -0.19035992880648842, 0.18194913988848541, -0.045896945404624932, -0.2601503823088735, 0.27429578524536952, 0.87791572866957457, 1.1747173276627942, 0.3782226136313796, 1.5638480130127614, -1.0502161590016221, -0.28144140655806793, 0.66007876209063499, 0.25575295594566605, -0.11471557758718753, 0.22751157962613866, -0.29100003355994186, 0.29242994865853178, 0.14950061311078749, -0.02214037256893809, 0.034503572794411914, -0.17412889405901469, 0.060297128338254534, -0.49717312826403576, -0.10585857030501357, 0.082780177430083327, -0.11056584899062352, -0.72499416196392785, -0.15612863751308359, -0.36586758725441215, -0.19718551141955715, -0.043434328775718851, -0.060442748560529294, 0.1383233017601592, -0.071714399164362744, 0.31725814504248484, 0.16801904131477274, 0.58675004339129755, 1.5155025161072819, 0.99232752650122635, -1.0129349058609656, -1.6725083187014358, -0.66077224091757791, 2.2217962254133496, 0.98390492917013095, -0.16319024909703178, 0.67271651276019184, 0.16380771710007475, 0.21989373735679621, -0.12296413131763459, -0.18224776807046256, -0.011168077595514938, 0.10364961453623285, 0.1359801303077682, -0.26339593722715721, 0.039396952561874886, -0.33866696253626483, -0.0043101841409601402, 0.17740469505625342, -0.10830858623812685, -0.33186051211466239, 0.12060535717228799, 0.084703474730635803, -0.086262426064740078, -0.1297477439897661, -0.28426475792188655, 0.21965961682575447, 0.24955999100642301, 0.46804088594167448, -0.46946217188769823, -0.31724338121882617, 1.7716903674840139, 0.56577881124465312, 0.71512595047089234, 0.4910867492003736, 0.92310119575914651, -1.0939934957719639, 0.18102793706565934, 0.35484595526186652, 0.48676804973393767, -0.097923922056211768, -7.8200063684236368e-05, -0.016095705887683227, -0.084263209727683391, 0.0080331646697531477, -0.044853168166469837, 0.0062170702455977547, -0.15890945005602863, 0.22815908460498888, 0.17110516400703918, -0.29052216822588434, -0.18224178792918044, -0.018421573557969844, 0.032535239746583795, -0.08121081614537759, -0.029175915115094032, 0.092929862040843081, 0.16824405476099044, -0.24679227625704581, 0.00030176170486908785, 0.023943010115746295, -0.43281940369171445, -0.57166836623813821, 1.2482467538506352, 0.74385331371246666, 0.54787745216002559, 0.92898941300038174, 0.54473301805335128, -0.4877077226718825, -0.40370312470951597, 0.39096527623299848, 0.12644205243911047, 0.0424168022733412, 0.049219693586430309, -0.077748186566067037, -0.043614575991677208, -0.0041635061718157101, 0.07897222152752259, 0.053944973270972973, 0.11232623315704468, -0.070445625631503542, -0.072057201177642652, 0.12706805404252855, -0.13757198545862262, -0.31639223989443899, -0.029240486244660611, 0.10973045554309782, 0.04102655016489614, 0.01891084247324943, -0.056922369420476487, 0.030805208457151782, -0.1512000567754726, -0.058122663069861934, -0.30506910575481916, -0.79033868813295383, 0.026308878650124864, 1.7521122327973906, 0.64566220514793682, 0.40042515638418263, -0.33461208848408402, -0.55369429571770823, -0.030140868003777126, 0.27230784814155334, 0.008194429787378334, -0.030645866021173498, 0.023928227792328404, 0.090706510487419734, -0.021569631345745226, -0.0064127815367693367, -0.026343653609827326, 0.0079365608693974798, -0.18791450411345401, 0.14319521757460194, 0.17003550871316017, -0.24661106106331201, -0.21167593067635404, -0.098206750946426211, -0.048592759447365123, 0.0028129255950110439, 0.049868939755416952, 0.039023237394102607, -0.0036267311717218496, -0.12930461632538415, -0.06741132095183785
var face_filter = {"real": [2.5919359538538909, 1.3480085770312511, -0.20482945082417442, 2.2477358192448036, 0.93540843887482139, 0.74314370383748074, 0.44299233336869565, 0.53646864525435445, -0.033677232548862526, -0.1522853308878499, -0.0031113453238400149, 0.052610669730581504, -0.0090421776029276455, 0.14571584983663624, 0.44057103654181279, -0.48335213540388067, -1.3567864542305328, -0.48335213540388222, 0.44057103654181745, 0.14571584983663588, -0.0090421776029276386, 0.052610669730583912, -0.0031113453238437146, -0.1522853308878454, -0.033677232548862526, 0.536468645254354, 0.44299233336869559, 0.74314370383748229, 0.9354084388748215, 2.2477358192448023, -0.20482945082417423, 1.3480085770312495, 2.0152106388329991, 0.85611134878653461, -1.3363494489312076, -0.52148568567931619, 1.2207493971968164, 0.88880185549210589, -0.12851357573552111, -0.1350280522901679, 0.041300904967699482, 0.44502243372725686, 0.029355734210915238, -0.51443976319946505, 0.08745222381708008, 1.2148708003194451, 1.1189080727093581, -0.27220544444671846, -0.36088426941083585, -0.093485947527556318, -0.9769818787641994, -0.68349100625395898, 0.024322257871818426, 0.60512811669399713, 0.15343788102432432, -0.4299366545774243, -0.15452787333937706, 0.9156200895039931, 1.19600272916941, 0.72364825206645089, 0.54200011692086325, 2.3400266438502029, -0.033608374945748302, 0.58898161413145322, 2.0269883277253808, 2.818789893714468, -3.5895244227646144, -3.5314332372596891, 2.0122812700890154, 0.93093181995227969, -0.96305400340897007, -0.73612667628472817, -0.053915776695886194, 0.42730242898842419, 0.029936824487282035, -0.35168293029190251, 0.25108420491884947, 0.8544524900293714, 0.16931894270710782, 0.0092385746333500125, 0.68672569869418298, 0.41915906104063394, -1.0984488703050921, -0.63697851900908631, 0.11186355371520935, 0.47269360156783113, 0.15279475225563477, -0.026106440237006989, -0.032262751173084157, 0.14542662300780329, 0.71981331903700141, 1.4137393979172745, 0.60857711312874896, -3.0736342072317173, -2.5537641666010327, 0.6337650914909162, 1.2343577579270657, 0.25345561236901865, -2.0331393954447585, 1.159193858429254, 3.0170447718709359, 0.49021233060315667, -0.684375328954414, -0.32927583863381799, -0.09284792777273311, -0.14740895498043241, -0.19413825853994604, 0.36919608239644319, 0.30546257655082493, -0.55256449500031701, -1.2130125640575424, 0.066961883917897494, -0.13876096422777703, 0.37902224678367341, 0.22718444978554084, 0.19963817528635963, 0.027529920247751867, -0.24231535965414738, -0.016338923407765684, 0.45136614923078927, 0.28975660783972312, -0.73094055491799104, -1.5465072446477164, -0.070769892332079726, 3.1701479989789885, 0.024916786279245037, -2.8717730703729369, -1.1681626968077414, -0.94600410103718435, -0.85872517244177848, 2.9516513032863374, 2.8131952593882126, -1.5261742763882251, -1.0558844683361728, 1.1680212024537544, 0.98450685108739822, 0.064067265719269059, -0.43727283330478184, -0.044395094277671916, 0.6179734700494115, 0.24878996343187737, -0.63891278340523816, -0.75864993025841965, -0.32304619466454659, -0.73387564471571265, -0.043145833390571785, 0.92391812888689884, 0.89946098537045804, 0.14871674926559622, -0.54822828954183223, -0.26728613142127311, 0.309011363128886, 0.21418689978013769, -0.52105157113820344, -1.0686411834884146, -1.3047927124000203, 1.0355627592914096, 2.9672746843849169, 1.9471218128812939, 0.36030875558033187, 0.22471825920653532, 1.3679256644146878, 2.3784795387427549, 0.73776440177250424, -2.2202952003703751, -0.98667153092188797, 0.60944427589951666, 0.29273424438530327, -0.054064553213066489, -0.1955430963609566, 0.13452976853580562, 0.17688857701463095, -0.02907863269662225, -0.037177619339377604, 0.22892611971691484, -0.22870850340942314, -0.41029268509332983, 0.061215349005760457, 0.37818604838169356, 0.34148146887082653, 0.099938245586444027, -0.099254338381423959, -0.11254516916626593, -0.2039622085642743, -0.20060216516957027, 0.30792957356810446, 1.1721236672075155, 0.56136417541067873, -2.3249600877666992, -2.4287881268668112, 2.0674326900187423, 2.8441
/*
* MOSSE correlation filter
*
* Optional parameters to constructor:
* drawResponse {canvasElement} : draws the correlation filter output on the given canvas element (default is none)
* psrThreshold {number} : peak-to-sidelobe-ratio threshold to use when updating filter while tracking (default is 10)
* eta {number} : adjusts how much new input affects the mosse filter, when updating filter while tracking
* number should be between 0 and 1 (default is 0.1)
* convertToGrayscale {boolean} : whether to convert canvas output to grayscale (default is true)
* if this is set to false, we assume all channels are equal and only grab values from red channel
*
* @author auduno / github.com/auduno
*/
function mosseFilter(params) {
var _filter, _top, _bottom;
var _fft;
var _w,_h;
var _im_part;
var _arrlen;
var _cc;
var _image_array;
this.psr_prev = undefined;
this.peak_prev = undefined;
var updateable = false;
if (!params) params = {};
// setup of canvas for drawing responses, if given
if (params.drawResponse === undefined) {
params.drawResponse = false;
} else {
if (params.drawResponse.tagName != 'CANVAS') {
params.drawResponse = false;
} else {
var responseContext = params.drawResponse.getContext('2d');
}
}
if (params.psrThreshold === undefined) params.psrThreshold = 10;
if (params.eta === undefined) params.eta = 0.10;
if (params.convertToGrayscale === undefined) params.convertToGrayscale = true;
this.load = function(filter) {
// initialize filter width and height
_w = filter.width;
_h = filter.height;
_arrlen = _w*_h;
_filter = [filter.real, filter.imag];
// handling top and bottom when they're not present
if (filter.top && filter.bottom) {
updateable = true;
_top = [filter.top.real, filter.top.imag];
_bottom = [filter.bottom.real, filter.bottom.imag];
}
// initialize fft to given width
_fft = new FFT();
_fft.init(filter.width);
// set up temporary variables
if(typeof Float64Array !== 'undefined') {
_im_part = new Float64Array(_arrlen);
_image_array = new Float64Array(_arrlen);
} else {
_im_part = new Array(_arrlen);
_image_array = new Array(_arrlen);
}
var canvas = document.createElement("canvas");
canvas.setAttribute('width', _w);
canvas.setAttribute('height', _h);
_cc = canvas.getContext('2d');
};
this.init = function(w,h) {
// initialize filter width and height for a blank filter
_w = w;
_h = h;
_arrlen = _w*_h;
_filter = [[],[]];
_top = [[],[]];
_bottom = [[],[]];
for (var i = 0;i < _arrlen;i++) {
_filter[0][i] = 0;
_filter[1][i] = 0;
_top[0][i] = 0;
_top[1][i] = 0;
_bottom[0][i] = 0;
_bottom[1][i] = 0;
}
updateable = true;
// initialize fft to given width
_fft = new FFT();
_fft.init(w);
// set up temporary variables
if(typeof Float64Array !== 'undefined') {
_im_part = new Float64Array(_arrlen);
} else {
_im_part = new Array(_arrlen);
}
var canvas = document.createElement("canvas");
canvas.setAttribute('width', _w);
canvas.setAttribute('height', _h);
_cc = canvas.getContext('2d');
};
// fft function
this.fft = function(array) {
// not in-place
var cn = new Array(_arrlen);
for (var i = 0;i < _arrlen;i++) {
cn[i] = 0.0;
}
_fft.fft2d(array,cn);
return [array, cn];
};
// fft function
this.fft_inplace = function(array) {
// in-place
for (var i = 0;i < _arrlen;i++) {
_im_part[i] = 0.0;
}
_fft.fft2d(array,_im_part);
return [array, _im_part];
};
this.ifft = function(rn, cn) {
// in-place
_fft.ifft2d(rn, cn);
return rn;
};
// peak to sidelobe ratio function (optional)
this.psr = function(array) {
// proper
var sum = 0;
var max = 0;
var maxpos = [0, 0];
var sdo = 0;
var val;
for (var x = 0;x < _w;x++) {
for (var y = 0;y < _h;y++) {
val = array[(y*_w)+x];
sum += val;
sdo += (val*val);
if (max < val) {
max = val;
maxpos = [x,y];
}
}
}
// subtract values around peak
for (var x = -5;x < 6;x++) {
for (var y = -5;y < 6;y++) {
if (Math.sqrt(x*x+y*y) < 5) {
val = array[((maxpos[1]+y)*_w)+(maxpos[0]+x)];
sdo -= (val*val);
sum -= val;
}
}
}
var mean = sum/array.length;
var sd = Math.sqrt((sdo/array.length)-(mean*mean));
// get mean/variance of output around peak
var psr = (max-mean)/sd;
return psr;
};
this.getResponse = function(imageData) {
// in-place
// preprocess
var prepImage = preprocess(imageData);
prepImage = cosine_window(prepImage);
// filter
var res = this.fft_inplace(prepImage);
// elementwise multiplication with filter
complex_mult_inplace(res, _filter);
// do inverse 2d fft
var filtered = this.ifft(res[0],res[1]);
return filtered;
};
this.track = function(input, left, top, width, height, updateFilter, gaussianPrior, calcPSR) {
// finds position of filter in input image
if (!_filter) {
console.log("Mosse-filter needs to be initialized or trained before starting tracking.");
return false;
}
if (input.tagName == "VIDEO" || input.tagName == "IMG") {
// scale selection according to original source image
var videoLeft = Math.round((left/input.width)*input.videoWidth);
var videoTop = Math.round((top/input.height)*input.videoHeight);
var videoWidth = Math.round((width/input.width)*input.videoWidth);
var videoHeight = Math.round((height/input.height)*input.videoHeight);
_cc.drawImage(input, videoLeft, videoTop, videoWidth, videoHeight, 0, 0, _w, _h);
} else if (input.tagName == "CANVAS") {
_cc.drawImage(input, left, top, width, height, 0, 0, _w, _h);
}
var image = _cc.getImageData(0,0,_w,_h);
var id = image.data;
if (params.convertToGrayscale) {
// convert to grayscale
for (var i = 0;i < _arrlen;i++) {
_image_array[i] = id[(4*i)]*0.3;
_image_array[i] += id[(4*i)+1]*0.59;
_image_array[i] += id[(4*i)+2]*0.11;
}
} else {
// use only one channel
for (var i = 0;i < _arrlen;i++) {
_image_array[i] = id[(4*i)];
}
}
// preprocess
var prepImage = preprocess(_image_array);
prepImage = cosine_window(prepImage);
// filter
var res = this.fft_inplace(prepImage);
// elementwise multiplication with filter
var nures = complex_mult(res, _filter);
// do inverse 2d fft
var filtered = this.ifft(nures[0],nures[1]);
// find max and min
var max = 0;
var min = 0;
var maxpos = [0, 0];
//method using centered gaussian prior
if (gaussianPrior) {
var prior, dx, dy;
var variance = 128;
for (var x = 0;x < _w;x++) {
for (var y = 0;y < _h;y++) {
dx = x - _w/2;
dy = y - _h/2;
prior = Math.exp(-0.5*((dx*dx)+(dy*dy))/variance);
if ((filtered[(y*_w)+x]*prior) > max) {
max = filtered[(y*_w)+x]*prior;
maxpos = [x,y];
}
if (filtered[(y*_w)+x] < min) {
min = filtered[(y*_w)+x];
}
}
}
} else {
for (var x = 0;x < _w;x++) {
for (var y = 0;y < _h;y++) {
if (filtered[(y*_w)+x] > max) {
max = filtered[(y*_w)+x];
maxpos = [x,y];
}
if (filtered[(y*_w)+x] < min) {
min = filtered[(y*_w)+x];
}
}
}
}
this.peak_prev = max;
if (params.drawResponse) {
// draw response
var diff = max-min;
var dc = document.createElement('canvas');
dc.setAttribute('width', 32);
dc.setAttribute('height', 32);
var dcc = dc.getContext('2d');
var psci = dcc.createImageData(32, 32);
var pscidata = psci.data;
for (var j = 0;j < 32*32;j++) {
//draw with priors
//var val = filtered[j]*Math.exp(-0.5*(((j%_w - _w/2)*(j%_w -_w/2))+((Math.floor(j/_h)-(_h/2))*(Math.floor(j/_h)-(_h/2))))/128);
var val = filtered[j];
val = Math.round((val+Math.abs(min))*(255/diff));
pscidata[j*4] = val;
pscidata[(j*4)+1] = val;
pscidata[(j*4)+2] = val;
pscidata[(j*4)+3] = 255;
}
dcc.putImageData(psci, 0, 0);
responseContext.drawImage(dc, left, top, width, width);
}
if (calcPSR) {
this.psr_prev = this.psr(filtered);
}
if (updateFilter) {
if (!updateable) {
console.log("The loaded filter does not support updating. Ignoring parameter 'updateFilter'.");
} else {
if (calcPSR) {
var psr = this.psr_prev;
} else {
var psr = this.psr(filtered);
}
if (psr > params.psrThreshold) {
// create target
var target = [];
var nux = maxpos[0];
var nuy = maxpos[1];
for (var x = 0;x < _w;x++) {
for (var y = 0;y < _h;y++) {
target[(y*_w)+x] = Math.exp(-(((x-nux)*(x-nux))+((y-nuy)*(y-nuy)))/(2*2));
}
}
//fft target
target = this.fft(target);
// create filter
var res_conj = complex_conj(res);
var fuTop = complex_mult(target,res_conj);
var fuBottom = complex_mult(res,res_conj);
// add up
var eta = params.eta;
for (var i = 0;i < _arrlen;i++) {
_top[0][i] = eta*fuTop[0][i] + (1-eta)*_top[0][i];
_top[1][i] = eta*fuTop[1][i] + (1-eta)*_top[1][i];
_bottom[0][i] = eta*fuBottom[0][i] + (1-eta)*_bottom[0][i];
_bottom[1][i] = eta*fuBottom[1][i] + (1-eta)*_bottom[1][i];
}
_filter = complex_div(_top,_bottom);
}
}
}
/*if (psr < 5) {
maxpos = [_w/2,_h/2];
}*/
maxpos[0] = maxpos[0]*(width/_w);
maxpos[1] = maxpos[1]*(width/_h);
// check if output is strong enough
// if not, return false?
if (max < 0) {
return false;
} else {
return maxpos;
}
};
this.train = function(input, left, top, width, height) {
if (!updateable) {
console.log("The loaded filter does not support updating. Unable to do training.");
return false;
}
if (input.tagName == "VIDEO" || input.tagName == "IMG") {
// scale selection according to original source image
var videoLeft = Math.round((left/input.width)*input.videoWidth);
var videoTop = Math.round((top/input.height)*input.videoHeight);
var videoWidth = Math.round((width/input.width)*input.videoWidth);
var videoHeight = Math.round((height/input.height)*input.videoHeight);
_cc.drawImage(input, videoLeft, videoTop, videoWidth, videoHeight, 0, 0, _w, _h);
} else if (input.tagName == "CANVAS") {
_cc.drawImage(input, left, top, width, height, 0, 0, _w, _h);
}
var image = _cc.getImageData(0,0,_w,_h);
var id = image.data;
// convert to grayscale
for (var i = 0;i < _arrlen;i++) {
_image_array[i] = id[(4*i)]*0.3;
_image_array[i] += id[(4*i)+1]*0.59;
_image_array[i] += id[(4*i)+2]*0.11;
}
// preprocess
var prepImage = preprocess(_image_array);
prepImage = cosine_window(prepImage);
// create target
var target = [];
var nux = _w/2;
var nuy = _h/2;
for (var x = 0;x < _w;x++) {
for (var y = 0;y < _h;y++) {
target[(y*_w)+x] = Math.exp(-(((x-nux)*(x-nux))+((y-nuy)*(y-nuy)))/(2*2));
}
}
//fft target
target = this.fft(target);
// filter
var res = this.fft(prepImage);
// create filter
var res_conj = complex_conj(res);
var fuTop = complex_mult(target,res_conj);
var fuBottom = complex_mult(res,res_conj);
// add up
var eta = params.eta;
for (var i = 0;i < _arrlen;i++) {
_top[0][i] = eta*fuTop[0][i] + (1-eta)*_top[0][i];
_top[1][i] = eta*fuTop[1][i] + (1-eta)*_top[1][i];
_bottom[0][i] = eta*fuBottom[0][i] + (1-eta)*_bottom[0][i];
_bottom[1][i] = eta*fuBottom[1][i] + (1-eta)*_bottom[1][i];
}
_filter = complex_div(_top,_bottom);
return true;
};
var preprocess = function(array) {
// in-place
// log adjusting
for (var i = 0;i < _arrlen;i++) {
array[i] = Math.log(array[i]+1);
}
// normalize to mean 0 and norm 1
var mean = 0;
for (var i = 0;i < _arrlen;i++) {
mean += array[i];
}
mean /= _arrlen;
for (var i = 0;i < _arrlen;i++) {
array[i] -= mean;
}
var norm = 0.0;
for (var i = 0;i < _arrlen;i++) {
norm += (array[i]*array[i]);
}
norm = Math.sqrt(norm);
if (norm !== 0) {
for (var i = 0;i < _arrlen;i++) {
array[i] /= norm;
}
}
return array;
};
var cosine_window = function(array) {
// calculate rect cosine window (in-place)
var pos = 0;
for (var i = 0;i < _w;i++) {
for (var j = 0;j < _h;j++) {
//pos = (i%_w)+(j*_w);
var cww = Math.sin((Math.PI*i)/(_w-1));
var cwh = Math.sin((Math.PI*j)/(_h-1));
array[pos] = Math.min(cww,cwh)*array[pos];
pos++;
}
}
return array;
};
var complex_mult = function(cn1, cn2) {
// not in-place
var re_part = new Array(_w);
var im_part = new Array(_w);
var nucn = [re_part, im_part];
for (var r = 0;r < _arrlen;r++) {
nucn[0][r] = (cn1[0][r]*cn2[0][r]) - (cn1[1][r]*cn2[1][r]);
nucn[1][r] = (cn1[0][r]*cn2[1][r]) + (cn1[1][r]*cn2[0][r]);
}
return nucn;
};
var complex_mult_inplace = function(cn1, cn2) {
// in-place
var temp1, temp2;
for (var r = 0;r < _arrlen;r++) {
temp1 = (cn1[0][r]*cn2[0][r]) - (cn1[1][r]*cn2[1][r]);
temp2 = (cn1[0][r]*cn2[1][r]) + (cn1[1][r]*cn2[0][r]);
cn1[0][r] = temp1;
cn1[1][r] = temp2;
}
};
var complex_conj = function(cn) {
// not in-place (TODO)
var nucn = [[],[]];
for (var i = 0;i < _arrlen;i++) {
nucn[0][i] = cn[0][i];
nucn[1][i] = -cn[1][i];
}
return nucn;
};
var complex_div = function(cn1, cn2) {
// not in-place (TODO)
var nucn = [[],[]];
for (var r = 0;r < _arrlen;r++) {
nucn[0][r] = ((cn1[0][r]*cn2[0][r])+(cn1[1][r]*cn2[1][r])) / ((cn2[0][r]*cn2[0][r]) + (cn2[1][r]*cn2[1][r]));
nucn[1][r] = ((cn1[1][r]*cn2[0][r])-(cn1[0][r]*cn2[1][r])) / ((cn2[0][r]*cn2[0][r]) + (cn2[1][r]*cn2[1][r]));
}
return nucn;
};
}
var mosse = {
mosseFilter : mosseFilter,
filters : {
left_eye_filter : left_eye_filter,
right_eye_filter : right_eye_filter,
mouth_filter : mouth_filter,
nose_filter : nose_filter,
face_filter : face_filter
}
};
var jsfeat_1 = createCommonjsModule(function (module) {
/**
* @author Eugene Zatepyakin / http://inspirit.ru/
*/
// namespace ?
var jsfeat = jsfeat || { REVISION: 'ALPHA' };
/**
* @author Eugene Zatepyakin / http://inspirit.ru/
*/
(function(global) {
"use strict";
//
// CONSTANTS
var EPSILON = 0.0000001192092896;
var FLT_MIN = 1E-37;
// implementation from CCV project
// currently working only with u8,s32,f32
var U8_t = 0x0100,
S32_t = 0x0200,
F32_t = 0x0400,
S64_t = 0x0800,
F64_t = 0x1000;
var C1_t = 0x01,
C2_t = 0x02,
C3_t = 0x03,
C4_t = 0x04;
var _data_type_size = new Int32Array([ -1, 1, 4, -1, 4, -1, -1, -1, 8, -1, -1, -1, -1, -1, -1, -1, 8 ]);
var get_data_type = (function () {
return function(type) {
return (type & 0xFF00);
}
})();
var get_channel = (function () {
return function(type) {
return (type & 0xFF);
}
})();
var get_data_type_size = (function () {
return function(type) {
return _data_type_size[(type & 0xFF00) >> 8];
}
})();
// color conversion
var COLOR_RGBA2GRAY = 0;
var COLOR_RGB2GRAY = 1;
var COLOR_BGRA2GRAY = 2;
var COLOR_BGR2GRAY = 3;
// box blur option
var BOX_BLUR_NOSCALE = 0x01;
// svd options
var SVD_U_T = 0x01;
var SVD_V_T = 0x02;
var data_t = (function () {
function data_t(size_in_bytes, buffer) {
// we need align size to multiple of 8
this.size = ((size_in_bytes + 7) | 0) & -8;
if (typeof buffer === "undefined") {
this.buffer = new ArrayBuffer(this.size);
} else {
this.buffer = buffer;
this.size = buffer.length;
}
this.u8 = new Uint8Array(this.buffer);
this.i32 = new Int32Array(this.buffer);
this.f32 = new Float32Array(this.buffer);
this.f64 = new Float64Array(this.buffer);
}
return data_t;
})();
var matrix_t = (function () {
// columns, rows, data_type
function matrix_t(c, r, data_type, data_buffer) {
this.type = get_data_type(data_type)|0;
this.channel = get_channel(data_type)|0;
this.cols = c|0;
this.rows = r|0;
if (typeof data_buffer === "undefined") {
this.allocate();
} else {
this.buffer = data_buffer;
// data user asked for
this.data = this.type&U8_t ? this.buffer.u8 : (this.type&S32_t ? this.buffer.i32 : (this.type&F32_t ? this.buffer.f32 : this.buffer.f64));
}
}
matrix_t.prototype.allocate = function() {
// clear references
delete this.data;
delete this.buffer;
//
this.buffer = new data_t((this.cols * get_data_type_size(this.type) * this.channel) * this.rows);
this.data = this.type&U8_t ? this.buffer.u8 : (this.type&S32_t ? this.buffer.i32 : (this.type&F32_t ? this.buffer.f32 : this.buffer.f64));
};
matrix_t.prototype.copy_to = function(other) {
var od = other.data, td = this.data;
var i = 0, n = (this.cols*this.rows*this.channel)|0;
for(; i < n-4; i+=4) {
od[i] = td[i];
od[i+1] = td[i+1];
od[i+2] = td[i+2];
od[i+3] = td[i+3];
}
for(; i < n; ++i) {
od[i] = td[i];
}
};
matrix_t.prototype.resize = function(c, r, ch) {
if (typeof ch === "undefined") { ch = this.channel; }
// relocate buffer only if new size doesnt fit
var new_size = (c * get_data_type_size(this.type) * ch) * r;
if(new_size > this.buffer.size) {
this.cols = c;
this.rows = r;
this.channel = ch;
this.allocate();
} else {
this.cols = c;
this.rows = r;
this.channel = ch;
}
};
return matrix_t;
})();
var pyramid_t = (function () {
function pyramid_t(levels) {
this.levels = levels|0;
this.data = new Array(levels);
this.pyrdown = jsfeat.imgproc.pyrdown;
}
pyramid_t.prototype.allocate = function(start_w, start_h, data_type) {
var i = this.levels;
while(--i >= 0) {
this.data[i] = new matrix_t(start_w >> i, start_h >> i, data_type);
}
};
pyramid_t.prototype.build = function(input, skip_first_level) {
if (typeof skip_first_level === "undefined") { skip_first_level = true; }
// just copy data to first level
var i = 2, a = input, b = this.data[0];
if(!skip_first_level) {
var j=input.cols*input.rows;
while(--j >= 0) {
b.data[j] = input.data[j];
}
}
b = this.data[1];
this.pyrdown(a, b);
for(; i < this.levels; ++i) {
a = b;
b = this.data[i];
this.pyrdown(a, b);
}
};
return pyramid_t;
})();
var keypoint_t = (function () {
function keypoint_t(x,y,score,level,angle) {
if (typeof x === "undefined") { x=0; }
if (typeof y === "undefined") { y=0; }
if (typeof score === "undefined") { score=0; }
if (typeof level === "undefined") { level=0; }
if (typeof angle === "undefined") { angle=-1.0; }
this.x = x;
this.y = y;
this.score = score;
this.level = level;
this.angle = angle;
}
return keypoint_t;
})();
// data types
global.U8_t = U8_t;
global.S32_t = S32_t;
global.F32_t = F32_t;
global.S64_t = S64_t;
global.F64_t = F64_t;
// data channels
global.C1_t = C1_t;
global.C2_t = C2_t;
global.C3_t = C3_t;
global.C4_t = C4_t;
// popular formats
global.U8C1_t = U8_t | C1_t;
global.U8C3_t = U8_t | C3_t;
global.U8C4_t = U8_t | C4_t;
global.F32C1_t = F32_t | C1_t;
global.F32C2_t = F32_t | C2_t;
global.S32C1_t = S32_t | C1_t;
global.S32C2_t = S32_t | C2_t;
// constants
global.EPSILON = EPSILON;
global.FLT_MIN = FLT_MIN;
// color convert
global.COLOR_RGBA2GRAY = COLOR_RGBA2GRAY;
global.COLOR_RGB2GRAY = COLOR_RGB2GRAY;
global.COLOR_BGRA2GRAY = COLOR_BGRA2GRAY;
global.COLOR_BGR2GRAY = COLOR_BGR2GRAY;
// options
global.BOX_BLUR_NOSCALE = BOX_BLUR_NOSCALE;
global.SVD_U_T = SVD_U_T;
global.SVD_V_T = SVD_V_T;
global.get_data_type = get_data_type;
global.get_channel = get_channel;
global.get_data_type_size = get_data_type_size;
global.data_t = data_t;
global.matrix_t = matrix_t;
global.pyramid_t = pyramid_t;
global.keypoint_t = keypoint_t;
})(jsfeat);
/**
* @author Eugene Zatepyakin / http://inspirit.ru/
*/
(function(global) {
"use strict";
//
var cache = (function() {
// very primitive array cache, still need testing if it helps
// of course V8 has its own powerful cache sys but i'm not sure
// it caches several multichannel 640x480 buffer creations each frame
var _pool_node_t = (function () {
function _pool_node_t(size_in_bytes) {
this.next = null;
this.data = new jsfeat.data_t(size_in_bytes);
this.size = this.data.size;
this.buffer = this.data.buffer;
this.u8 = this.data.u8;
this.i32 = this.data.i32;
this.f32 = this.data.f32;
this.f64 = this.data.f64;
}
_pool_node_t.prototype.resize = function(size_in_bytes) {
delete this.data;
this.data = new jsfeat.data_t(size_in_bytes);
this.size = this.data.size;
this.buffer = this.data.buffer;
this.u8 = this.data.u8;
this.i32 = this.data.i32;
this.f32 = this.data.f32;
this.f64 = this.data.f64;
};
return _pool_node_t;
})();
var _pool_head, _pool_tail;
var _pool_size = 0;
return {
allocate: function(capacity, data_size) {
_pool_head = _pool_tail = new _pool_node_t(data_size);
for (var i = 0; i < capacity; ++i) {
var node = new _pool_node_t(data_size);
_pool_tail = _pool_tail.next = node;
_pool_size++;
}
},
get_buffer: function(size_in_bytes) {
// assume we have enough free nodes
var node = _pool_head;
_pool_head = _pool_head.next;
_pool_size--;
if(size_in_bytes > node.size) {
node.resize(size_in_bytes);
}
return node;
},
put_buffer: function(node) {
_pool_tail = _pool_tail.next = node;
_pool_size++;
}
};
})();
global.cache = cache;
// for now we dont need more than 30 buffers
// if having cache sys really helps we can add auto extending sys
cache.allocate(30, 640*4);
})(jsfeat);
/**
* @author Eugene Zatepyakin / http://inspirit.ru/
*/
(function(global) {
"use strict";
//
var math = (function() {
var qsort_stack = new Int32Array(48*2);
return {
get_gaussian_kernel: function(size, sigma, kernel, data_type) {
var i=0,x=0.0,t=0.0,sigma_x=0.0,scale_2x=0.0;
var sum = 0.0;
var kern_node = jsfeat.cache.get_buffer(size<<2);
var _kernel = kern_node.f32;//new Float32Array(size);
if((size&1) == 1 && size <= 7 && sigma <= 0) {
switch(size>>1) {
case 0:
_kernel[0] = 1.0;
sum = 1.0;
break;
case 1:
_kernel[0] = 0.25, _kernel[1] = 0.5, _kernel[2] = 0.25;
sum = 0.25+0.5+0.25;
break;
case 2:
_kernel[0] = 0.0625, _kernel[1] = 0.25, _kernel[2] = 0.375,
_kernel[3] = 0.25, _kernel[4] = 0.0625;
sum = 0.0625+0.25+0.375+0.25+0.0625;
break;
case 3:
_kernel[0] = 0.03125, _kernel[1] = 0.109375, _kernel[2] = 0.21875,
_kernel[3] = 0.28125, _kernel[4] = 0.21875, _kernel[5] = 0.109375, _kernel[6] = 0.03125;
sum = 0.03125+0.109375+0.21875+0.28125+0.21875+0.109375+0.03125;
break;
}
} else {
sigma_x = sigma > 0 ? sigma : ((size-1)*0.5 - 1.0)*0.3 + 0.8;
scale_2x = -0.5/(sigma_x*sigma_x);
for( ; i < size; ++i )
{
x = i - (size-1)*0.5;
t = Math.exp(scale_2x*x*x);
_kernel[i] = t;
sum += t;
}
}
if(data_type & jsfeat.U8_t) {
// int based kernel
sum = 256.0/sum;
for (i = 0; i < size; ++i) {
kernel[i] = (_kernel[i] * sum + 0.5)|0;
}
} else {
// classic kernel
sum = 1.0/sum;
for (i = 0; i < size; ++i) {
kernel[i] = _kernel[i] * sum;
}
}
jsfeat.cache.put_buffer(kern_node);
},
// model is 3x3 matrix_t
perspective_4point_transform: function(model, src_x0, src_y0, dst_x0, dst_y0,
src_x1, src_y1, dst_x1, dst_y1,
src_x2, src_y2, dst_x2, dst_y2,
src_x3, src_y3, dst_x3, dst_y3) {
var t1 = src_x0;
var t2 = src_x2;
var t4 = src_y1;
var t5 = t1 * t2 * t4;
var t6 = src_y3;
var t7 = t1 * t6;
var t8 = t2 * t7;
var t9 = src_y2;
var t10 = t1 * t9;
var t11 = src_x1;
var t14 = src_y0;
var t15 = src_x3;
var t16 = t14 * t15;
var t18 = t16 * t11;
var t20 = t15 * t11 * t9;
var t21 = t15 * t4;
var t24 = t15 * t9;
var t25 = t2 * t4;
var t26 = t6 * t2;
var t27 = t6 * t11;
var t28 = t9 * t11;
var t30 = 1.0 / (t21-t24 - t25 + t26 - t27 + t28);
var t32 = t1 * t15;
var t35 = t14 * t11;
var t41 = t4 * t1;
var t42 = t6 * t41;
var t43 = t14 * t2;
var t46 = t16 * t9;
var t48 = t14 * t9 * t11;
var t51 = t4 * t6 * t2;
var t55 = t6 * t14;
var Hr0 = -(t8-t5 + t10 * t11 - t11 * t7 - t16 * t2 + t18 - t20 + t21 * t2) * t30;
var Hr1 = (t5 - t8 - t32 * t4 + t32 * t9 + t18 - t2 * t35 + t27 * t2 - t20) * t30;
var Hr2 = t1;
var Hr3 = (-t9 * t7 + t42 + t43 * t4 - t16 * t4 + t46 - t48 + t27 * t9 - t51) * t30;
var Hr4 = (-t42 + t41 * t9 - t55 * t2 + t46 - t48 + t55 * t11 + t51 - t21 * t9) * t30;
var Hr5 = t14;
var Hr6 = (-t10 + t41 + t43 - t35 + t24 - t21 - t26 + t27) * t30;
var Hr7 = (-t7 + t10 + t16 - t43 + t27 - t28 - t21 + t25) * t30;
t1 = dst_x0;
t2 = dst_x2;
t4 = dst_y1;
t5 = t1 * t2 * t4;
t6 = dst_y3;
t7 = t1 * t6;
t8 = t2 * t7;
t9 = dst_y2;
t10 = t1 * t9;
t11 = dst_x1;
t14 = dst_y0;
t15 = dst_x3;
t16 = t14 * t15;
t18 = t16 * t11;
t20 = t15 * t11 * t9;
t21 = t15 * t4;
t24 = t15 * t9;
t25 = t2 * t4;
t26 = t6 * t2;
t27 = t6 * t11;
t28 = t9 * t11;
t30 = 1.0 / (t21-t24 - t25 + t26 - t27 + t28);
t32 = t1 * t15;
t35 = t14 * t11;
t41 = t4 * t1;
t42 = t6 * t41;
t43 = t14 * t2;
t46 = t16 * t9;
t48 = t14 * t9 * t11;
t51 = t4 * t6 * t2;
t55 = t6 * t14;
var Hl0 = -(t8-t5 + t10 * t11 - t11 * t7 - t16 * t2 + t18 - t20 + t21 * t2) * t30;
var Hl1 = (t5 - t8 - t32 * t4 + t32 * t9 + t18 - t2 * t35 + t27 * t2 - t20) * t30;
var Hl2 = t1;
var Hl3 = (-t9 * t7 + t42 + t43 * t4 - t16 * t4 + t46 - t48 + t27 * t9 - t51) * t30;
var Hl4 = (-t42 + t41 * t9 - t55 * t2 + t46 - t48 + t55 * t11 + t51 - t21 * t9) * t30;
var Hl5 = t14;
var Hl6 = (-t10 + t41 + t43 - t35 + t24 - t21 - t26 + t27) * t30;
var Hl7 = (-t7 + t10 + t16 - t43 + t27 - t28 - t21 + t25) * t30;
// the following code computes R = Hl * inverse Hr
t2 = Hr4-Hr7*Hr5;
t4 = Hr0*Hr4;
t5 = Hr0*Hr5;
t7 = Hr3*Hr1;
t8 = Hr2*Hr3;
t10 = Hr1*Hr6;
var t12 = Hr2*Hr6;
t15 = 1.0 / (t4-t5*Hr7-t7+t8*Hr7+t10*Hr5-t12*Hr4);
t18 = -Hr3+Hr5*Hr6;
var t23 = -Hr3*Hr7+Hr4*Hr6;
t28 = -Hr1+Hr2*Hr7;
var t31 = Hr0-t12;
t35 = Hr0*Hr7-t10;
t41 = -Hr1*Hr5+Hr2*Hr4;
var t44 = t5-t8;
var t47 = t4-t7;
t48 = t2*t15;
var t49 = t28*t15;
var t50 = t41*t15;
var mat = model.data;
mat[0] = Hl0*t48+Hl1*(t18*t15)-Hl2*(t23*t15);
mat[1] = Hl0*t49+Hl1*(t31*t15)-Hl2*(t35*t15);
mat[2] = -Hl0*t50-Hl1*(t44*t15)+Hl2*(t47*t15);
mat[3] = Hl3*t48+Hl4*(t18*t15)-Hl5*(t23*t15);
mat[4] = Hl3*t49+Hl4*(t31*t15)-Hl5*(t35*t15);
mat[5] = -Hl3*t50-Hl4*(t44*t15)+Hl5*(t47*t15);
mat[6] = Hl6*t48+Hl7*(t18*t15)-t23*t15;
mat[7] = Hl6*t49+Hl7*(t31*t15)-t35*t15;
mat[8] = -Hl6*t50-Hl7*(t44*t15)+t47*t15;
},
// The current implementation was derived from *BSD system qsort():
// Copyright (c) 1992, 1993
// The Regents of the University of California. All rights reserved.
qsort: function(array, low, high, cmp) {
var isort_thresh = 7;
var t,ta,tb,tc;
var sp = 0,left=0,right=0,i=0,n=0,m=0,ptr=0,ptr2=0,d=0;
var left0=0,left1=0,right0=0,right1=0,pivot=0,a=0,b=0,c=0,swap_cnt=0;
var stack = qsort_stack;
if( (high-low+1) <= 1 ) return;
stack[0] = low;
stack[1] = high;
while( sp >= 0 ) {
left = stack[sp<<1];
right = stack[(sp<<1)+1];
sp--;
for(;;) {
n = (right - left) + 1;
if( n <= isort_thresh ) {
//insert_sort:
for( ptr = left + 1; ptr <= right; ptr++ ) {
for( ptr2 = ptr; ptr2 > left && cmp(array[ptr2],array[ptr2-1]); ptr2--) {
t = array[ptr2];
array[ptr2] = array[ptr2-1];
array[ptr2-1] = t;
}
}
break;
} else {
swap_cnt = 0;
left0 = left;
right0 = right;
pivot = left + (n>>1);
if( n > 40 ) {
d = n >> 3;
a = left, b = left + d, c = left + (d<<1);
ta = array[a],tb = array[b],tc = array[c];
left = cmp(ta, tb) ? (cmp(tb, tc) ? b : (cmp(ta, tc) ? c : a))
: (cmp(tc, tb) ? b : (cmp(ta, tc) ? a : c));
a = pivot - d, b = pivot, c = pivot + d;
ta = array[a],tb = array[b],tc = array[c];
pivot = cmp(ta, tb) ? (cmp(tb, tc) ? b : (cmp(ta, tc) ? c : a))
: (cmp(tc, tb) ? b : (cmp(ta, tc) ? a : c));
a = right - (d<<1), b = right - d, c = right;
ta = array[a],tb = array[b],tc = array[c];
right = cmp(ta, tb) ? (cmp(tb, tc) ? b : (cmp(ta, tc) ? c : a))
: (cmp(tc, tb) ? b : (cmp(ta, tc) ? a : c));
}
a = left, b = pivot, c = right;
ta = array[a],tb = array[b],tc = array[c];
pivot = cmp(ta, tb) ? (cmp(tb, tc) ? b : (cmp(ta, tc) ? c : a))
: (cmp(tc, tb) ? b : (cmp(ta, tc) ? a : c));
if( pivot != left0 ) {
t = array[pivot];
array[pivot] = array[left0];
array[left0] = t;
pivot = left0;
}
left = left1 = left0 + 1;
right = right1 = right0;
ta = array[pivot];
for(;;) {
while( left <= right && !cmp(ta, array[left]) ) {
if( !cmp(array[left], ta) ) {
if( left > left1 ) {
t = array[left1];
array[left1] = array[left];
array[left] = t;
}
swap_cnt = 1;
left1++;
}
left++;
}
while( left <= right && !cmp(array[right], ta) ) {
if( !cmp(ta, array[right]) ) {
if( right < right1 ) {
t = array[right1];
array[right1] = array[right];
array[right] = t;
}
swap_cnt = 1;
right1--;
}
right--;
}
if( left > right ) break;
t = array[left];
array[left] = array[right];
array[right] = t;
swap_cnt = 1;
left++;
right--;
}
if( swap_cnt == 0 ) {
left = left0, right = right0;
//goto insert_sort;
for( ptr = left + 1; ptr <= right; ptr++ ) {
for( ptr2 = ptr; ptr2 > left && cmp(array[ptr2],array[ptr2-1]); ptr2--) {
t = array[ptr2];
array[ptr2] = array[ptr2-1];
array[ptr2-1] = t;
}
}
break;
}
n = Math.min( (left1 - left0), (left - left1) );
m = (left-n)|0;
for( i = 0; i < n; ++i,++m ) {
t = array[left0+i];
array[left0+i] = array[m];
array[m] = t;
}
n = Math.min( (right0 - right1), (right1 - right) );
m = (right0-n+1)|0;
for( i = 0; i < n; ++i,++m ) {
t = array[left+i];
array[left+i] = array[m];
array[m] = t;
}
n = (left - left1);
m = (right1 - right);
if( n > 1 ) {
if( m > 1 ) {
if( n > m ) {
++sp;
stack[sp<<1] = left0;
stack[(sp<<1)+1] = left0 + n - 1;
left = right0 - m + 1, right = right0;
} else {
++sp;
stack[sp<<1] = right0 - m + 1;
stack[(sp<<1)+1] = right0;
left = left0, right = left0 + n - 1;
}
} else {
left = left0, right = left0 + n - 1;
}
}
else if( m > 1 )
left = right0 - m + 1, right = right0;
else
break;
}
}
}
},
median: function(array, low, high) {
var w;
var middle=0,ll=0,hh=0,median=(low+high)>>1;
for (;;) {
if (high <= low) return array[median];
if (high == (low + 1)) {
if (array[low] > array[high]) {
w = array[low];
array[low] = array[high];
array[high] = w;
}
return array[median];
}
middle = ((low + high) >> 1);
if (array[middle] > array[high]) {
w = array[middle];
array[middle] = array[high];
array[high] = w;
}
if (array[low] > array[high]) {
w = array[low];
array[low] = array[high];
array[high] = w;
}
if (array[middle] > array[low]) {
w = array[middle];
array[middle] = array[low];
array[low] = w;
}
ll = (low + 1);
w = array[middle];
array[middle] = array[ll];
array[ll] = w;
hh = high;
for (;;) {
do ++ll; while (array[low] > array[ll]);
do --hh; while (array[hh] > array[low]);
if (hh < ll) break;
w = array[ll];
array[ll] = array[hh];
array[hh] = w;
}
w = array[low];
array[low] = array[hh];
array[hh] = w;
if (hh <= median)
low = ll;
else if (hh >= median)
high = (hh - 1);
}
return 0;
}
};
})();
global.math = math;
})(jsfeat);
/**
* @author Eugene Zatepyakin / http://inspirit.ru/
*
*/
(function(global) {
"use strict";
//
var matmath = (function() {
return {
identity: function(M, value) {
if (typeof value === "undefined") { value=1; }
var src=M.data;
var rows=M.rows, cols=M.cols, cols_1=(cols+1)|0;
var len = rows * cols;
var k = len;
while(--len >= 0) src[len] = 0.0;
len = k;
k = 0;
while(k < len) {
src[k] = value;
k = k + cols_1;
}
},
transpose: function(At, A) {
var i=0,j=0,nrows=A.rows,ncols=A.cols;
var Ai=0,Ati=0,pAt=0;
var ad=A.data,atd=At.data;
for (; i < nrows; Ati += 1, Ai += ncols, i++) {
pAt = Ati;
for (j = 0; j < ncols; pAt += nrows, j++) atd[pAt] = ad[Ai+j];
}
},
// C = A * B
multiply: function(C, A, B) {
var i=0,j=0,k=0;
var Ap=0,pA=0,pB=0,p_B=0,Cp=0;
var ncols=A.cols,nrows=A.rows,mcols=B.cols;
var ad=A.data,bd=B.data,cd=C.data;
var sum=0.0;
for (; i < nrows; Ap += ncols, i++) {
for (p_B = 0, j = 0; j < mcols; Cp++, p_B++, j++) {
pB = p_B;
pA = Ap;
sum = 0.0;
for (k = 0; k < ncols; pA++, pB += mcols, k++) {
sum += ad[pA] * bd[pB];
}
cd[Cp] = sum;
}
}
},
// C = A * B'
multiply_ABt: function(C, A, B) {
var i=0,j=0,k=0;
var Ap=0,pA=0,pB=0,Cp=0;
var ncols=A.cols,nrows=A.rows,mrows=B.rows;
var ad=A.data,bd=B.data,cd=C.data;
var sum=0.0;
for (; i < nrows; Ap += ncols, i++) {
for (pB = 0, j = 0; j < mrows; Cp++, j++) {
pA = Ap;
sum = 0.0;
for (k = 0; k < ncols; pA++, pB++, k++) {
sum += ad[pA] * bd[pB];
}
cd[Cp] = sum;
}
}
},
// C = A' * B
multiply_AtB: function(C, A, B) {
var i=0,j=0,k=0;
var Ap=0,pA=0,pB=0,p_B=0,Cp=0;
var ncols=A.cols,nrows=A.rows,mcols=B.cols;
var ad=A.data,bd=B.data,cd=C.data;
var sum=0.0;
for (; i < ncols; Ap++, i++) {
for (p_B = 0, j = 0; j < mcols; Cp++, p_B++, j++) {
pB = p_B;
pA = Ap;
sum = 0.0;
for (k = 0; k < nrows; pA += ncols, pB += mcols, k++) {
sum += ad[pA] * bd[pB];
}
cd[Cp] = sum;
}
}
},
// C = A * A'
multiply_AAt: function(C, A) {
var i=0,j=0,k=0;
var pCdiag=0,p_A=0,pA=0,pB=0,pC=0,pCt=0;
var ncols=A.cols,nrows=A.rows;
var ad=A.data,cd=C.data;
var sum=0.0;
for (; i < nrows; pCdiag += nrows + 1, p_A = pA, i++) {
pC = pCdiag;
pCt = pCdiag;
pB = p_A;
for (j = i; j < nrows; pC++, pCt += nrows, j++) {
pA = p_A;
sum = 0.0;
for (k = 0; k < ncols; k++) {
sum += ad[pA++] * ad[pB++];
}
cd[pC] = sum;
cd[pCt] = sum;
}
}
},
// C = A' * A
multiply_AtA: function(C, A) {
var i=0,j=0,k=0;
var p_A=0,pA=0,pB=0,p_C=0,pC=0,p_CC=0;
var ncols=A.cols,nrows=A.rows;
var ad=A.data,cd=C.data;
var sum=0.0;
for (; i < ncols; p_C += ncols, i++) {
p_A = i;
p_CC = p_C + i;
pC = p_CC;
for (j = i; j < ncols; pC++, p_CC += ncols, j++) {
pA = p_A;
pB = j;
sum = 0.0;
for (k = 0; k < nrows; pA += ncols, pB += ncols, k++) {
sum += ad[pA] * ad[pB];
}
cd[pC] = sum;
cd[p_CC] = sum;
}
}
},
// various small matrix operations
identity_3x3: function(M, value) {
if (typeof value === "undefined") { value=1; }
var dt=M.data;
dt[0] = dt[4] = dt[8] = value;
dt[1] = dt[2] = dt[3] = 0;
dt[5] = dt[6] = dt[7] = 0;
},
invert_3x3: function(from, to) {
var A = from.data, invA = to.data;
var t1 = A[4];
var t2 = A[8];
var t4 = A[5];
var t5 = A[7];
var t8 = A[0];
var t9 = t8*t1;
var t11 = t8*t4;
var t13 = A[3];
var t14 = A[1];
var t15 = t13*t14;
var t17 = A[2];
var t18 = t13*t17;
var t20 = A[6];
var t21 = t20*t14;
var t23 = t20*t17;
var t26 = 1.0/(t9*t2-t11*t5-t15*t2+t18*t5+t21*t4-t23*t1);
invA[0] = (t1*t2-t4*t5)*t26;
invA[1] = -(t14*t2-t17*t5)*t26;
invA[2] = -(-t14*t4+t17*t1)*t26;
invA[3] = -(t13*t2-t4*t20)*t26;
invA[4] = (t8*t2-t23)*t26;
invA[5] = -(t11-t18)*t26;
invA[6] = -(-t13*t5+t1*t20)*t26;
invA[7] = -(t8*t5-t21)*t26;
invA[8] = (t9-t15)*t26;
},
// C = A * B
multiply_3x3: function(C, A, B) {
var Cd=C.data, Ad=A.data, Bd=B.data;
var m1_0 = Ad[0], m1_1 = Ad[1], m1_2 = Ad[2];
var m1_3 = Ad[3], m1_4 = Ad[4], m1_5 = Ad[5];
var m1_6 = Ad[6], m1_7 = Ad[7], m1_8 = Ad[8];
var m2_0 = Bd[0], m2_1 = Bd[1], m2_2 = Bd[2];
var m2_3 = Bd[3], m2_4 = Bd[4], m2_5 = Bd[5];
var m2_6 = Bd[6], m2_7 = Bd[7], m2_8 = Bd[8];
Cd[0] = m1_0 * m2_0 + m1_1 * m2_3 + m1_2 * m2_6;
Cd[1] = m1_0 * m2_1 + m1_1 * m2_4 + m1_2 * m2_7;
Cd[2] = m1_0 * m2_2 + m1_1 * m2_5 + m1_2 * m2_8;
Cd[3] = m1_3 * m2_0 + m1_4 * m2_3 + m1_5 * m2_6;
Cd[4] = m1_3 * m2_1 + m1_4 * m2_4 + m1_5 * m2_7;
Cd[5] = m1_3 * m2_2 + m1_4 * m2_5 + m1_5 * m2_8;
Cd[6] = m1_6 * m2_0 + m1_7 * m2_3 + m1_8 * m2_6;
Cd[7] = m1_6 * m2_1 + m1_7 * m2_4 + m1_8 * m2_7;
Cd[8] = m1_6 * m2_2 + m1_7 * m2_5 + m1_8 * m2_8;
},
mat3x3_determinant: function(M) {
var md=M.data;
return md[0] * md[4] * md[8] -
md[0] * md[5] * md[7] -
md[3] * md[1] * md[8] +
md[3] * md[2] * md[7] +
md[6] * md[1] * md[5] -
md[6] * md[2] * md[4];
},
determinant_3x3: function(M11, M12, M13,
M21, M22, M23,
M31, M32, M33) {
return M11 * M22 * M33 - M11 * M23 * M32 -
M21 * M12 * M33 + M21 * M13 * M32 +
M31 * M12 * M23 - M31 * M13 * M22;
}
};
})();
global.matmath = matmath;
})(jsfeat);
/**
* @author Eugene Zatepyakin / http://inspirit.ru/
*
*/
(function(global) {
"use strict";
//
var linalg = (function() {
var swap = function(A, i0, i1, t) {
t = A[i0];
A[i0] = A[i1];
A[i1] = t;
};
var hypot = function(a, b) {
a = Math.abs(a);
b = Math.abs(b);
if( a > b ) {
b /= a;
return a*Math.sqrt(1.0 + b*b);
}
if( b > 0 ) {
a /= b;
return b*Math.sqrt(1.0 + a*a);
}
return 0.0;
};
var JacobiImpl = function(A, astep, W, V, vstep, n) {
var eps = jsfeat.EPSILON;
var i=0,j=0,k=0,m=0,l=0,idx=0,_in=0,_in2=0;
var iters=0,max_iter=n*n*30;
var mv=0.0,val=0.0,p=0.0,y=0.0,t=0.0,s=0.0,c=0.0,a0=0.0,b0=0.0;
var indR_buff = jsfeat.cache.get_buffer(n<<2);
var indC_buff = jsfeat.cache.get_buffer(n<<2);
var indR = indR_buff.i32;
var indC = indC_buff.i32;
if(V) {
for(; i < n; i++) {
k = i*vstep;
for(j = 0; j < n; j++) {
V[k + j] = 0.0;
}
V[k + i] = 1.0;
}
}
for(k = 0; k < n; k++) {
W[k] = A[(astep + 1)*k];
if(k < n - 1) {
for(m = k+1, mv = Math.abs(A[astep*k + m]), i = k+2; i < n; i++) {
val = Math.abs(A[astep*k+i]);
if(mv < val)
mv = val, m = i;
}
indR[k] = m;
}
if(k > 0) {
for(m = 0, mv = Math.abs(A[k]), i = 1; i < k; i++) {
val = Math.abs(A[astep*i+k]);
if(mv < val)
mv = val, m = i;
}
indC[k] = m;
}
}
if(n > 1) for( ; iters < max_iter; iters++) {
// find index (k,l) of pivot p
for(k = 0, mv = Math.abs(A[indR[0]]), i = 1; i < n-1; i++) {
val = Math.abs(A[astep*i + indR[i]]);
if( mv < val )
mv = val, k = i;
}
l = indR[k];
for(i = 1; i < n; i++) {
val = Math.abs(A[astep*indC[i] + i]);
if( mv < val )
mv = val, k = indC[i], l = i;
}
p = A[astep*k + l];
if(Math.abs(p) <= eps) break;
y = (W[l] - W[k])*0.5;
t = Math.abs(y) + hypot(p, y);
s = hypot(p, t);
c = t/s;
s = p/s; t = (p/t)*p;
if(y < 0)
s = -s, t = -t;
A[astep*k + l] = 0;
W[k] -= t;
W[l] += t;
// rotate rows and columns k and l
for (i = 0; i < k; i++) {
_in = (astep * i + k);
_in2 = (astep * i + l);
a0 = A[_in];
b0 = A[_in2];
A[_in] = a0 * c - b0 * s;
A[_in2] = a0 * s + b0 * c;
}
for (i = (k + 1); i < l; i++) {
_in = (astep * k + i);
_in2 = (astep * i + l);
a0 = A[_in];
b0 = A[_in2];
A[_in] = a0 * c - b0 * s;
A[_in2] = a0 * s + b0 * c;
}
i = l + 1;
_in = (astep * k + i);
_in2 = (astep * l + i);
for (; i < n; i++, _in++, _in2++) {
a0 = A[_in];
b0 = A[_in2];
A[_in] = a0 * c - b0 * s;
A[_in2] = a0 * s + b0 * c;
}
// rotate eigenvectors
if (V) {
_in = vstep * k;
_in2 = vstep * l;
for (i = 0; i < n; i++, _in++, _in2++) {
a0 = V[_in];
b0 = V[_in2];
V[_in] = a0 * c - b0 * s;
V[_in2] = a0 * s + b0 * c;
}
}
for(j = 0; j < 2; j++) {
idx = j == 0 ? k : l;
if(idx < n - 1) {
for(m = idx+1, mv = Math.abs(A[astep*idx + m]), i = idx+2; i < n; i++) {
val = Math.abs(A[astep*idx+i]);
if( mv < val )
mv = val, m = i;
}
indR[idx] = m;
}
if(idx > 0) {
for(m = 0, mv = Math.abs(A[idx]), i = 1; i < idx; i++) {
val = Math.abs(A[astep*i+idx]);
if( mv < val )
mv = val, m = i;
}
indC[idx] = m;
}
}
}
// sort eigenvalues & eigenvectors
for(k = 0; k < n-1; k++) {
m = k;
for(i = k+1; i < n; i++) {
if(W[m] < W[i])
m = i;
}
if(k != m) {
swap(W, m, k, mv);
if(V) {
for(i = 0; i < n; i++) {
swap(V, vstep*m + i, vstep*k + i, mv);
}
}
}
}
jsfeat.cache.put_buffer(indR_buff);
jsfeat.cache.put_buffer(indC_buff);
};
var JacobiSVDImpl = function(At, astep, _W, Vt, vstep, m, n, n1) {
var eps = jsfeat.EPSILON * 2.0;
var minval = jsfeat.FLT_MIN;
var i=0,j=0,k=0,iter=0,max_iter=Math.max(m, 30);
var Ai=0,Aj=0,Vi=0,Vj=0,changed=0;
var c=0.0, s=0.0, t=0.0;
var t0=0.0,t1=0.0,sd=0.0,beta=0.0,gamma=0.0,delta=0.0,a=0.0,p=0.0,b=0.0;
var seed = 0x1234;
var val=0.0,val0=0.0,asum=0.0;
var W_buff = jsfeat.cache.get_buffer(n<<3);
var W = W_buff.f64;
for(; i < n; i++) {
for(k = 0, sd = 0; k < m; k++) {
t = At[i*astep + k];
sd += t*t;
}
W[i] = sd;
if(Vt) {
for(k = 0; k < n; k++) {
Vt[i*vstep + k] = 0;
}
Vt[i*vstep + i] = 1;
}
}
for(; iter < max_iter; iter++) {
changed = 0;
for(i = 0; i < n-1; i++) {
for(j = i+1; j < n; j++) {
Ai = (i*astep)|0, Aj = (j*astep)|0;
a = W[i], p = 0, b = W[j];
k = 2;
p += At[Ai]*At[Aj];
p += At[Ai+1]*At[Aj+1];
for(; k < m; k++)
p += At[Ai+k]*At[Aj+k];
if(Math.abs(p) <= eps*Math.sqrt(a*b)) continue;
p *= 2.0;
beta = a - b, gamma = hypot(p, beta);
if( beta < 0 ) {
delta = (gamma - beta)*0.5;
s = Math.sqrt(delta/gamma);
c = (p/(gamma*s*2.0));
} else {
c = Math.sqrt((gamma + beta)/(gamma*2.0));
s = (p/(gamma*c*2.0));
}
a=0.0, b=0.0;
k = 2; // unroll
t0 = c*At[Ai] + s*At[Aj];
t1 = -s*At[Ai] + c*At[Aj];
At[Ai] = t0; At[Aj] = t1;
a += t0*t0; b += t1*t1;
t0 = c*At[Ai+1] + s*At[Aj+1];
t1 = -s*At[Ai+1] + c*At[Aj+1];
At[Ai+1] = t0; At[Aj+1] = t1;
a += t0*t0; b += t1*t1;
for( ; k < m; k++ )
{
t0 = c*At[Ai+k] + s*At[Aj+k];
t1 = -s*At[Ai+k] + c*At[Aj+k];
At[Ai+k] = t0; At[Aj+k] = t1;
a += t0*t0; b += t1*t1;
}
W[i] = a; W[j] = b;
changed = 1;
if(Vt) {
Vi = (i*vstep)|0, Vj = (j*vstep)|0;
k = 2;
t0 = c*Vt[Vi] + s*Vt[Vj];
t1 = -s*Vt[Vi] + c*Vt[Vj];
Vt[Vi] = t0; Vt[Vj] = t1;
t0 = c*Vt[Vi+1] + s*Vt[Vj+1];
t1 = -s*Vt[Vi+1] + c*Vt[Vj+1];
Vt[Vi+1] = t0; Vt[Vj+1] = t1;
for(; k < n; k++) {
t0 = c*Vt[Vi+k] + s*Vt[Vj+k];
t1 = -s*Vt[Vi+k] + c*Vt[Vj+k];
Vt[Vi+k] = t0; Vt[Vj+k] = t1;
}
}
}
}
if(changed == 0) break;
}
for(i = 0; i < n; i++) {
for(k = 0, sd = 0; k < m; k++) {
t = At[i*astep + k];
sd += t*t;
}
W[i] = Math.sqrt(sd);
}
for(i = 0; i < n-1; i++) {
j = i;
for(k = i+1; k < n; k++) {
if(W[j] < W[k])
j = k;
}
if(i != j) {
swap(W, i, j, sd);
if(Vt) {
for(k = 0; k < m; k++) {
swap(At, i*astep + k, j*astep + k, t);
}
for(k = 0; k < n; k++) {
swap(Vt, i*vstep + k, j*vstep + k, t);
}
}
}
}
for(i = 0; i < n; i++) {
_W[i] = W[i];
}
if(!Vt) {
jsfeat.cache.put_buffer(W_buff);
return;
}
for(i = 0; i < n1; i++) {
sd = i < n ? W[i] : 0;
while(sd <= minval) {
// if we got a zero singular value, then in order to get the corresponding left singular vector
// we generate a random vector, project it to the previously computed left singular vectors,
// subtract the projection and normalize the difference.
val0 = (1.0/m);
for(k = 0; k < m; k++) {
seed = (seed * 214013 + 2531011);
val = (((seed >> 16) & 0x7fff) & 256) != 0 ? val0 : -val0;
At[i*astep + k] = val;
}
for(iter = 0; iter < 2; iter++) {
for(j = 0; j < i; j++) {
sd = 0;
for(k = 0; k < m; k++) {
sd += At[i*astep + k]*At[j*astep + k];
}
asum = 0.0;
for(k = 0; k < m; k++) {
t = (At[i*astep + k] - sd*At[j*astep + k]);
At[i*astep + k] = t;
asum += Math.abs(t);
}
asum = asum ? 1.0/asum : 0;
for(k = 0; k < m; k++) {
At[i*astep + k] *= asum;
}
}
}
sd = 0;
for(k = 0; k < m; k++) {
t = At[i*astep + k];
sd += t*t;
}
sd = Math.sqrt(sd);
}
s = (1.0/sd);
for(k = 0; k < m; k++) {
At[i*astep + k] *= s;
}
}
jsfeat.cache.put_buffer(W_buff);
};
return {
lu_solve: function(A, B) {
var i=0,j=0,k=0,p=1,astep=A.cols;
var ad=A.data, bd=B.data;
var t,alpha,d,s;
for(i = 0; i < astep; i++) {
k = i;
for(j = i+1; j < astep; j++) {
if(Math.abs(ad[j*astep + i]) > Math.abs(ad[k*astep+i])) {
k = j;
}
}
if(Math.abs(ad[k*astep+i]) < jsfeat.EPSILON) {
return 0; // FAILED
}
if(k != i) {
for(j = i; j < astep; j++ ) {
swap(ad, i*astep+j, k*astep+j, t);
}
swap(bd, i, k, t);
p = -p;
}
d = -1.0/ad[i*astep+i];
for(j = i+1; j < astep; j++) {
alpha = ad[j*astep+i]*d;
for(k = i+1; k < astep; k++) {
ad[j*astep+k] += alpha*ad[i*astep+k];
}
bd[j] += alpha*bd[i];
}
ad[i*astep+i] = -d;
}
for(i = astep-1; i >= 0; i--) {
s = bd[i];
for(k = i+1; k < astep; k++) {
s -= ad[i*astep+k]*bd[k];
}
bd[i] = s*ad[i*astep+i];
}
return 1; // OK
},
cholesky_solve: function(A, B) {
var col=0,row=0,col2=0,cs=0,rs=0,i=0,j=0;
var size = A.cols;
var ad=A.data, bd=B.data;
var val,inv_diag;
for (col = 0; col < size; col++) {
inv_diag = 1.0;
cs = (col * size);
rs = cs;
for (row = col; row < size; row++)
{
// correct for the parts of cholesky already computed
val = ad[(rs+col)];
for (col2 = 0; col2 < col; col2++) {
val -= ad[(col2*size+col)] * ad[(rs+col2)];
}
if (row == col) {
// this is the diagonal element so don't divide
ad[(rs+col)] = val;
if(val == 0) {
return 0;
}
inv_diag = 1.0 / val;
} else {
// cache the value without division in the upper half
ad[(cs+row)] = val;
// divide my the diagonal element for all others
ad[(rs+col)] = val * inv_diag;
}
rs = (rs + size);
}
}
// first backsub through L
cs = 0;
for (i = 0; i < size; i++) {
val = bd[i];
for (j = 0; j < i; j++) {
val -= ad[(cs+j)] * bd[j];
}
bd[i] = val;
cs = (cs + size);
}
// backsub through diagonal
cs = 0;
for (i = 0; i < size; i++) {
bd[i] /= ad[(cs + i)];
cs = (cs + size);
}
// backsub through L Transpose
i = (size-1);
for (; i >= 0; i--) {
val = bd[i];
j = (i + 1);
cs = (j * size);
for (; j < size; j++) {
val -= ad[(cs + i)] * bd[j];
cs = (cs + size);
}
bd[i] = val;
}
return 1;
},
svd_decompose: function(A, W, U, V, options) {
if (typeof options === "undefined") { options = 0; }
var at=0,i=0,j=0,_m=A.rows,_n=A.cols,m=_m,n=_n;
var dt = A.type | jsfeat.C1_t; // we only work with single channel
if(m < n) {
at = 1;
i = m;
m = n;
n = i;
}
var a_buff = jsfeat.cache.get_buffer((m*m)<<3);
var w_buff = jsfeat.cache.get_buffer(n<<3);
var v_buff = jsfeat.cache.get_buffer((n*n)<<3);
var a_mt = new jsfeat.matrix_t(m, m, dt, a_buff.data);
var w_mt = new jsfeat.matrix_t(1, n, dt, w_buff.data);
var v_mt = new jsfeat.matrix_t(n, n, dt, v_buff.data);
if(at == 0) {
// transpose
jsfeat.matmath.transpose(a_mt, A);
} else {
for(i = 0; i < _n*_m; i++) {
a_mt.data[i] = A.data[i];
}
for(; i < n*m; i++) {
a_mt.data[i] = 0;
}
}
JacobiSVDImpl(a_mt.data, m, w_mt.data, v_mt.data, n, m, n, m);
if(W) {
for(i=0; i < n; i++) {
W.data[i] = w_mt.data[i];
}
for(; i < _n; i++) {
W.data[i] = 0;
}
}
if (at == 0) {
if(U && (options & jsfeat.SVD_U_T)) {
i = m*m;
while(--i >= 0) {
U.data[i] = a_mt.data[i];
}
} else if(U) {
jsfeat.matmath.transpose(U, a_mt);
}
if(V && (options & jsfeat.SVD_V_T)) {
i = n*n;
while(--i >= 0) {
V.data[i] = v_mt.data[i];
}
} else if(V) {
jsfeat.matmath.transpose(V, v_mt);
}
} else {
if(U && (options & jsfeat.SVD_U_T)) {
i = n*n;
while(--i >= 0) {
U.data[i] = v_mt.data[i];
}
} else if(U) {
jsfeat.matmath.transpose(U, v_mt);
}
if(V && (options & jsfeat.SVD_V_T)) {
i = m*m;
while(--i >= 0) {
V.data[i] = a_mt.data[i];
}
} else if(V) {
jsfeat.matmath.transpose(V, a_mt);
}
}
jsfeat.cache.put_buffer(a_buff);
jsfeat.cache.put_buffer(w_buff);
jsfeat.cache.put_buffer(v_buff);
},
svd_solve: function(A, X, B) {
var i=0,j=0,k=0;
var pu=0,pv=0;
var nrows=A.rows,ncols=A.cols;
var sum=0.0,xsum=0.0,tol=0.0;
var dt = A.type | jsfeat.C1_t;
var u_buff = jsfeat.cache.get_buffer((nrows*nrows)<<3);
var w_buff = jsfeat.cache.get_buffer(ncols<<3);
var v_buff = jsfeat.cache.get_buffer((ncols*ncols)<<3);
var u_mt = new jsfeat.matrix_t(nrows, nrows, dt, u_buff.data);
var w_mt = new jsfeat.matrix_t(1, ncols, dt, w_buff.data);
var v_mt = new jsfeat.matrix_t(ncols, ncols, dt, v_buff.data);
var bd = B.data, ud = u_mt.data, wd = w_mt.data, vd = v_mt.data;
this.svd_decompose(A, w_mt, u_mt, v_mt, 0);
tol = jsfeat.EPSILON * wd[0] * ncols;
for (; i < ncols; i++, pv += ncols) {
xsum = 0.0;
for(j = 0; j < ncols; j++) {
if(wd[j] > tol) {
for(k = 0, sum = 0.0, pu = 0; k < nrows; k++, pu += ncols) {
sum += ud[pu + j] * bd[k];
}
xsum += sum * vd[pv + j] / wd[j];
}
}
X.data[i] = xsum;
}
jsfeat.cache.put_buffer(u_buff);
jsfeat.cache.put_buffer(w_buff);
jsfeat.cache.put_buffer(v_buff);
},
svd_invert: function(Ai, A) {
var i=0,j=0,k=0;
var pu=0,pv=0,pa=0;
var nrows=A.rows,ncols=A.cols;
var sum=0.0,tol=0.0;
var dt = A.type | jsfeat.C1_t;
var u_buff = jsfeat.cache.get_buffer((nrows*nrows)<<3);
var w_buff = jsfeat.cache.get_buffer(ncols<<3);
var v_buff = jsfeat.cache.get_buffer((ncols*ncols)<<3);
var u_mt = new jsfeat.matrix_t(nrows, nrows, dt, u_buff.data);
var w_mt = new jsfeat.matrix_t(1, ncols, dt, w_buff.data);
var v_mt = new jsfeat.matrix_t(ncols, ncols, dt, v_buff.data);
var id = Ai.data, ud = u_mt.data, wd = w_mt.data, vd = v_mt.data;
this.svd_decompose(A, w_mt, u_mt, v_mt, 0);
tol = jsfeat.EPSILON * wd[0] * ncols;
for (; i < ncols; i++, pv += ncols) {
for (j = 0, pu = 0; j < nrows; j++, pa++) {
for (k = 0, sum = 0.0; k < ncols; k++, pu++) {
if (wd[k] > tol) sum += vd[pv + k] * ud[pu] / wd[k];
}
id[pa] = sum;
}
}
jsfeat.cache.put_buffer(u_buff);
jsfeat.cache.put_buffer(w_buff);
jsfeat.cache.put_buffer(v_buff);
},
eigenVV: function(A, vects, vals) {
var n=A.cols,i=n*n;
var dt = A.type | jsfeat.C1_t;
var a_buff = jsfeat.cache.get_buffer((n*n)<<3);
var w_buff = jsfeat.cache.get_buffer(n<<3);
var a_mt = new jsfeat.matrix_t(n, n, dt, a_buff.data);
var w_mt = new jsfeat.matrix_t(1, n, dt, w_buff.data);
while(--i >= 0) {
a_mt.data[i] = A.data[i];
}
JacobiImpl(a_mt.data, n, w_mt.data, vects ? vects.data : null, n, n);
if(vals) {
while(--n >= 0) {
vals.data[n] = w_mt.data[n];
}
}
jsfeat.cache.put_buffer(a_buff);
jsfeat.cache.put_buffer(w_buff);
}
};
})();
global.linalg = linalg;
})(jsfeat);
/**
* @author Eugene Zatepyakin / http://inspirit.ru/
*
*/
(function(global) {
"use strict";
//
var motion_model = (function() {
var sqr = function(x) {
return x*x;
};
// does isotropic normalization
var iso_normalize_points = function(from, to, T0, T1, count) {
var i=0;
var cx0=0.0, cy0=0.0, d0=0.0, s0=0.0;
var cx1=0.0, cy1=0.0, d1=0.0, s1=0.0;
var dx=0.0,dy=0.0;
for (; i < count; ++i) {
cx0 += from[i].x;
cy0 += from[i].y;
cx1 += to[i].x;
cy1 += to[i].y;
}
cx0 /= count; cy0 /= count;
cx1 /= count; cy1 /= count;
for (i = 0; i < count; ++i) {
dx = from[i].x - cx0;
dy = from[i].y - cy0;
d0 += Math.sqrt(dx*dx + dy*dy);
dx = to[i].x - cx1;
dy = to[i].y - cy1;
d1 += Math.sqrt(dx*dx + dy*dy);
}
d0 /= count; d1 /= count;
s0 = Math.SQRT2 / d0; s1 = Math.SQRT2 / d1;
T0[0] = T0[4] = s0;
T0[2] = -cx0*s0;
T0[5] = -cy0*s0;
T0[1] = T0[3] = T0[6] = T0[7] = 0.0;
T0[8] = 1.0;
T1[0] = T1[4] = s1;
T1[2] = -cx1*s1;
T1[5] = -cy1*s1;
T1[1] = T1[3] = T1[6] = T1[7] = 0.0;
T1[8] = 1.0;
};
var have_collinear_points = function(points, count) {
var j=0,k=0,i=(count-1)|0;
var dx1=0.0,dy1=0.0,dx2=0.0,dy2=0.0;
// check that the i-th selected point does not belong
// to a line connecting some previously selected points
for(; j < i; ++j) {
dx1 = points[j].x - points[i].x;
dy1 = points[j].y - points[i].y;
for(k = 0; k < j; ++k) {
dx2 = points[k].x - points[i].x;
dy2 = points[k].y - points[i].y;
if( Math.abs(dx2*dy1 - dy2*dx1) <= jsfeat.EPSILON*(Math.abs(dx1) + Math.abs(dy1) + Math.abs(dx2) + Math.abs(dy2)))
return true;
}
}
return false;
};
var T0 = new jsfeat.matrix_t(3, 3, jsfeat.F32_t|jsfeat.C1_t);
var T1 = new jsfeat.matrix_t(3, 3, jsfeat.F32_t|jsfeat.C1_t);
var AtA = new jsfeat.matrix_t(6, 6, jsfeat.F32_t|jsfeat.C1_t);
var AtB = new jsfeat.matrix_t(6, 1, jsfeat.F32_t|jsfeat.C1_t);
var affine2d = (function () {
function affine2d() {
// empty constructor
}
affine2d.prototype.run = function(from, to, model, count) {
var i=0,j=0;
var dt=model.type|jsfeat.C1_t;
var md=model.data, t0d=T0.data, t1d=T1.data;
var pt0,pt1,px=0.0,py=0.0;
iso_normalize_points(from, to, t0d, t1d, count);
var a_buff = jsfeat.cache.get_buffer((2*count*6)<<3);
var b_buff = jsfeat.cache.get_buffer((2*count)<<3);
var a_mt = new jsfeat.matrix_t(6, 2*count, dt, a_buff.data);
var b_mt = new jsfeat.matrix_t(1, 2*count, dt, b_buff.data);
var ad=a_mt.data, bd=b_mt.data;
for (; i < count; ++i) {
pt0 = from[i];
pt1 = to[i];
px = t0d[0]*pt0.x + t0d[1]*pt0.y + t0d[2];
py = t0d[3]*pt0.x + t0d[4]*pt0.y + t0d[5];
j = i*2*6;
ad[j]=px, ad[j+1]=py, ad[j+2]=1.0, ad[j+3]=0.0, ad[j+4]=0.0, ad[j+5]=0.0;
j += 6;
ad[j]=0.0, ad[j+1]=0.0, ad[j+2]=0.0, ad[j+3]=px, ad[j+4]=py, ad[j+5]=1.0;
bd[i<<1] = t1d[0]*pt1.x + t1d[1]*pt1.y + t1d[2];
bd[(i<<1)+1] = t1d[3]*pt1.x + t1d[4]*pt1.y + t1d[5];
}
jsfeat.matmath.multiply_AtA(AtA, a_mt);
jsfeat.matmath.multiply_AtB(AtB, a_mt, b_mt);
jsfeat.linalg.lu_solve(AtA, AtB);
md[0] = AtB.data[0], md[1]=AtB.data[1], md[2]=AtB.data[2];
md[3] = AtB.data[3], md[4]=AtB.data[4], md[5]=AtB.data[5];
md[6] = 0.0, md[7] = 0.0, md[8] = 1.0; // fill last row
// denormalize
jsfeat.matmath.invert_3x3(T1, T1);
jsfeat.matmath.multiply_3x3(model, T1, model);
jsfeat.matmath.multiply_3x3(model, model, T0);
// free buffer
jsfeat.cache.put_buffer(a_buff);
jsfeat.cache.put_buffer(b_buff);
return 1;
};
affine2d.prototype.error = function(from, to, model, err, count) {
var i=0;
var pt0,pt1;
var m=model.data;
for (; i < count; ++i) {
pt0 = from[i];
pt1 = to[i];
err[i] = sqr(pt1.x - m[0]*pt0.x - m[1]*pt0.y - m[2]) +
sqr(pt1.y - m[3]*pt0.x - m[4]*pt0.y - m[5]);
}
};
affine2d.prototype.check_subset = function(from, to, count) {
return true; // all good
};
return affine2d;
})();
var mLtL = new jsfeat.matrix_t(9, 9, jsfeat.F32_t|jsfeat.C1_t);
var Evec = new jsfeat.matrix_t(9, 9, jsfeat.F32_t|jsfeat.C1_t);
var homography2d = (function () {
function homography2d() {
// empty constructor
//this.T0 = new jsfeat.matrix_t(3, 3, jsfeat.F32_t|jsfeat.C1_t);
//this.T1 = new jsfeat.matrix_t(3, 3, jsfeat.F32_t|jsfeat.C1_t);
//this.mLtL = new jsfeat.matrix_t(9, 9, jsfeat.F32_t|jsfeat.C1_t);
//this.Evec = new jsfeat.matrix_t(9, 9, jsfeat.F32_t|jsfeat.C1_t);
}
homography2d.prototype.run = function(from, to, model, count) {
var i=0,j=0;
var md=model.data, t0d=T0.data, t1d=T1.data;
var LtL=mLtL.data, evd=Evec.data;
var x=0.0,y=0.0,X=0.0,Y=0.0;
// norm
var smx=0.0, smy=0.0, cmx=0.0, cmy=0.0, sMx=0.0, sMy=0.0, cMx=0.0, cMy=0.0;
for(; i < count; ++i) {
cmx += to[i].x;
cmy += to[i].y;
cMx += from[i].x;
cMy += from[i].y;
}
cmx /= count; cmy /= count;
cMx /= count; cMy /= count;
for(i = 0; i < count; ++i)
{
smx += Math.abs(to[i].x - cmx);
smy += Math.abs(to[i].y - cmy);
sMx += Math.abs(from[i].x - cMx);
sMy += Math.abs(from[i].y - cMy);
}
if( Math.abs(smx) < jsfeat.EPSILON
|| Math.abs(smy) < jsfeat.EPSILON
|| Math.abs(sMx) < jsfeat.EPSILON
|| Math.abs(sMy) < jsfeat.EPSILON ) return 0;
smx = count/smx; smy = count/smy;
sMx = count/sMx; sMy = count/sMy;
t0d[0] = sMx; t0d[1] = 0; t0d[2] = -cMx*sMx;
t0d[3] = 0; t0d[4] = sMy; t0d[5] = -cMy*sMy;
t0d[6] = 0; t0d[7] = 0; t0d[8] = 1;
t1d[0] = 1.0/smx; t1d[1] = 0; t1d[2] = cmx;
t1d[3] = 0; t1d[4] = 1.0/smy; t1d[5] = cmy;
t1d[6] = 0; t1d[7] = 0; t1d[8] = 1;
//
// construct system
i = 81;
while(--i >= 0) {
LtL[i] = 0.0;
}
for(i = 0; i < count; ++i) {
x = (to[i].x - cmx) * smx;
y = (to[i].y - cmy) * smy;
X = (from[i].x - cMx) * sMx;
Y = (from[i].y - cMy) * sMy;
LtL[0] += X*X;
LtL[1] += X*Y;
LtL[2] += X;
LtL[6] += X*-x*X;
LtL[7] += X*-x*Y;
LtL[8] += X*-x;
LtL[10] += Y*Y;
LtL[11] += Y;
LtL[15] += Y*-x*X;
LtL[16] += Y*-x*Y;
LtL[17] += Y*-x;
LtL[20] += 1.0;
LtL[24] += -x*X;
LtL[25] += -x*Y;
LtL[26] += -x;
LtL[30] += X*X;
LtL[31] += X*Y;
LtL[32] += X;
LtL[33] += X*-y*X;
LtL[34] += X*-y*Y;
LtL[35] += X*-y;
LtL[40] += Y*Y;
LtL[41] += Y;
LtL[42] += Y*-y*X;
LtL[43] += Y*-y*Y;
LtL[44] += Y*-y;
LtL[50] += 1.0;
LtL[51] += -y*X;
LtL[52] += -y*Y;
LtL[53] += -y;
LtL[60] += -x*X*-x*X + -y*X*-y*X;
LtL[61] += -x*X*-x*Y + -y*X*-y*Y;
LtL[62] += -x*X*-x + -y*X*-y;
LtL[70] += -x*Y*-x*Y + -y*Y*-y*Y;
LtL[71] += -x*Y*-x + -y*Y*-y;
LtL[80] += -x*-x + -y*-y;
}
//
// symmetry
for(i = 0; i < 9; ++i) {
for(j = 0; j < i; ++j)
LtL[i*9+j] = LtL[j*9+i];
}
jsfeat.linalg.eigenVV(mLtL, Evec);
md[0]=evd[72], md[1]=evd[73], md[2]=evd[74];
md[3]=evd[75], md[4]=evd[76], md[5]=evd[77];
md[6]=evd[78], md[7]=evd[79], md[8]=evd[80];
// denormalize
jsfeat.matmath.multiply_3x3(model, T1, model);
jsfeat.matmath.multiply_3x3(model, model, T0);
// set bottom right to 1.0
x = 1.0/md[8];
md[0] *= x; md[1] *= x; md[2] *= x;
md[3] *= x; md[4] *= x; md[5] *= x;
md[6] *= x; md[7] *= x; md[8] = 1.0;
return 1;
};
homography2d.prototype.error = function(from, to, model, err, count) {
var i=0;
var pt0,pt1,ww=0.0,dx=0.0,dy=0.0;
var m=model.data;
for (; i < count; ++i) {
pt0 = from[i];
pt1 = to[i];
ww = 1.0/(m[6]*pt0.x + m[7]*pt0.y + 1.0);
dx = (m[0]*pt0.x + m[1]*pt0.y + m[2])*ww - pt1.x;
dy = (m[3]*pt0.x + m[4]*pt0.y + m[5])*ww - pt1.y;
err[i] = (dx*dx + dy*dy);
}
};
homography2d.prototype.check_subset = function(from, to, count) {
// seems to reject good subsets actually
//if( have_collinear_points(from, count) || have_collinear_points(to, count) ) {
//return false;
//}
if( count == 4 ) {
var negative = 0;
var fp0=from[0],fp1=from[1],fp2=from[2],fp3=from[3];
var tp0=to[0],tp1=to[1],tp2=to[2],tp3=to[3];
// set1
var A11=fp0.x, A12=fp0.y, A13=1.0;
var A21=fp1.x, A22=fp1.y, A23=1.0;
var A31=fp2.x, A32=fp2.y, A33=1.0;
var B11=tp0.x, B12=tp0.y, B13=1.0;
var B21=tp1.x, B22=tp1.y, B23=1.0;
var B31=tp2.x, B32=tp2.y, B33=1.0;
var detA = jsfeat.matmath.determinant_3x3(A11,A12,A13, A21,A22,A23, A31,A32,A33);
var detB = jsfeat.matmath.determinant_3x3(B11,B12,B13, B21,B22,B23, B31,B32,B33);
if(detA*detB < 0) negative++;
// set2
A11=fp1.x, A12=fp1.y;
A21=fp2.x, A22=fp2.y;
A31=fp3.x, A32=fp3.y;
B11=tp1.x, B12=tp1.y;
B21=tp2.x, B22=tp2.y;
B31=tp3.x, B32=tp3.y;
detA = jsfeat.matmath.determinant_3x3(A11,A12,A13, A21,A22,A23, A31,A32,A33);
detB = jsfeat.matmath.determinant_3x3(B11,B12,B13, B21,B22,B23, B31,B32,B33);
if(detA*detB < 0) negative++;
// set3
A11=fp0.x, A12=fp0.y;
A21=fp2.x, A22=fp2.y;
A31=fp3.x, A32=fp3.y;
B11=tp0.x, B12=tp0.y;
B21=tp2.x, B22=tp2.y;
B31=tp3.x, B32=tp3.y;
detA = jsfeat.matmath.determinant_3x3(A11,A12,A13, A21,A22,A23, A31,A32,A33);
detB = jsfeat.matmath.determinant_3x3(B11,B12,B13, B21,B22,B23, B31,B32,B33);
if(detA*detB < 0) negative++;
// set4
A11=fp0.x, A12=fp0.y;
A21=fp1.x, A22=fp1.y;
A31=fp3.x, A32=fp3.y;
B11=tp0.x, B12=tp0.y;
B21=tp1.x, B22=tp1.y;
B31=tp3.x, B32=tp3.y;
detA = jsfeat.matmath.determinant_3x3(A11,A12,A13, A21,A22,A23, A31,A32,A33);
detB = jsfeat.matmath.determinant_3x3(B11,B12,B13, B21,B22,B23, B31,B32,B33);
if(detA*detB < 0) negative++;
if(negative != 0 && negative != 4) {
return false;
}
}
return true; // all good
};
return homography2d;
})();
return {
affine2d:affine2d,
homography2d:homography2d
};
})();
var ransac_params_t = (function () {
function ransac_params_t(size, thresh, eps, prob) {
if (typeof size === "undefined") { size=0; }
if (typeof thresh === "undefined") { thresh=0.5; }
if (typeof eps === "undefined") { eps=0.5; }
if (typeof prob === "undefined") { prob=0.99; }
this.size = size;
this.thresh = thresh;
this.eps = eps;
this.prob = prob;
}
ransac_params_t.prototype.update_iters = function(_eps, max_iters) {
var num = Math.log(1 - this.prob);
var denom = Math.log(1 - Math.pow(1 - _eps, this.size));
return (denom >= 0 || -num >= max_iters*(-denom) ? max_iters : Math.round(num/denom))|0;
};
return ransac_params_t;
})();
var motion_estimator = (function() {
var get_subset = function(kernel, from, to, need_cnt, max_cnt, from_sub, to_sub) {
var max_try = 1000;
var indices = [];
var i=0, j=0, ssiter=0, idx_i=0, ok=false;
for(; ssiter < max_try; ++ssiter) {
i = 0;
for (; i < need_cnt && ssiter < max_try;) {
ok = false;
idx_i = 0;
while (!ok) {
ok = true;
idx_i = indices[i] = Math.floor(Math.random() * max_cnt)|0;
for (j = 0; j < i; ++j) {
if (idx_i == indices[j])
{ ok = false; break; }
}
}
from_sub[i] = from[idx_i];
to_sub[i] = to[idx_i];
if( !kernel.check_subset( from_sub, to_sub, i+1 ) ) {
ssiter++;
continue;
}
++i;
}
break;
}
return (i == need_cnt && ssiter < max_try);
};
var find_inliers = function(kernel, model, from, to, count, thresh, err, mask) {
var numinliers = 0, i=0, f=0;
var t = thresh*thresh;
kernel.error(from, to, model, err, count);
for(; i < count; ++i) {
f = err[i] <= t;
mask[i] = f;
numinliers += f;
}
return numinliers;
};
return {
ransac: function(params, kernel, from, to, count, model, mask, max_iters) {
if (typeof max_iters === "undefined") { max_iters=1000; }
if(count < params.size) return false;
var model_points = params.size;
var niters = max_iters, iter=0;
var result = false;
var subset0 = [];
var subset1 = [];
var found = false;
var mc=model.cols,mr=model.rows;
var dt = model.type | jsfeat.C1_t;
var m_buff = jsfeat.cache.get_buffer((mc*mr)<<3);
var ms_buff = jsfeat.cache.get_buffer(count);
var err_buff = jsfeat.cache.get_buffer(count<<2);
var M = new jsfeat.matrix_t(mc, mr, dt, m_buff.data);
var curr_mask = new jsfeat.matrix_t(count, 1, jsfeat.U8C1_t, ms_buff.data);
var inliers_max = -1, numinliers=0;
var nmodels = 0;
var err = err_buff.f32;
// special case
if(count == model_points) {
if(kernel.run(from, to, M, count) <= 0) {
jsfeat.cache.put_buffer(m_buff);
jsfeat.cache.put_buffer(ms_buff);
jsfeat.cache.put_buffer(err_buff);
return false;
}
M.copy_to(model);
if(mask) {
while(--count >= 0) {
mask.data[count] = 1;
}
}
jsfeat.cache.put_buffer(m_buff);
jsfeat.cache.put_buffer(ms_buff);
jsfeat.cache.put_buffer(err_buff);
return true;
}
for (; iter < niters; ++iter) {
// generate subset
found = get_subset(kernel, from, to, model_points, count, subset0, subset1);
if(!found) {
if(iter == 0) {
jsfeat.cache.put_buffer(m_buff);
jsfeat.cache.put_buffer(ms_buff);
jsfeat.cache.put_buffer(err_buff);
return false;
}
break;
}
nmodels = kernel.run( subset0, subset1, M, model_points );
if(nmodels <= 0)
continue;
// TODO handle multimodel output
numinliers = find_inliers(kernel, M, from, to, count, params.thresh, err, curr_mask.data);
if( numinliers > Math.max(inliers_max, model_points-1) ) {
M.copy_to(model);
inliers_max = numinliers;
if(mask) curr_mask.copy_to(mask);
niters = params.update_iters((count - numinliers)/count, niters);
result = true;
}
}
jsfeat.cache.put_buffer(m_buff);
jsfeat.cache.put_buffer(ms_buff);
jsfeat.cache.put_buffer(err_buff);
return result;
},
lmeds: function(params, kernel, from, to, count, model, mask, max_iters) {
if (typeof max_iters === "undefined") { max_iters=1000; }
if(count < params.size) return false;
var model_points = params.size;
var niters = max_iters, iter=0;
var result = false;
var subset0 = [];
var subset1 = [];
var found = false;
var mc=model.cols,mr=model.rows;
var dt = model.type | jsfeat.C1_t;
var m_buff = jsfeat.cache.get_buffer((mc*mr)<<3);
var ms_buff = jsfeat.cache.get_buffer(count);
var err_buff = jsfeat.cache.get_buffer(count<<2);
var M = new jsfeat.matrix_t(mc, mr, dt, m_buff.data);
var curr_mask = new jsfeat.matrix_t(count, 1, jsfeat.U8_t|jsfeat.C1_t, ms_buff.data);
var numinliers=0;
var nmodels = 0;
var err = err_buff.f32;
var min_median = 1000000000.0, sigma=0.0, median=0.0;
params.eps = 0.45;
niters = params.update_iters(params.eps, niters);
// special case
if(count == model_points) {
if(kernel.run(from, to, M, count) <= 0) {
jsfeat.cache.put_buffer(m_buff);
jsfeat.cache.put_buffer(ms_buff);
jsfeat.cache.put_buffer(err_buff);
return false;
}
M.copy_to(model);
if(mask) {
while(--count >= 0) {
mask.data[count] = 1;
}
}
jsfeat.cache.put_buffer(m_buff);
jsfeat.cache.put_buffer(ms_buff);
jsfeat.cache.put_buffer(err_buff);
return true;
}
for (; iter < niters; ++iter) {
// generate subset
found = get_subset(kernel, from, to, model_points, count, subset0, subset1);
if(!found) {
if(iter == 0) {
jsfeat.cache.put_buffer(m_buff);
jsfeat.cache.put_buffer(ms_buff);
jsfeat.cache.put_buffer(err_buff);
return false;
}
break;
}
nmodels = kernel.run( subset0, subset1, M, model_points );
if(nmodels <= 0)
continue;
// TODO handle multimodel output
kernel.error(from, to, M, err, count);
median = jsfeat.math.median(err, 0, count-1);
if(median < min_median) {
min_median = median;
M.copy_to(model);
result = true;
}
}
if(result) {
sigma = 2.5*1.4826*(1 + 5.0/(count - model_points))*Math.sqrt(min_median);
sigma = Math.max(sigma, 0.001);
numinliers = find_inliers(kernel, model, from, to, count, sigma, err, curr_mask.data);
if(mask) curr_mask.copy_to(mask);
result = numinliers >= model_points;
}
jsfeat.cache.put_buffer(m_buff);
jsfeat.cache.put_buffer(ms_buff);
jsfeat.cache.put_buffer(err_buff);
return result;
}
};
})();
global.ransac_params_t = ransac_params_t;
global.motion_model = motion_model;
global.motion_estimator = motion_estimator;
})(jsfeat);
/**
* @author Eugene Zatepyakin / http://inspirit.ru/
*/
(function(global) {
"use strict";
//
var imgproc = (function() {
var _resample_u8 = function(src, dst, nw, nh) {
var xofs_count=0;
var ch=src.channel,w=src.cols,h=src.rows;
var src_d=src.data,dst_d=dst.data;
var scale_x = w / nw, scale_y = h / nh;
var inv_scale_256 = (scale_x * scale_y * 0x10000)|0;
var dx=0,dy=0,sx=0,sy=0,sx1=0,sx2=0,i=0,k=0,fsx1=0.0,fsx2=0.0;
var a=0,b=0,dxn=0,alpha=0,beta=0,beta1=0;
var buf_node = jsfeat.cache.get_buffer((nw*ch)<<2);
var sum_node = jsfeat.cache.get_buffer((nw*ch)<<2);
var xofs_node = jsfeat.cache.get_buffer((w*2*3)<<2);
var buf = buf_node.i32;
var sum = sum_node.i32;
var xofs = xofs_node.i32;
for (; dx < nw; dx++) {
fsx1 = dx * scale_x, fsx2 = fsx1 + scale_x;
sx1 = (fsx1 + 1.0 - 1e-6)|0, sx2 = fsx2|0;
sx1 = Math.min(sx1, w - 1);
sx2 = Math.min(sx2, w - 1);
if(sx1 > fsx1) {
xofs[k++] = (dx * ch)|0;
xofs[k++] = ((sx1 - 1)*ch)|0;
xofs[k++] = ((sx1 - fsx1) * 0x100)|0;
xofs_count++;
}
for(sx = sx1; sx < sx2; sx++){
xofs_count++;
xofs[k++] = (dx * ch)|0;
xofs[k++] = (sx * ch)|0;
xofs[k++] = 256;
}
if(fsx2 - sx2 > 1e-3) {
xofs_count++;
xofs[k++] = (dx * ch)|0;
xofs[k++] = (sx2 * ch)|0;
xofs[k++] = ((fsx2 - sx2) * 256)|0;
}
}
for (dx = 0; dx < nw * ch; dx++) {
buf[dx] = sum[dx] = 0;
}
dy = 0;
for (sy = 0; sy < h; sy++) {
a = w * sy;
for (k = 0; k < xofs_count; k++) {
dxn = xofs[k*3];
sx1 = xofs[k*3+1];
alpha = xofs[k*3+2];
for (i = 0; i < ch; i++) {
buf[dxn + i] += src_d[a+sx1+i] * alpha;
}
}
if ((dy + 1) * scale_y <= sy + 1 || sy == h - 1) {
beta = (Math.max(sy + 1 - (dy + 1) * scale_y, 0.0) * 256)|0;
beta1 = 256 - beta;
b = nw * dy;
if (beta <= 0) {
for (dx = 0; dx < nw * ch; dx++) {
dst_d[b+dx] = Math.min(Math.max((sum[dx] + buf[dx] * 256) / inv_scale_256, 0), 255);
sum[dx] = buf[dx] = 0;
}
} else {
for (dx = 0; dx < nw * ch; dx++) {
dst_d[b+dx] = Math.min(Math.max((sum[dx] + buf[dx] * beta1) / inv_scale_256, 0), 255);
sum[dx] = buf[dx] * beta;
buf[dx] = 0;
}
}
dy++;
} else {
for(dx = 0; dx < nw * ch; dx++) {
sum[dx] += buf[dx] * 256;
buf[dx] = 0;
}
}
}
jsfeat.cache.put_buffer(sum_node);
jsfeat.cache.put_buffer(buf_node);
jsfeat.cache.put_buffer(xofs_node);
};
var _resample = function(src, dst, nw, nh) {
var xofs_count=0;
var ch=src.channel,w=src.cols,h=src.rows;
var src_d=src.data,dst_d=dst.data;
var scale_x = w / nw, scale_y = h / nh;
var scale = 1.0 / (scale_x * scale_y);
var dx=0,dy=0,sx=0,sy=0,sx1=0,sx2=0,i=0,k=0,fsx1=0.0,fsx2=0.0;
var a=0,b=0,dxn=0,alpha=0.0,beta=0.0,beta1=0.0;
var buf_node = jsfeat.cache.get_buffer((nw*ch)<<2);
var sum_node = jsfeat.cache.get_buffer((nw*ch)<<2);
var xofs_node = jsfeat.cache.get_buffer((w*2*3)<<2);
var buf = buf_node.f32;
var sum = sum_node.f32;
var xofs = xofs_node.f32;
for (; dx < nw; dx++) {
fsx1 = dx * scale_x, fsx2 = fsx1 + scale_x;
sx1 = (fsx1 + 1.0 - 1e-6)|0, sx2 = fsx2|0;
sx1 = Math.min(sx1, w - 1);
sx2 = Math.min(sx2, w - 1);
if(sx1 > fsx1) {
xofs_count++;
xofs[k++] = ((sx1 - 1)*ch)|0;
xofs[k++] = (dx * ch)|0;
xofs[k++] = (sx1 - fsx1) * scale;
}
for(sx = sx1; sx < sx2; sx++){
xofs_count++;
xofs[k++] = (sx * ch)|0;
xofs[k++] = (dx * ch)|0;
xofs[k++] = scale;
}
if(fsx2 - sx2 > 1e-3) {
xofs_count++;
xofs[k++] = (sx2 * ch)|0;
xofs[k++] = (dx * ch)|0;
xofs[k++] = (fsx2 - sx2) * scale;
}
}
for (dx = 0; dx < nw * ch; dx++) {
buf[dx] = sum[dx] = 0;
}
dy = 0;
for (sy = 0; sy < h; sy++) {
a = w * sy;
for (k = 0; k < xofs_count; k++) {
sx1 = xofs[k*3]|0;
dxn = xofs[k*3+1]|0;
alpha = xofs[k*3+2];
for (i = 0; i < ch; i++) {
buf[dxn + i] += src_d[a+sx1+i] * alpha;
}
}
if ((dy + 1) * scale_y <= sy + 1 || sy == h - 1) {
beta = Math.max(sy + 1 - (dy + 1) * scale_y, 0.0);
beta1 = 1.0 - beta;
b = nw * dy;
if (Math.abs(beta) < 1e-3) {
for (dx = 0; dx < nw * ch; dx++) {
dst_d[b+dx] = sum[dx] + buf[dx];
sum[dx] = buf[dx] = 0;
}
} else {
for (dx = 0; dx < nw * ch; dx++) {
dst_d[b+dx] = sum[dx] + buf[dx] * beta1;
sum[dx] = buf[dx] * beta;
buf[dx] = 0;
}
}
dy++;
} else {
for(dx = 0; dx < nw * ch; dx++) {
sum[dx] += buf[dx];
buf[dx] = 0;
}
}
}
jsfeat.cache.put_buffer(sum_node);
jsfeat.cache.put_buffer(buf_node);
jsfeat.cache.put_buffer(xofs_node);
};
var _convol_u8 = function(buf, src_d, dst_d, w, h, filter, kernel_size, half_kernel) {
var i=0,j=0,k=0,sp=0,dp=0,sum=0,sum1=0,sum2=0,sum3=0,f0=filter[0],fk=0;
var w2=w<<1,w3=w*3,w4=w<<2;
// hor pass
for (; i < h; ++i) {
sum = src_d[sp];
for (j = 0; j < half_kernel; ++j) {
buf[j] = sum;
}
for (j = 0; j <= w-2; j+=2) {
buf[j + half_kernel] = src_d[sp+j];
buf[j + half_kernel+1] = src_d[sp+j+1];
}
for (; j < w; ++j) {
buf[j + half_kernel] = src_d[sp+j];
}
sum = src_d[sp+w-1];
for (j = w; j < half_kernel + w; ++j) {
buf[j + half_kernel] = sum;
}
for (j = 0; j <= w-4; j+=4) {
sum = buf[j] * f0,
sum1 = buf[j+1] * f0,
sum2 = buf[j+2] * f0,
sum3 = buf[j+3] * f0;
for (k = 1; k < kernel_size; ++k) {
fk = filter[k];
sum += buf[k + j] * fk;
sum1 += buf[k + j+1] * fk;
sum2 += buf[k + j+2] * fk;
sum3 += buf[k + j+3] * fk;
}
dst_d[dp+j] = Math.min(sum >> 8, 255);
dst_d[dp+j+1] = Math.min(sum1 >> 8, 255);
dst_d[dp+j+2] = Math.min(sum2 >> 8, 255);
dst_d[dp+j+3] = Math.min(sum3 >> 8, 255);
}
for (; j < w; ++j) {
sum = buf[j] * f0;
for (k = 1; k < kernel_size; ++k) {
sum += buf[k + j] * filter[k];
}
dst_d[dp+j] = Math.min(sum >> 8, 255);
}
sp += w;
dp += w;
}
// vert pass
for (i = 0; i < w; ++i) {
sum = dst_d[i];
for (j = 0; j < half_kernel; ++j) {
buf[j] = sum;
}
k = i;
for (j = 0; j <= h-2; j+=2, k+=w2) {
buf[j+half_kernel] = dst_d[k];
buf[j+half_kernel+1] = dst_d[k+w];
}
for (; j < h; ++j, k+=w) {
buf[j+half_kernel] = dst_d[k];
}
sum = dst_d[(h-1)*w + i];
for (j = h; j < half_kernel + h; ++j) {
buf[j + half_kernel] = sum;
}
dp = i;
for (j = 0; j <= h-4; j+=4, dp+=w4) {
sum = buf[j] * f0,
sum1 = buf[j+1] * f0,
sum2 = buf[j+2] * f0,
sum3 = buf[j+3] * f0;
for (k = 1; k < kernel_size; ++k) {
fk = filter[k];
sum += buf[k + j] * fk;
sum1 += buf[k + j+1] * fk;
sum2 += buf[k + j+2] * fk;
sum3 += buf[k + j+3] * fk;
}
dst_d[dp] = Math.min(sum >> 8, 255);
dst_d[dp+w] = Math.min(sum1 >> 8, 255);
dst_d[dp+w2] = Math.min(sum2 >> 8, 255);
dst_d[dp+w3] = Math.min(sum3 >> 8, 255);
}
for (; j < h; ++j, dp+=w) {
sum = buf[j] * f0;
for (k = 1; k < kernel_size; ++k) {
sum += buf[k + j] * filter[k];
}
dst_d[dp] = Math.min(sum >> 8, 255);
}
}
};
var _convol = function(buf, src_d, dst_d, w, h, filter, kernel_size, half_kernel) {
var i=0,j=0,k=0,sp=0,dp=0,sum=0.0,sum1=0.0,sum2=0.0,sum3=0.0,f0=filter[0],fk=0.0;
var w2=w<<1,w3=w*3,w4=w<<2;
// hor pass
for (; i < h; ++i) {
sum = src_d[sp];
for (j = 0; j < half_kernel; ++j) {
buf[j] = sum;
}
for (j = 0; j <= w-2; j+=2) {
buf[j + half_kernel] = src_d[sp+j];
buf[j + half_kernel+1] = src_d[sp+j+1];
}
for (; j < w; ++j) {
buf[j + half_kernel] = src_d[sp+j];
}
sum = src_d[sp+w-1];
for (j = w; j < half_kernel + w; ++j) {
buf[j + half_kernel] = sum;
}
for (j = 0; j <= w-4; j+=4) {
sum = buf[j] * f0,
sum1 = buf[j+1] * f0,
sum2 = buf[j+2] * f0,
sum3 = buf[j+3] * f0;
for (k = 1; k < kernel_size; ++k) {
fk = filter[k];
sum += buf[k + j] * fk;
sum1 += buf[k + j+1] * fk;
sum2 += buf[k + j+2] * fk;
sum3 += buf[k + j+3] * fk;
}
dst_d[dp+j] = sum;
dst_d[dp+j+1] = sum1;
dst_d[dp+j+2] = sum2;
dst_d[dp+j+3] = sum3;
}
for (; j < w; ++j) {
sum = buf[j] * f0;
for (k = 1; k < kernel_size; ++k) {
sum += buf[k + j] * filter[k];
}
dst_d[dp+j] = sum;
}
sp += w;
dp += w;
}
// vert pass
for (i = 0; i < w; ++i) {
sum = dst_d[i];
for (j = 0; j < half_kernel; ++j) {
buf[j] = sum;
}
k = i;
for (j = 0; j <= h-2; j+=2, k+=w2) {
buf[j+half_kernel] = dst_d[k];
buf[j+half_kernel+1] = dst_d[k+w];
}
for (; j < h; ++j, k+=w) {
buf[j+half_kernel] = dst_d[k];
}
sum = dst_d[(h-1)*w + i];
for (j = h; j < half_kernel + h; ++j) {
buf[j + half_kernel] = sum;
}
dp = i;
for (j = 0; j <= h-4; j+=4, dp+=w4) {
sum = buf[j] * f0,
sum1 = buf[j+1] * f0,
sum2 = buf[j+2] * f0,
sum3 = buf[j+3] * f0;
for (k = 1; k < kernel_size; ++k) {
fk = filter[k];
sum += buf[k + j] * fk;
sum1 += buf[k + j+1] * fk;
sum2 += buf[k + j+2] * fk;
sum3 += buf[k + j+3] * fk;
}
dst_d[dp] = sum;
dst_d[dp+w] = sum1;
dst_d[dp+w2] = sum2;
dst_d[dp+w3] = sum3;
}
for (; j < h; ++j, dp+=w) {
sum = buf[j] * f0;
for (k = 1; k < kernel_size; ++k) {
sum += buf[k + j] * filter[k];
}
dst_d[dp] = sum;
}
}
};
return {
// TODO: add support for RGB/BGR order
// for raw arrays
grayscale: function(src, w, h, dst, code) {
// this is default image data representation in browser
if (typeof code === "undefined") { code = jsfeat.COLOR_RGBA2GRAY; }
var x=0, y=0, i=0, j=0, ir=0,jr=0;
var coeff_r = 4899, coeff_g = 9617, coeff_b = 1868, cn = 4;
if(code == jsfeat.COLOR_BGRA2GRAY || code == jsfeat.COLOR_BGR2GRAY) {
coeff_r = 1868;
coeff_b = 4899;
}
if(code == jsfeat.COLOR_RGB2GRAY || code == jsfeat.COLOR_BGR2GRAY) {
cn = 3;
}
var cn2 = cn<<1, cn3 = (cn*3)|0;
dst.resize(w, h, 1);
var dst_u8 = dst.data;
for(y = 0; y < h; ++y, j+=w, i+=w*cn) {
for(x = 0, ir = i, jr = j; x <= w-4; x+=4, ir+=cn<<2, jr+=4) {
dst_u8[jr] = (src[ir] * coeff_r + src[ir+1] * coeff_g + src[ir+2] * coeff_b + 8192) >> 14;
dst_u8[jr + 1] = (src[ir+cn] * coeff_r + src[ir+cn+1] * coeff_g + src[ir+cn+2] * coeff_b + 8192) >> 14;
dst_u8[jr + 2] = (src[ir+cn2] * coeff_r + src[ir+cn2+1] * coeff_g + src[ir+cn2+2] * coeff_b + 8192) >> 14;
dst_u8[jr + 3] = (src[ir+cn3] * coeff_r + src[ir+cn3+1] * coeff_g + src[ir+cn3+2] * coeff_b + 8192) >> 14;
}
for (; x < w; ++x, ++jr, ir+=cn) {
dst_u8[jr] = (src[ir] * coeff_r + src[ir+1] * coeff_g + src[ir+2] * coeff_b + 8192) >> 14;
}
}
},
// derived from CCV library
resample: function(src, dst, nw, nh) {
var h=src.rows,w=src.cols;
if (h > nh && w > nw) {
dst.resize(nw, nh, src.channel);
// using the fast alternative (fix point scale, 0x100 to avoid overflow)
if (src.type&jsfeat.U8_t && dst.type&jsfeat.U8_t && h * w / (nh * nw) < 0x100) {
_resample_u8(src, dst, nw, nh);
} else {
_resample(src, dst, nw, nh);
}
}
},
box_blur_gray: function(src, dst, radius, options) {
if (typeof options === "undefined") { options = 0; }
var w=src.cols, h=src.rows, h2=h<<1, w2=w<<1;
var i=0,x=0,y=0,end=0;
var windowSize = ((radius << 1) + 1)|0;
var radiusPlusOne = (radius + 1)|0, radiusPlus2 = (radiusPlusOne+1)|0;
var scale = options&jsfeat.BOX_BLUR_NOSCALE ? 1 : (1.0 / (windowSize*windowSize));
var tmp_buff = jsfeat.cache.get_buffer((w*h)<<2);
var sum=0, dstIndex=0, srcIndex = 0, nextPixelIndex=0, previousPixelIndex=0;
var data_i32 = tmp_buff.i32; // to prevent overflow
var data_u8 = src.data;
var hold=0;
dst.resize(w, h, src.channel);
// first pass
// no need to scale
//data_u8 = src.data;
//data_i32 = tmp;
for (y = 0; y < h; ++y) {
dstIndex = y;
sum = radiusPlusOne * data_u8[srcIndex];
for(i = (srcIndex+1)|0, end=(srcIndex+radius)|0; i <= end; ++i) {
sum += data_u8[i];
}
nextPixelIndex = (srcIndex + radiusPlusOne)|0;
previousPixelIndex = srcIndex;
hold = data_u8[previousPixelIndex];
for(x = 0; x < radius; ++x, dstIndex += h) {
data_i32[dstIndex] = sum;
sum += data_u8[nextPixelIndex]- hold;
nextPixelIndex ++;
}
for(; x < w-radiusPlus2; x+=2, dstIndex += h2) {
data_i32[dstIndex] = sum;
sum += data_u8[nextPixelIndex]- data_u8[previousPixelIndex];
data_i32[dstIndex+h] = sum;
sum += data_u8[nextPixelIndex+1]- data_u8[previousPixelIndex+1];
nextPixelIndex +=2;
previousPixelIndex +=2;
}
for(; x < w-radiusPlusOne; ++x, dstIndex += h) {
data_i32[dstIndex] = sum;
sum += data_u8[nextPixelIndex]- data_u8[previousPixelIndex];
nextPixelIndex ++;
previousPixelIndex ++;
}
hold = data_u8[nextPixelIndex-1];
for(; x < w; ++x, dstIndex += h) {
data_i32[dstIndex] = sum;
sum += hold- data_u8[previousPixelIndex];
previousPixelIndex ++;
}
srcIndex += w;
}
//
// second pass
srcIndex = 0;
//data_i32 = tmp; // this is a transpose
data_u8 = dst.data;
// dont scale result
if(scale == 1) {
for (y = 0; y < w; ++y) {
dstIndex = y;
sum = radiusPlusOne * data_i32[srcIndex];
for(i = (srcIndex+1)|0, end=(srcIndex+radius)|0; i <= end; ++i) {
sum += data_i32[i];
}
nextPixelIndex = srcIndex + radiusPlusOne;
previousPixelIndex = srcIndex;
hold = data_i32[previousPixelIndex];
for(x = 0; x < radius; ++x, dstIndex += w) {
data_u8[dstIndex] = sum;
sum += data_i32[nextPixelIndex]- hold;
nextPixelIndex ++;
}
for(; x < h-radiusPlus2; x+=2, dstIndex += w2) {
data_u8[dstIndex] = sum;
sum += data_i32[nextPixelIndex]- data_i32[previousPixelIndex];
data_u8[dstIndex+w] = sum;
sum += data_i32[nextPixelIndex+1]- data_i32[previousPixelIndex+1];
nextPixelIndex +=2;
previousPixelIndex +=2;
}
for(; x < h-radiusPlusOne; ++x, dstIndex += w) {
data_u8[dstIndex] = sum;
sum += data_i32[nextPixelIndex]- data_i32[previousPixelIndex];
nextPixelIndex ++;
previousPixelIndex ++;
}
hold = data_i32[nextPixelIndex-1];
for(; x < h; ++x, dstIndex += w) {
data_u8[dstIndex] = sum;
sum += hold- data_i32[previousPixelIndex];
previousPixelIndex ++;
}
srcIndex += h;
}
} else {
for (y = 0; y < w; ++y) {
dstIndex = y;
sum = radiusPlusOne * data_i32[srcIndex];
for(i = (srcIndex+1)|0, end=(srcIndex+radius)|0; i <= end; ++i) {
sum += data_i32[i];
}
nextPixelIndex = srcIndex + radiusPlusOne;
previousPixelIndex = srcIndex;
hold = data_i32[previousPixelIndex];
for(x = 0; x < radius; ++x, dstIndex += w) {
data_u8[dstIndex] = sum*scale;
sum += data_i32[nextPixelIndex]- hold;
nextPixelIndex ++;
}
for(; x < h-radiusPlus2; x+=2, dstIndex += w2) {
data_u8[dstIndex] = sum*scale;
sum += data_i32[nextPixelIndex]- data_i32[previousPixelIndex];
data_u8[dstIndex+w] = sum*scale;
sum += data_i32[nextPixelIndex+1]- data_i32[previousPixelIndex+1];
nextPixelIndex +=2;
previousPixelIndex +=2;
}
for(; x < h-radiusPlusOne; ++x, dstIndex += w) {
data_u8[dstIndex] = sum*scale;
sum += data_i32[nextPixelIndex]- data_i32[previousPixelIndex];
nextPixelIndex ++;
previousPixelIndex ++;
}
hold = data_i32[nextPixelIndex-1];
for(; x < h; ++x, dstIndex += w) {
data_u8[dstIndex] = sum*scale;
sum += hold- data_i32[previousPixelIndex];
previousPixelIndex ++;
}
srcIndex += h;
}
}
jsfeat.cache.put_buffer(tmp_buff);
},
gaussian_blur: function(src, dst, kernel_size, sigma) {
if (typeof sigma === "undefined") { sigma = 0.0; }
if (typeof kernel_size === "undefined") { kernel_size = 0; }
kernel_size = kernel_size == 0 ? (Math.max(1, (4.0 * sigma + 1.0 - 1e-8)) * 2 + 1)|0 : kernel_size;
var half_kernel = kernel_size >> 1;
var w = src.cols, h = src.rows;
var data_type = src.type, is_u8 = data_type&jsfeat.U8_t;
dst.resize(w, h, src.channel);
var src_d = src.data, dst_d = dst.data;
var buf,filter,buf_sz=(kernel_size + Math.max(h, w))|0;
var buf_node = jsfeat.cache.get_buffer(buf_sz<<2);
var filt_node = jsfeat.cache.get_buffer(kernel_size<<2);
if(is_u8) {
buf = buf_node.i32;
filter = filt_node.i32;
} else if(data_type&jsfeat.S32_t) {
buf = buf_node.i32;
filter = filt_node.f32;
} else {
buf = buf_node.f32;
filter = filt_node.f32;
}
jsfeat.math.get_gaussian_kernel(kernel_size, sigma, filter, data_type);
if(is_u8) {
_convol_u8(buf, src_d, dst_d, w, h, filter, kernel_size, half_kernel);
} else {
_convol(buf, src_d, dst_d, w, h, filter, kernel_size, half_kernel);
}
jsfeat.cache.put_buffer(buf_node);
jsfeat.cache.put_buffer(filt_node);
},
hough_transform: function( img, rho_res, theta_res, threshold ) {
var image = img.data;
var width = img.cols;
var height = img.rows;
var step = width;
min_theta = 0.0;
max_theta = Math.PI;
numangle = Math.round((max_theta - min_theta) / theta_res);
numrho = Math.round(((width + height) * 2 + 1) / rho_res);
irho = 1.0 / rho_res;
var accum = new Int32Array((numangle+2) * (numrho+2)); //typed arrays are initialized to 0
var tabSin = new Float32Array(numangle);
var tabCos = new Float32Array(numangle);
var n=0;
var ang = min_theta;
for(; n < numangle; n++ ) {
tabSin[n] = Math.sin(ang) * irho;
tabCos[n] = Math.cos(ang) * irho;
ang += theta_res;
}
// stage 1. fill accumulator
for( var i = 0; i < height; i++ ) {
for( var j = 0; j < width; j++ ) {
if( image[i * step + j] != 0 ) {
//console.log(r, (n+1) * (numrho+2) + r+1, tabCos[n], tabSin[n]);
for(var n = 0; n < numangle; n++ ) {
var r = Math.round( j * tabCos[n] + i * tabSin[n] );
r += (numrho - 1) / 2;
accum[(n+1) * (numrho+2) + r+1] += 1;
}
}
}
}
// stage 2. find local maximums
//TODO: Consider making a vector class that uses typed arrays
_sort_buf = new Array();
for(var r = 0; r < numrho; r++ ) {
for(var n = 0; n < numangle; n++ ) {
var base = (n+1) * (numrho+2) + r+1;
if( accum[base] > threshold &&
accum[base] > accum[base - 1] && accum[base] >= accum[base + 1] &&
accum[base] > accum[base - numrho - 2] && accum[base] >= accum[base + numrho + 2] ) {
_sort_buf.push(base);
}
}
}
// stage 3. sort the detected lines by accumulator value
_sort_buf.sort(function(l1, l2) {
return accum[l1] > accum[l2] || (accum[l1] == accum[l2] && l1 < l2);
});
// stage 4. store the first min(total,linesMax) lines to the output buffer
linesMax = Math.min(numangle*numrho, _sort_buf.length);
scale = 1.0 / (numrho+2);
lines = new Array();
for( var i = 0; i < linesMax; i++ ) {
var idx = _sort_buf[i];
var n = Math.floor(idx*scale) - 1;
var r = idx - (n+1)*(numrho+2) - 1;
var lrho = (r - (numrho - 1)*0.5) * rho_res;
var langle = n * theta_res;
lines.push([lrho, langle]);
}
return lines;
},
// assume we always need it for u8 image
pyrdown: function(src, dst, sx, sy) {
// this is needed for bbf
if (typeof sx === "undefined") { sx = 0; }
if (typeof sy === "undefined") { sy = 0; }
var w = src.cols, h = src.rows;
var w2 = w >> 1, h2 = h >> 1;
var _w2 = w2 - (sx << 1), _h2 = h2 - (sy << 1);
var x=0,y=0,sptr=sx+sy*w,sline=0,dptr=0,dline=0;
dst.resize(w2, h2, src.channel);
var src_d = src.data, dst_d = dst.data;
for(y = 0; y < _h2; ++y) {
sline = sptr;
dline = dptr;
for(x = 0; x <= _w2-2; x+=2, dline+=2, sline += 4) {
dst_d[dline] = (src_d[sline] + src_d[sline+1] +
src_d[sline+w] + src_d[sline+w+1] + 2) >> 2;
dst_d[dline+1] = (src_d[sline+2] + src_d[sline+3] +
src_d[sline+w+2] + src_d[sline+w+3] + 2) >> 2;
}
for(; x < _w2; ++x, ++dline, sline += 2) {
dst_d[dline] = (src_d[sline] + src_d[sline+1] +
src_d[sline+w] + src_d[sline+w+1] + 2) >> 2;
}
sptr += w << 1;
dptr += w2;
}
},
// dst: [gx,gy,...]
scharr_derivatives: function(src, dst) {
var w = src.cols, h = src.rows;
var dstep = w<<1,x=0,y=0,x1=0,a,b,c,d,e,f;
var srow0=0,srow1=0,srow2=0,drow=0;
var trow0,trow1;
dst.resize(w, h, 2); // 2 channel output gx, gy
var img = src.data, gxgy=dst.data;
var buf0_node = jsfeat.cache.get_buffer((w+2)<<2);
var buf1_node = jsfeat.cache.get_buffer((w+2)<<2);
if(src.type&jsfeat.U8_t || src.type&jsfeat.S32_t) {
trow0 = buf0_node.i32;
trow1 = buf1_node.i32;
} else {
trow0 = buf0_node.f32;
trow1 = buf1_node.f32;
}
for(; y < h; ++y, srow1+=w) {
srow0 = ((y > 0 ? y-1 : 1)*w)|0;
srow2 = ((y < h-1 ? y+1 : h-2)*w)|0;
drow = (y*dstep)|0;
// do vertical convolution
for(x = 0, x1 = 1; x <= w-2; x+=2, x1+=2) {
a = img[srow0+x], b = img[srow2+x];
trow0[x1] = ( (a + b)*3 + (img[srow1+x])*10 );
trow1[x1] = ( b - a );
//
a = img[srow0+x+1], b = img[srow2+x+1];
trow0[x1+1] = ( (a + b)*3 + (img[srow1+x+1])*10 );
trow1[x1+1] = ( b - a );
}
for(; x < w; ++x, ++x1) {
a = img[srow0+x], b = img[srow2+x];
trow0[x1] = ( (a + b)*3 + (img[srow1+x])*10 );
trow1[x1] = ( b - a );
}
// make border
x = (w + 1)|0;
trow0[0] = trow0[1]; trow0[x] = trow0[w];
trow1[0] = trow1[1]; trow1[x] = trow1[w];
// do horizontal convolution, interleave the results and store them
for(x = 0; x <= w-4; x+=4) {
a = trow1[x+2], b = trow1[x+1], c = trow1[x+3], d = trow1[x+4],
e = trow0[x+2], f = trow0[x+3];
gxgy[drow++] = ( e - trow0[x] );
gxgy[drow++] = ( (a + trow1[x])*3 + b*10 );
gxgy[drow++] = ( f - trow0[x+1] );
gxgy[drow++] = ( (c + b)*3 + a*10 );
gxgy[drow++] = ( (trow0[x+4] - e) );
gxgy[drow++] = ( ((d + a)*3 + c*10) );
gxgy[drow++] = ( (trow0[x+5] - f) );
gxgy[drow++] = ( ((trow1[x+5] + c)*3 + d*10) );
}
for(; x < w; ++x) {
gxgy[drow++] = ( (trow0[x+2] - trow0[x]) );
gxgy[drow++] = ( ((trow1[x+2] + trow1[x])*3 + trow1[x+1]*10) );
}
}
jsfeat.cache.put_buffer(buf0_node);
jsfeat.cache.put_buffer(buf1_node);
},
// compute gradient using Sobel kernel [1 2 1] * [-1 0 1]^T
// dst: [gx,gy,...]
sobel_derivatives: function(src, dst) {
var w = src.cols, h = src.rows;
var dstep = w<<1,x=0,y=0,x1=0,a,b,c,d,e,f;
var srow0=0,srow1=0,srow2=0,drow=0;
var trow0,trow1;
dst.resize(w, h, 2); // 2 channel output gx, gy
var img = src.data, gxgy=dst.data;
var buf0_node = jsfeat.cache.get_buffer((w+2)<<2);
var buf1_node = jsfeat.cache.get_buffer((w+2)<<2);
if(src.type&jsfeat.U8_t || src.type&jsfeat.S32_t) {
trow0 = buf0_node.i32;
trow1 = buf1_node.i32;
} else {
trow0 = buf0_node.f32;
trow1 = buf1_node.f32;
}
for(; y < h; ++y, srow1+=w) {
srow0 = ((y > 0 ? y-1 : 1)*w)|0;
srow2 = ((y < h-1 ? y+1 : h-2)*w)|0;
drow = (y*dstep)|0;
// do vertical convolution
for(x = 0, x1 = 1; x <= w-2; x+=2, x1+=2) {
a = img[srow0+x], b = img[srow2+x];
trow0[x1] = ( (a + b) + (img[srow1+x]*2) );
trow1[x1] = ( b - a );
//
a = img[srow0+x+1], b = img[srow2+x+1];
trow0[x1+1] = ( (a + b) + (img[srow1+x+1]*2) );
trow1[x1+1] = ( b - a );
}
for(; x < w; ++x, ++x1) {
a = img[srow0+x], b = img[srow2+x];
trow0[x1] = ( (a + b) + (img[srow1+x]*2) );
trow1[x1] = ( b - a );
}
// make border
x = (w + 1)|0;
trow0[0] = trow0[1]; trow0[x] = trow0[w];
trow1[0] = trow1[1]; trow1[x] = trow1[w];
// do horizontal convolution, interleave the results and store them
for(x = 0; x <= w-4; x+=4) {
a = trow1[x+2], b = trow1[x+1], c = trow1[x+3], d = trow1[x+4],
e = trow0[x+2], f = trow0[x+3];
gxgy[drow++] = ( e - trow0[x] );
gxgy[drow++] = ( a + trow1[x] + b*2 );
gxgy[drow++] = ( f - trow0[x+1] );
gxgy[drow++] = ( c + b + a*2 );
gxgy[drow++] = ( trow0[x+4] - e );
gxgy[drow++] = ( d + a + c*2 );
gxgy[drow++] = ( trow0[x+5] - f );
gxgy[drow++] = ( trow1[x+5] + c + d*2 );
}
for(; x < w; ++x) {
gxgy[drow++] = ( trow0[x+2] - trow0[x] );
gxgy[drow++] = ( trow1[x+2] + trow1[x] + trow1[x+1]*2 );
}
}
jsfeat.cache.put_buffer(buf0_node);
jsfeat.cache.put_buffer(buf1_node);
},
// please note:
// dst_(type) size should be cols = src.cols+1, rows = src.rows+1
compute_integral_image: function(src, dst_sum, dst_sqsum, dst_tilted) {
var w0=src.cols|0,h0=src.rows|0,src_d=src.data;
var w1=(w0+1)|0;
var s=0,s2=0,p=0,pup=0,i=0,j=0,v=0,k=0;
if(dst_sum && dst_sqsum) {
// fill first row with zeros
for(; i < w1; ++i) {
dst_sum[i] = 0, dst_sqsum[i] = 0;
}
p = (w1+1)|0, pup = 1;
for(i = 0, k = 0; i < h0; ++i, ++p, ++pup) {
s = s2 = 0;
for(j = 0; j <= w0-2; j+=2, k+=2, p+=2, pup+=2) {
v = src_d[k];
s += v, s2 += v*v;
dst_sum[p] = dst_sum[pup] + s;
dst_sqsum[p] = dst_sqsum[pup] + s2;
v = src_d[k+1];
s += v, s2 += v*v;
dst_sum[p+1] = dst_sum[pup+1] + s;
dst_sqsum[p+1] = dst_sqsum[pup+1] + s2;
}
for(; j < w0; ++j, ++k, ++p, ++pup) {
v = src_d[k];
s += v, s2 += v*v;
dst_sum[p] = dst_sum[pup] + s;
dst_sqsum[p] = dst_sqsum[pup] + s2;
}
}
} else if(dst_sum) {
// fill first row with zeros
for(; i < w1; ++i) {
dst_sum[i] = 0;
}
p = (w1+1)|0, pup = 1;
for(i = 0, k = 0; i < h0; ++i, ++p, ++pup) {
s = 0;
for(j = 0; j <= w0-2; j+=2, k+=2, p+=2, pup+=2) {
s += src_d[k];
dst_sum[p] = dst_sum[pup] + s;
s += src_d[k+1];
dst_sum[p+1] = dst_sum[pup+1] + s;
}
for(; j < w0; ++j, ++k, ++p, ++pup) {
s += src_d[k];
dst_sum[p] = dst_sum[pup] + s;
}
}
} else if(dst_sqsum) {
// fill first row with zeros
for(; i < w1; ++i) {
dst_sqsum[i] = 0;
}
p = (w1+1)|0, pup = 1;
for(i = 0, k = 0; i < h0; ++i, ++p, ++pup) {
s2 = 0;
for(j = 0; j <= w0-2; j+=2, k+=2, p+=2, pup+=2) {
v = src_d[k];
s2 += v*v;
dst_sqsum[p] = dst_sqsum[pup] + s2;
v = src_d[k+1];
s2 += v*v;
dst_sqsum[p+1] = dst_sqsum[pup+1] + s2;
}
for(; j < w0; ++j, ++k, ++p, ++pup) {
v = src_d[k];
s2 += v*v;
dst_sqsum[p] = dst_sqsum[pup] + s2;
}
}
}
if(dst_tilted) {
// fill first row with zeros
for(i = 0; i < w1; ++i) {
dst_tilted[i] = 0;
}
// diagonal
p = (w1+1)|0, pup = 0;
for(i = 0, k = 0; i < h0; ++i, ++p, ++pup) {
for(j = 0; j <= w0-2; j+=2, k+=2, p+=2, pup+=2) {
dst_tilted[p] = src_d[k] + dst_tilted[pup];
dst_tilted[p+1] = src_d[k+1] + dst_tilted[pup+1];
}
for(; j < w0; ++j, ++k, ++p, ++pup) {
dst_tilted[p] = src_d[k] + dst_tilted[pup];
}
}
// diagonal
p = (w1+w0)|0, pup = w0;
for(i = 0; i < h0; ++i, p+=w1, pup+=w1) {
dst_tilted[p] += dst_tilted[pup];
}
for(j = w0-1; j > 0; --j) {
p = j+h0*w1, pup=p-w1;
for(i = h0; i > 0; --i, p-=w1, pup-=w1) {
dst_tilted[p] += dst_tilted[pup] + dst_tilted[pup+1];
}
}
}
},
equalize_histogram: function(src, dst) {
var w=src.cols,h=src.rows,src_d=src.data;
dst.resize(w, h, src.channel);
var dst_d=dst.data,size=w*h;
var i=0,prev=0,hist0,norm;
var hist0_node = jsfeat.cache.get_buffer(256<<2);
hist0 = hist0_node.i32;
for(; i < 256; ++i) hist0[i] = 0;
for (i = 0; i < size; ++i) {
++hist0[src_d[i]];
}
prev = hist0[0];
for (i = 1; i < 256; ++i) {
prev = hist0[i] += prev;
}
norm = 255 / size;
for (i = 0; i < size; ++i) {
dst_d[i] = (hist0[src_d[i]] * norm + 0.5)|0;
}
jsfeat.cache.put_buffer(hist0_node);
},
canny: function(src, dst, low_thresh, high_thresh) {
var w=src.cols,h=src.rows,src_d=src.data;
dst.resize(w, h, src.channel);
var dst_d=dst.data;
var i=0,j=0,grad=0,w2=w<<1,_grad=0,suppress=0,f=0,x=0,y=0,s=0;
var tg22x=0,tg67x=0;
// cache buffers
var dxdy_node = jsfeat.cache.get_buffer((h * w2)<<2);
var buf_node = jsfeat.cache.get_buffer((3 * (w + 2))<<2);
var map_node = jsfeat.cache.get_buffer(((h+2) * (w + 2))<<2);
var stack_node = jsfeat.cache.get_buffer((h * w)<<2);
var buf = buf_node.i32;
var map = map_node.i32;
var stack = stack_node.i32;
var dxdy = dxdy_node.i32;
var dxdy_m = new jsfeat.matrix_t(w, h, jsfeat.S32C2_t, dxdy_node.data);
var row0=1,row1=(w+2+1)|0,row2=(2*(w+2)+1)|0,map_w=(w+2)|0,map_i=(map_w+1)|0,stack_i=0;
this.sobel_derivatives(src, dxdy_m);
if(low_thresh > high_thresh) {
i = low_thresh;
low_thresh = high_thresh;
high_thresh = i;
}
i = (3 * (w + 2))|0;
while(--i>=0) {
buf[i] = 0;
}
i = ((h+2) * (w + 2))|0;
while(--i>=0) {
map[i] = 0;
}
for (; j < w; ++j, grad+=2) {
//buf[row1+j] = Math.abs(dxdy[grad]) + Math.abs(dxdy[grad+1]);
x = dxdy[grad], y = dxdy[grad+1];
//buf[row1+j] = x*x + y*y;
buf[row1+j] = ((x ^ (x >> 31)) - (x >> 31)) + ((y ^ (y >> 31)) - (y >> 31));
}
for(i=1; i <= h; ++i, grad+=w2) {
if(i == h) {
j = row2+w;
while(--j>=row2) {
buf[j] = 0;
}
} else {
for (j = 0; j < w; j++) {
//buf[row2+j] = Math.abs(dxdy[grad+(j<<1)]) + Math.abs(dxdy[grad+(j<<1)+1]);
x = dxdy[grad+(j<<1)], y = dxdy[grad+(j<<1)+1];
//buf[row2+j] = x*x + y*y;
buf[row2+j] = ((x ^ (x >> 31)) - (x >> 31)) + ((y ^ (y >> 31)) - (y >> 31));
}
}
_grad = (grad - w2)|0;
map[map_i-1] = 0;
suppress = 0;
for(j = 0; j < w; ++j, _grad+=2) {
f = buf[row1+j];
if (f > low_thresh) {
x = dxdy[_grad];
y = dxdy[_grad+1];
s = x ^ y;
// seems ot be faster than Math.abs
x = ((x ^ (x >> 31)) - (x >> 31))|0;
y = ((y ^ (y >> 31)) - (y >> 31))|0;
//x * tan(22.5) x * tan(67.5) == 2 * x + x * tan(22.5)
tg22x = x * 13573;
tg67x = tg22x + ((x + x) << 15);
y <<= 15;
if (y < tg22x) {
if (f > buf[row1+j-1] && f >= buf[row1+j+1]) {
if (f > high_thresh && !suppress && map[map_i+j-map_w] != 2) {
map[map_i+j] = 2;
suppress = 1;
stack[stack_i++] = map_i + j;
} else {
map[map_i+j] = 1;
}
continue;
}
} else if (y > tg67x) {
if (f > buf[row0+j] && f >= buf[row2+j]) {
if (f > high_thresh && !suppress && map[map_i+j-map_w] != 2) {
map[map_i+j] = 2;
suppress = 1;
stack[stack_i++] = map_i + j;
} else {
map[map_i+j] = 1;
}
continue;
}
} else {
s = s < 0 ? -1 : 1;
if (f > buf[row0+j-s] && f > buf[row2+j+s]) {
if (f > high_thresh && !suppress && map[map_i+j-map_w] != 2) {
map[map_i+j] = 2;
suppress = 1;
stack[stack_i++] = map_i + j;
} else {
map[map_i+j] = 1;
}
continue;
}
}
}
map[map_i+j] = 0;
suppress = 0;
}
map[map_i+w] = 0;
map_i += map_w;
j = row0;
row0 = row1;
row1 = row2;
row2 = j;
}
j = map_i - map_w - 1;
for(i = 0; i < map_w; ++i, ++j) {
map[j] = 0;
}
// path following
while(stack_i > 0) {
map_i = stack[--stack_i];
map_i -= map_w+1;
if(map[map_i] == 1) map[map_i] = 2, stack[stack_i++] = map_i;
map_i += 1;
if(map[map_i] == 1) map[map_i] = 2, stack[stack_i++] = map_i;
map_i += 1;
if(map[map_i] == 1) map[map_i] = 2, stack[stack_i++] = map_i;
map_i += map_w;
if(map[map_i] == 1) map[map_i] = 2, stack[stack_i++] = map_i;
map_i -= 2;
if(map[map_i] == 1) map[map_i] = 2, stack[stack_i++] = map_i;
map_i += map_w;
if(map[map_i] == 1) map[map_i] = 2, stack[stack_i++] = map_i;
map_i += 1;
if(map[map_i] == 1) map[map_i] = 2, stack[stack_i++] = map_i;
map_i += 1;
if(map[map_i] == 1) map[map_i] = 2, stack[stack_i++] = map_i;
}
map_i = map_w + 1;
row0 = 0;
for(i = 0; i < h; ++i, map_i+=map_w) {
for(j = 0; j < w; ++j) {
dst_d[row0++] = (map[map_i+j] == 2) * 0xff;
}
}
// free buffers
jsfeat.cache.put_buffer(dxdy_node);
jsfeat.cache.put_buffer(buf_node);
jsfeat.cache.put_buffer(map_node);
jsfeat.cache.put_buffer(stack_node);
},
// transform is 3x3 matrix_t
warp_perspective: function(src, dst, transform, fill_value) {
if (typeof fill_value === "undefined") { fill_value = 0; }
var src_width=src.cols|0, src_height=src.rows|0, dst_width=dst.cols|0, dst_height=dst.rows|0;
var src_d=src.data, dst_d=dst.data;
var x=0,y=0,off=0,ixs=0,iys=0,xs=0.0,ys=0.0,xs0=0.0,ys0=0.0,ws=0.0,sc=0.0,a=0.0,b=0.0,p0=0.0,p1=0.0;
var td=transform.data;
var m00=td[0],m01=td[1],m02=td[2],
m10=td[3],m11=td[4],m12=td[5],
m20=td[6],m21=td[7],m22=td[8];
for(var dptr = 0; y < dst_height; ++y) {
xs0 = m01 * y + m02,
ys0 = m11 * y + m12,
ws = m21 * y + m22;
for(x = 0; x < dst_width; ++x, ++dptr, xs0+=m00, ys0+=m10, ws+=m20) {
sc = 1.0 / ws;
xs = xs0 * sc, ys = ys0 * sc;
ixs = xs | 0, iys = ys | 0;
if(xs > 0 && ys > 0 && ixs < (src_width - 1) && iys < (src_height - 1)) {
a = Math.max(xs - ixs, 0.0);
b = Math.max(ys - iys, 0.0);
off = (src_width*iys + ixs)|0;
p0 = src_d[off] + a * (src_d[off+1] - src_d[off]);
p1 = src_d[off+src_width] + a * (src_d[off+src_width+1] - src_d[off+src_width]);
dst_d[dptr] = p0 + b * (p1 - p0);
}
else dst_d[dptr] = fill_value;
}
}
},
// transform is 3x3 or 2x3 matrix_t only first 6 values referenced
warp_affine: function(src, dst, transform, fill_value) {
if (typeof fill_value === "undefined") { fill_value = 0; }
var src_width=src.cols, src_height=src.rows, dst_width=dst.cols, dst_height=dst.rows;
var src_d=src.data, dst_d=dst.data;
var x=0,y=0,off=0,ixs=0,iys=0,xs=0.0,ys=0.0,a=0.0,b=0.0,p0=0.0,p1=0.0;
var td=transform.data;
var m00=td[0],m01=td[1],m02=td[2],
m10=td[3],m11=td[4],m12=td[5];
for(var dptr = 0; y < dst_height; ++y) {
xs = m01 * y + m02;
ys = m11 * y + m12;
for(x = 0; x < dst_width; ++x, ++dptr, xs+=m00, ys+=m10) {
ixs = xs | 0; iys = ys | 0;
if(ixs >= 0 && iys >= 0 && ixs < (src_width - 1) && iys < (src_height - 1)) {
a = xs - ixs;
b = ys - iys;
off = src_width*iys + ixs;
p0 = src_d[off] + a * (src_d[off+1] - src_d[off]);
p1 = src_d[off+src_width] + a * (src_d[off+src_width+1] - src_d[off+src_width]);
dst_d[dptr] = p0 + b * (p1 - p0);
}
else dst_d[dptr] = fill_value;
}
}
},
// Basic RGB Skin detection filter
// from http://popscan.blogspot.fr/2012/08/skin-detection-in-digital-images.html
skindetector: function(src,dst) {
var r,g,b,j;
var i = src.width*src.height;
while(i--){
j = i*4;
r = src.data[j];
g = src.data[j+1];
b = src.data[j+2];
if((r>95)&&(g>40)&&(b>20)
&&(r>g)&&(r>b)
&&(r-Math.min(g,b)>15)
&&(Math.abs(r-g)>15)){
dst[i] = 255;
} else {
dst[i] = 0;
}
}
}
};
})();
global.imgproc = imgproc;
})(jsfeat);
/**
* @author Eugene Zatepyakin / http://inspirit.ru/
*
* This is FAST corner detector, contributed to OpenCV by the author, Edward Rosten.
*/
/*
The references are:
* Machine learning for high-speed corner detection,
E. Rosten and T. Drummond, ECCV 2006
* Faster and better: A machine learning approach to corner detection
E. Rosten, R. Porter and T. Drummond, PAMI, 2009
*/
(function(global) {
"use strict";
//
var fast_corners = (function() {
var offsets16 = new Int32Array([0, 3, 1, 3, 2, 2, 3, 1, 3, 0, 3, -1, 2, -2, 1, -3, 0, -3, -1, -3, -2, -2, -3, -1, -3, 0, -3, 1, -2, 2, -1, 3]);
var threshold_tab = new Uint8Array(512);
var pixel_off = new Int32Array(25);
var score_diff = new Int32Array(25);
// private functions
var _cmp_offsets = function(pixel, step, pattern_size) {
var k = 0;
var offsets = offsets16;
for( ; k < pattern_size; ++k ) {
pixel[k] = offsets[k<<1] + offsets[(k<<1)+1] * step;
}
for( ; k < 25; ++k ) {
pixel[k] = pixel[k - pattern_size];
}
},
_cmp_score_16 = function(src, off, pixel, d, threshold) {
var N = 25, k = 0, v = src[off];
var a0 = threshold,a=0,b0=0,b=0;
for( ; k < N; ++k ) {
d[k] = v - src[off+pixel[k]];
}
for( k = 0; k < 16; k += 2 ) {
a = Math.min(d[k+1], d[k+2]);
a = Math.min(a, d[k+3]);
if( a <= a0 ) continue;
a = Math.min(a, d[k+4]);
a = Math.min(a, d[k+5]);
a = Math.min(a, d[k+6]);
a = Math.min(a, d[k+7]);
a = Math.min(a, d[k+8]);
a0 = Math.max(a0, Math.min(a, d[k]));
a0 = Math.max(a0, Math.min(a, d[k+9]));
}
b0 = -a0;
for( k = 0; k < 16; k += 2 ) {
b = Math.max(d[k+1], d[k+2]);
b = Math.max(b, d[k+3]);
b = Math.max(b, d[k+4]);
b = Math.max(b, d[k+5]);
if( b >= b0 ) continue;
b = Math.max(b, d[k+6]);
b = Math.max(b, d[k+7]);
b = Math.max(b, d[k+8]);
b0 = Math.min(b0, Math.max(b, d[k]));
b0 = Math.min(b0, Math.max(b, d[k+9]));
}
return -b0-1;
};
var _threshold = 20;
return {
set_threshold: function(threshold) {
_threshold = Math.min(Math.max(threshold, 0), 255);
for (var i = -255; i <= 255; ++i) {
threshold_tab[(i + 255)] = (i < -_threshold ? 1 : (i > _threshold ? 2 : 0));
}
return _threshold;
},
detect: function(src, corners, border) {
if (typeof border === "undefined") { border = 3; }
var K = 8, N = 25;
var img = src.data, w = src.cols, h = src.rows;
var i=0, j=0, k=0, vt=0, x=0, m3=0;
var buf_node = jsfeat.cache.get_buffer(3 * w);
var cpbuf_node = jsfeat.cache.get_buffer(((w+1)*3)<<2);
var buf = buf_node.u8;
var cpbuf = cpbuf_node.i32;
var pixel = pixel_off;
var sd = score_diff;
var sy = Math.max(3, border);
var ey = Math.min((h-2), (h-border));
var sx = Math.max(3, border);
var ex = Math.min((w - 3), (w - border));
var _count = 0, corners_cnt = 0, pt;
var score_func = _cmp_score_16;
var thresh_tab = threshold_tab;
var threshold = _threshold;
var v=0,tab=0,d=0,ncorners=0,cornerpos=0,curr=0,ptr=0,prev=0,pprev=0;
var jp1=0,jm1=0,score=0;
_cmp_offsets(pixel, w, 16);
// local vars are faster?
var pixel0 = pixel[0];
var pixel1 = pixel[1];
var pixel2 = pixel[2];
var pixel3 = pixel[3];
var pixel4 = pixel[4];
var pixel5 = pixel[5];
var pixel6 = pixel[6];
var pixel7 = pixel[7];
var pixel8 = pixel[8];
var pixel9 = pixel[9];
var pixel10 = pixel[10];
var pixel11 = pixel[11];
var pixel12 = pixel[12];
var pixel13 = pixel[13];
var pixel14 = pixel[14];
var pixel15 = pixel[15];
for(i = 0; i < w*3; ++i) {
buf[i] = 0;
}
for(i = sy; i < ey; ++i) {
ptr = ((i * w) + sx)|0;
m3 = (i - 3)%3;
curr = (m3*w)|0;
cornerpos = (m3*(w+1))|0;
for (j = 0; j < w; ++j) buf[curr+j] = 0;
ncorners = 0;
if( i < (ey - 1) ) {
j = sx;
for( ; j < ex; ++j, ++ptr ) {
v = img[ptr];
tab = ( - v + 255 );
d = ( thresh_tab[tab+img[ptr+pixel0]] | thresh_tab[tab+img[ptr+pixel8]] );
if( d == 0 ) {
continue;
}
d &= ( thresh_tab[tab+img[ptr+pixel2]] | thresh_tab[tab+img[ptr+pixel10]] );
d &= ( thresh_tab[tab+img[ptr+pixel4]] | thresh_tab[tab+img[ptr+pixel12]] );
d &= ( thresh_tab[tab+img[ptr+pixel6]] | thresh_tab[tab+img[ptr+pixel14]] );
if( d == 0 ) {
continue;
}
d &= ( thresh_tab[tab+img[ptr+pixel1]] | thresh_tab[tab+img[ptr+pixel9]] );
d &= ( thresh_tab[tab+img[ptr+pixel3]] | thresh_tab[tab+img[ptr+pixel11]] );
d &= ( thresh_tab[tab+img[ptr+pixel5]] | thresh_tab[tab+img[ptr+pixel13]] );
d &= ( thresh_tab[tab+img[ptr+pixel7]] | thresh_tab[tab+img[ptr+pixel15]] );
if( d & 1 ) {
vt = (v - threshold);
_count = 0;
for( k = 0; k < N; ++k ) {
x = img[(ptr+pixel[k])];
if(x < vt) {
++_count;
if( _count > K ) {
++ncorners;
cpbuf[cornerpos+ncorners] = j;
buf[curr+j] = score_func(img, ptr, pixel, sd, threshold);
break;
}
}
else {
_count = 0;
}
}
}
if( d & 2 ) {
vt = (v + threshold);
_count = 0;
for( k = 0; k < N; ++k ) {
x = img[(ptr+pixel[k])];
if(x > vt) {
++_count;
if( _count > K ) {
++ncorners;
cpbuf[cornerpos+ncorners] = j;
buf[curr+j] = score_func(img, ptr, pixel, sd, threshold);
break;
}
}
else {
_count = 0;
}
}
}
}
}
cpbuf[cornerpos+w] = ncorners;
if ( i == sy ) {
continue;
}
m3 = (i - 4 + 3)%3;
prev = (m3*w)|0;
cornerpos = (m3*(w+1))|0;
m3 = (i - 5 + 3)%3;
pprev = (m3*w)|0;
ncorners = cpbuf[cornerpos+w];
for( k = 0; k < ncorners; ++k ) {
j = cpbuf[cornerpos+k];
jp1 = (j+1)|0;
jm1 = (j-1)|0;
score = buf[prev+j];
if( (score > buf[prev+jp1] && score > buf[prev+jm1] &&
score > buf[pprev+jm1] && score > buf[pprev+j] && score > buf[pprev+jp1] &&
score > buf[curr+jm1] && score > buf[curr+j] && score > buf[curr+jp1]) ) {
// save corner
pt = corners[corners_cnt];
pt.x = j, pt.y = (i-1), pt.score = score;
corners_cnt++;
}
}
} // y loop
jsfeat.cache.put_buffer(buf_node);
jsfeat.cache.put_buffer(cpbuf_node);
return corners_cnt;
}
};
})();
global.fast_corners = fast_corners;
fast_corners.set_threshold(20); // set default
})(jsfeat);
/**
* @author Eugene Zatepyakin / http://inspirit.ru/
*
* Copyright 2007 Computer Vision Lab,
* Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland.
* @author Vincent Lepetit (http://cvlab.epfl.ch/~lepetit)
*/
(function(global) {
"use strict";
//
var yape06 = (function() {
var compute_laplacian = function(src, dst, w, h, Dxx, Dyy, sx,sy, ex,ey) {
var y=0,x=0,yrow=(sy*w+sx)|0,row=yrow;
for(y = sy; y < ey; ++y, yrow+=w, row = yrow) {
for(x = sx; x < ex; ++x, ++row) {
dst[row] = -4 * src[row] + src[row+Dxx] + src[row-Dxx] + src[row+Dyy] + src[row-Dyy];
}
}
};
var hessian_min_eigen_value = function(src, off, tr, Dxx, Dyy, Dxy, Dyx) {
var Ixx = -2 * src[off] + src[off + Dxx] + src[off - Dxx];
var Iyy = -2 * src[off] + src[off + Dyy] + src[off - Dyy];
var Ixy = src[off + Dxy] + src[off - Dxy] - src[off + Dyx] - src[off - Dyx];
var sqrt_delta = ( Math.sqrt(((Ixx - Iyy) * (Ixx - Iyy) + 4 * Ixy * Ixy) ) )|0;
return Math.min(Math.abs(tr - sqrt_delta), Math.abs(-(tr + sqrt_delta)));
};
return {
laplacian_threshold: 30,
min_eigen_value_threshold: 25,
detect: function(src, points, border) {
if (typeof border === "undefined") { border = 5; }
var x=0,y=0;
var w=src.cols, h=src.rows, srd_d=src.data;
var Dxx = 5, Dyy = (5 * w)|0;
var Dxy = (3 + 3 * w)|0, Dyx = (3 - 3 * w)|0;
var lap_buf = jsfeat.cache.get_buffer((w*h)<<2);
var laplacian = lap_buf.i32;
var lv=0, row=0,rowx=0,min_eigen_value=0,pt;
var number_of_points = 0;
var lap_thresh = this.laplacian_threshold;
var eigen_thresh = this.min_eigen_value_threshold;
var sx = Math.max(5, border)|0;
var sy = Math.max(3, border)|0;
var ex = Math.min(w-5, w-border)|0;
var ey = Math.min(h-3, h-border)|0;
x = w*h;
while(--x>=0) {laplacian[x]=0;}
compute_laplacian(srd_d, laplacian, w, h, Dxx, Dyy, sx,sy, ex,ey);
row = (sy*w+sx)|0;
for(y = sy; y < ey; ++y, row += w) {
for(x = sx, rowx=row; x < ex; ++x, ++rowx) {
lv = laplacian[rowx];
if ((lv < -lap_thresh &&
lv < laplacian[rowx - 1] && lv < laplacian[rowx + 1] &&
lv < laplacian[rowx - w] && lv < laplacian[rowx + w] &&
lv < laplacian[rowx - w - 1] && lv < laplacian[rowx + w - 1] &&
lv < laplacian[rowx - w + 1] && lv < laplacian[rowx + w + 1])
||
(lv > lap_thresh &&
lv > laplacian[rowx - 1] && lv > laplacian[rowx + 1] &&
lv > laplacian[rowx - w] && lv > laplacian[rowx + w] &&
lv > laplacian[rowx - w - 1] && lv > laplacian[rowx + w - 1] &&
lv > laplacian[rowx - w + 1] && lv > laplacian[rowx + w + 1])
) {
min_eigen_value = hessian_min_eigen_value(srd_d, rowx, lv, Dxx, Dyy, Dxy, Dyx);
if (min_eigen_value > eigen_thresh) {
pt = points[number_of_points];
pt.x = x, pt.y = y, pt.score = min_eigen_value;
++number_of_points;
++x, ++rowx; // skip next pixel since this is maxima in 3x3
}
}
}
}
jsfeat.cache.put_buffer(lap_buf);
return number_of_points;
}
};
})();
global.yape06 = yape06;
})(jsfeat);
/**
* @author Eugene Zatepyakin / http://inspirit.ru/
*
* Copyright 2007 Computer Vision Lab,
* Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland.
*/
(function(global) {
"use strict";
//
var yape = (function() {
var precompute_directions = function(step, dirs, R) {
var i = 0;
var x, y;
x = R;
for(y = 0; y < x; y++, i++)
{
x = (Math.sqrt((R * R - y * y)) + 0.5)|0;
dirs[i] = (x + step * y);
}
for(x-- ; x < y && x >= 0; x--, i++)
{
y = (Math.sqrt((R * R - x * x)) + 0.5)|0;
dirs[i] = (x + step * y);
}
for( ; -x < y; x--, i++)
{
y = (Math.sqrt((R * R - x * x)) + 0.5)|0;
dirs[i] = (x + step * y);
}
for(y-- ; y >= 0; y--, i++)
{
x = (-Math.sqrt((R * R - y * y)) - 0.5)|0;
dirs[i] = (x + step * y);
}
for(; y > x; y--, i++)
{
x = (-Math.sqrt((R * R - y * y)) - 0.5)|0;
dirs[i] = (x + step * y);
}
for(x++ ; x <= 0; x++, i++)
{
y = (-Math.sqrt((R * R - x * x)) - 0.5)|0;
dirs[i] = (x + step * y);
}
for( ; x < -y; x++, i++)
{
y = (-Math.sqrt((R * R - x * x)) - 0.5)|0;
dirs[i] = (x + step * y);
}
for(y++ ; y < 0; y++, i++)
{
x = (Math.sqrt((R * R - y * y)) + 0.5)|0;
dirs[i] = (x + step * y);
}
dirs[i] = dirs[0];
dirs[i + 1] = dirs[1];
return i;
};
var third_check = function (Sb, off, step) {
var n = 0;
if(Sb[off+1] != 0) n++;
if(Sb[off-1] != 0) n++;
if(Sb[off+step] != 0) n++;
if(Sb[off+step+1] != 0) n++;
if(Sb[off+step-1] != 0) n++;
if(Sb[off-step] != 0) n++;
if(Sb[off-step+1] != 0) n++;
if(Sb[off-step-1] != 0) n++;
return n;
};
var is_local_maxima = function(p, off, v, step, neighborhood) {
var x, y;
if (v > 0) {
off -= step*neighborhood;
for (y= -neighborhood; y<=neighborhood; ++y) {
for (x= -neighborhood; x<=neighborhood; ++x) {
if (p[off+x] > v) return false;
}
off += step;
}
} else {
off -= step*neighborhood;
for (y= -neighborhood; y<=neighborhood; ++y) {
for (x= -neighborhood; x<=neighborhood; ++x) {
if (p[off+x] < v) return false;
}
off += step;
}
}
return true;
};
var perform_one_point = function(I, x, Scores, Im, Ip, dirs, opposite, dirs_nb) {
var score = 0;
var a = 0, b = (opposite - 1)|0;
var A=0, B0=0, B1=0, B2=0;
var state=0;
// WE KNOW THAT NOT(A ~ I0 & B1 ~ I0):
A = I[x+dirs[a]];
if ((A <= Ip)) {
if ((A >= Im)) { // A ~ I0
B0 = I[x+dirs[b]];
if ((B0 <= Ip)) {
if ((B0 >= Im)) { Scores[x] = 0; return; }
else {
b++; B1 = I[x+dirs[b]];
if ((B1 > Ip)) {
b++; B2 = I[x+dirs[b]];
if ((B2 > Ip)) state = 3;
else if ((B2 < Im)) state = 6;
else { Scores[x] = 0; return; } // A ~ I0, B2 ~ I0
}
else/* if ((B1 < Im))*/ {
b++; B2 = I[x+dirs[b]];
if ((B2 > Ip)) state = 7;
else if ((B2 < Im)) state = 2;
else { Scores[x] = 0; return; } // A ~ I0, B2 ~ I0
}
//else { Scores[x] = 0; return; } // A ~ I0, B1 ~ I0
}
}
else { // B0 < I0
b++; B1 = I[x+dirs[b]];
if ((B1 > Ip)) {
b++; B2 = I[x+dirs[b]];
if ((B2 > Ip)) state = 3;
else if ((B2 < Im)) state = 6;
else { Scores[x] = 0; return; } // A ~ I0, B2 ~ I0
}
else if ((B1 < Im)) {
b++; B2 = I[x+dirs[b]];
if ((B2 > Ip)) state = 7;
else if ((B2 < Im)) state = 2;
else { Scores[x] = 0; return; } // A ~ I0, B2 ~ I0
}
else { Scores[x] = 0; return; } // A ~ I0, B1 ~ I0
}
}
else { // A > I0
B0 = I[x+dirs[b]];
if ((B0 > Ip)) { Scores[x] = 0; return; }
b++; B1 = I[x+dirs[b]];
if ((B1 > Ip)) { Scores[x] = 0; return; }
b++; B2 = I[x+dirs[b]];
if ((B2 > Ip)) { Scores[x] = 0; return; }
state = 1;
}
}
else // A < I0
{
B0 = I[x+dirs[b]];
if ((B0 < Im)) { Scores[x] = 0; return; }
b++; B1 = I[x+dirs[b]];
if ((B1 < Im)) { Scores[x] = 0; return; }
b++; B2 = I[x+dirs[b]];
if ((B2 < Im)) { Scores[x] = 0; return; }
state = 0;
}
for(a = 1; a <= opposite; a++)
{
A = I[x+dirs[a]];
switch(state)
{
case 0:
if ((A > Ip)) {
B1 = B2; b++; B2 = I[x+dirs[b]];
if ((B2 < Im)) { Scores[x] = 0; return; }
{ score -= A + B1; state = 0; break; }
}
if ((A < Im)) {
if ((B1 > Ip)) { Scores[x] = 0; return; }
if ((B2 > Ip)) { Scores[x] = 0; return; }
B1 = B2; b++; B2 = I[x+dirs[b]];
if ((B2 > Ip)) { Scores[x] = 0; return; }
{ score -= A + B1; state = 8; break; }
}
// A ~ I0
if ((B1 <= Ip)) { Scores[x] = 0; return; }
if ((B2 <= Ip)) { Scores[x] = 0; return; }
B1 = B2; b++; B2 = I[x+dirs[b]];
if ((B2 > Ip)) { score -= A + B1; state = 3; break; };
if ((B2 < Im)) { score -= A + B1; state = 6; break; };
{ Scores[x] = 0; return; }
case 1:
if ((A < Im)) {
B1 = B2; b++; B2 = I[x+dirs[b]];
if ((B2 > Ip)) { Scores[x] = 0; return; }
{ score -= A + B1; state = 1; break; }
}
if ((A > Ip)) {
if ((B1 < Im)) { Scores[x] = 0; return; }
if ((B2 < Im)) { Scores[x] = 0; return; }
B1 = B2; b++; B2 = I[x+dirs[b]];
if ((B2 < Im)) { Scores[x] = 0; return; }
{ score -= A + B1; state = 9; break; }
}
// A ~ I0
if ((B1 >= Im)) { Scores[x] = 0; return; }
if ((B2 >= Im)) { Scores[x] = 0; return; }
B1 = B2; b++; B2 = I[x+dirs[b]];
if ((B2 < Im)) { score -= A + B1; state = 2; break; };
if ((B2 > Ip)) { score -= A + B1; state = 7; break; };
{ Scores[x] = 0; return; }
case 2:
if ((A > Ip)) { Scores[x] = 0; return; }
B1 = B2; b++; B2 = I[x+dirs[b]];
if ((A < Im))
{
if ((B2 > Ip)) { Scores[x] = 0; return; }
{ score -= A + B1; state = 4; break; }
}
// A ~ I0
if ((B2 > Ip)) { score -= A + B1; state = 7; break; };
if ((B2 < Im)) { score -= A + B1; state = 2; break; };
{ Scores[x] = 0; return; } // A ~ I0, B2 ~ I0
case 3:
if ((A < Im)) { Scores[x] = 0; return; }
B1 = B2; b++; B2 = I[x+dirs[b]];
if ((A > Ip)) {
if ((B2 < Im)) { Scores[x] = 0; return; }
{ score -= A + B1; state = 5; break; }
}
// A ~ I0
if ((B2 > Ip)) { score -= A + B1; state = 3; break; };
if ((B2 < Im)) { score -= A + B1; state = 6; break; };
{ Scores[x] = 0; return; }
case 4:
if ((A > Ip)) { Scores[x] = 0; return; }
if ((A < Im)) {
B1 = B2; b++; B2 = I[x+dirs[b]];
if ((B2 > Ip)) { Scores[x] = 0; return; }
{ score -= A + B1; state = 1; break; }
}
if ((B2 >= Im)) { Scores[x] = 0; return; }
B1 = B2; b++; B2 = I[x+dirs[b]];
if ((B2 < Im)) { score -= A + B1; state = 2; break; };
if ((B2 > Ip)) { score -= A + B1; state = 7; break; };
{ Scores[x] = 0; return; }
case 5:
if ((A < Im)) { Scores[x] = 0; return; }
if ((A > Ip)) {
B1 = B2; b++; B2 = I[x+dirs[b]];
if ((B2 < Im)) { Scores[x] = 0; return; }
{ score -= A + B1; state = 0; break; }
}
// A ~ I0
if ((B2 <= Ip)) { Scores[x] = 0; return; }
B1 = B2; b++; B2 = I[x+dirs[b]];
if ((B2 > Ip)) { score -= A + B1; state = 3; break; };
if ((B2 < Im)) { score -= A + B1; state = 6; break; };
{ Scores[x] = 0; return; }
case 7:
if ((A > Ip)) { Scores[x] = 0; return; }
if ((A < Im)) { Scores[x] = 0; return; }
B1 = B2; b++; B2 = I[x+dirs[b]];
// A ~ I0
if ((B2 > Ip)) { score -= A + B1; state = 3; break; };
if ((B2 < Im)) { score -= A + B1; state = 6; break; };
{ Scores[x] = 0; return; } // A ~ I0, B2 ~ I0
case 6:
if ((A > Ip)) { Scores[x] = 0; return; }
if ((A < Im)) { Scores[x] = 0; return; }
B1 = B2; b++; B2 = I[x+dirs[b]];
// A ~ I0
if ((B2 < Im)) { score -= A + B1; state = 2; break; };
if ((B2 > Ip)) { score -= A + B1; state = 7; break; };
{ Scores[x] = 0; return; } // A ~ I0, B2 ~ I0
case 8:
if ((A > Ip)) {
if ((B2 < Im)) { Scores[x] = 0; return; }
B1 = B2; b++; B2 = I[x+dirs[b]];
if ((B2 < Im)) { Scores[x] = 0; return; }
{ score -= A + B1; state = 9; break; }
}
if ((A < Im)) {
B1 = B2; b++; B2 = I[x+dirs[b]];
if ((B2 > Ip)) { Scores[x] = 0; return; }
{ score -= A + B1; state = 1; break; }
}
{ Scores[x] = 0; return; }
case 9:
if ((A < Im)) {
if ((B2 > Ip)) { Scores[x] = 0; return; }
B1 = B2; b++; B2 = I[x+dirs[b]];
if ((B2 > Ip)) { Scores[x] = 0; return; }
{ score -= A + B1; state = 8; break; }
}
if ((A > Ip)) {
B1 = B2; b++; B2 = I[x+dirs[b]];
if ((B2 < Im)) { Scores[x] = 0; return; }
{ score -= A + B1; state = 0; break; }
}
{ Scores[x] = 0; return; }
default:
//"PB default";
break;
} // switch(state)
} // for(a...)
Scores[x] = (score + dirs_nb * I[x]);
};
var lev_table_t = (function () {
function lev_table_t(w, h, r) {
this.dirs = new Int32Array(1024);
this.dirs_count = precompute_directions(w, this.dirs, r)|0;
this.scores = new Int32Array(w*h);
this.radius = r|0;
}
return lev_table_t;
})();
return {
level_tables: [],
tau: 7,
init: function(width, height, radius, pyramid_levels) {
if (typeof pyramid_levels === "undefined") { pyramid_levels = 1; }
var i;
radius = Math.min(radius, 7);
radius = Math.max(radius, 3);
for(i = 0; i < pyramid_levels; ++i) {
this.level_tables[i] = new lev_table_t(width>>i, height>>i, radius);
}
},
detect: function(src, points, border) {
if (typeof border === "undefined") { border = 4; }
var t = this.level_tables[0];
var R = t.radius|0, Rm1 = (R-1)|0;
var dirs = t.dirs;
var dirs_count = t.dirs_count|0;
var opposite = dirs_count >> 1;
var img = src.data, w=src.cols|0, h=src.rows|0,hw=w>>1;
var scores = t.scores;
var x=0,y=0,row=0,rowx=0,ip=0,im=0,abs_score=0, score=0;
var tau = this.tau|0;
var number_of_points = 0, pt;
var sx = Math.max(R+1, border)|0;
var sy = Math.max(R+1, border)|0;
var ex = Math.min(w-R-2, w-border)|0;
var ey = Math.min(h-R-2, h-border)|0;
row = (sy*w+sx)|0;
for(y = sy; y < ey; ++y, row+=w) {
for(x = sx, rowx = row; x < ex; ++x, ++rowx) {
ip = img[rowx] + tau, im = img[rowx] - tau;
if (im<img[rowx+R] && img[rowx+R]<ip && im<img[rowx-R] && img[rowx-R]<ip) {
scores[rowx] = 0;
} else {
perform_one_point(img, rowx, scores, im, ip, dirs, opposite, dirs_count);
}
}
}
// local maxima
row = (sy*w+sx)|0;
for(y = sy; y < ey; ++y, row+=w) {
for(x = sx, rowx = row; x < ex; ++x, ++rowx) {
score = scores[rowx];
abs_score = Math.abs(score);
if(abs_score < 5) {
// if this pixel is 0, the next one will not be good enough. Skip it.
++x, ++rowx;
} else {
if(third_check(scores, rowx, w) >= 3 && is_local_maxima(scores, rowx, score, hw, R)) {
pt = points[number_of_points];
pt.x = x, pt.y = y, pt.score = abs_score;
++number_of_points;
x += Rm1, rowx += Rm1;
}
}
}
}
return number_of_points;
}
};
})();
global.yape = yape;
})(jsfeat);
/**
* @author Eugene Zatepyakin / http://inspirit.ru/
*
* Original implementation derived from OpenCV,
* @authors Ethan Rublee, Vincent Rabaud, Gary Bradski
*/
(function(global) {
"use strict";
//
var orb = (function() {
var bit_pattern_31_ = new Int32Array([
8,-3, 9,5/*mean (0), correlation (0)*/,
4,2, 7,-12/*mean (1.12461e-05), correlation (0.0437584)*/,
-11,9, -8,2/*mean (3.37382e-05), correlation (0.0617409)*/,
7,-12, 12,-13/*mean (5.62303e-05), correlation (0.0636977)*/,
2,-13, 2,12/*mean (0.000134953), correlation (0.085099)*/,
1,-7, 1,6/*mean (0.000528565), correlation (0.0857175)*/,
-2,-10, -2,-4/*mean (0.0188821), correlation (0.0985774)*/,
-13,-13, -11,-8/*mean (0.0363135), correlation (0.0899616)*/,
-13,-3, -12,-9/*mean (0.121806), correlation (0.099849)*/,
10,4, 11,9/*mean (0.122065), correlation (0.093285)*/,
-13,-8, -8,-9/*mean (0.162787), correlation (0.0942748)*/,
-11,7, -9,12/*mean (0.21561), correlation (0.0974438)*/,
7,7, 12,6/*mean (0.160583), correlation (0.130064)*/,
-4,-5, -3,0/*mean (0.228171), correlation (0.132998)*/,
-13,2, -12,-3/*mean (0.00997526), correlation (0.145926)*/,
-9,0, -7,5/*mean (0.198234), correlation (0.143636)*/,
12,-6, 12,-1/*mean (0.0676226), correlation (0.16689)*/,
-3,6, -2,12/*mean (0.166847), correlation (0.171682)*/,
-6,-13, -4,-8/*mean (0.101215), correlation (0.179716)*/,
11,-13, 12,-8/*mean (0.200641), correlation (0.192279)*/,
4,7, 5,1/*mean (0.205106), correlation (0.186848)*/,
5,-3, 10,-3/*mean (0.234908), correlation (0.192319)*/,
3,-7, 6,12/*mean (0.0709964), correlation (0.210872)*/,
-8,-7, -6,-2/*mean (0.0939834), correlation (0.212589)*/,
-2,11, -1,-10/*mean (0.127778), correlation (0.20866)*/,
-13,12, -8,10/*mean (0.14783), correlation (0.206356)*/,
-7,3, -5,-3/*mean (0.182141), correlation (0.198942)*/,
-4,2, -3,7/*mean (0.188237), correlation (0.21384)*/,
-10,-12, -6,11/*mean (0.14865), correlation (0.23571)*/,
5,-12, 6,-7/*mean (0.222312), correlation (0.23324)*/,
5,-6, 7,-1/*mean (0.229082), correlation (0.23389)*/,
1,0, 4,-5/*mean (0.241577), correlation (0.215286)*/,
9,11, 11,-13/*mean (0.00338507), correlation (0.251373)*/,
4,7, 4,12/*mean (0.131005), correlation (0.257622)*/,
2,-1, 4,4/*mean (0.152755), correlation (0.255205)*/,
-4,-12, -2,7/*mean (0.182771), correlation (0.244867)*/,
-8,-5, -7,-10/*mean (0.186898), correlation (0.23901)*/,
4,11, 9,12/*mean (0.226226), correlation (0.258255)*/,
0,-8, 1,-13/*mean (0.0897886), correlation (0.274827)*/,
-13,-2, -8,2/*mean (0.148774), correlation (0.28065)*/,
-3,-2, -2,3/*mean (0.153048), correlation (0.283063)*/,
-6,9, -4,-9/*mean (0.169523), correlation (0.278248)*/,
8,12, 10,7/*mean (0.225337), correlation (0.282851)*/,
0,9, 1,3/*mean (0.226687), correlation (0.278734)*/,
7,-5, 11,-10/*mean (0.00693882), correlation (0.305161)*/,
-13,-6, -11,0/*mean (0.0227283), correlation (0.300181)*/,
10,7, 12,1/*mean (0.125517), correlation (0.31089)*/,
-6,-3, -6,12/*mean (0.131748), correlation (0.312779)*/,
10,-9, 12,-4/*mean (0.144827), correlation (0.292797)*/,
-13,8, -8,-12/*mean (0.149202), correlation (0.308918)*/,
-13,0, -8,-4/*mean (0.160909), correlation (0.310013)*/,
3,3, 7,8/*mean (0.177755), correlation (0.309394)*/,
5,7, 10,-7/*mean (0.212337), correlation (0.310315)*/,
-1,7, 1,-12/*mean (0.214429), correlation (0.311933)*/,
3,-10, 5,6/*mean (0.235807), correlation (0.313104)*/,
2,-4, 3,-10/*mean (0.00494827), correlation (0.344948)*/,
-13,0, -13,5/*mean (0.0549145), correlation (0.344675)*/,
-13,-7, -12,12/*mean (0.103385), correlation (0.342715)*/,
-13,3, -11,8/*mean (0.134222), correlation (0.322922)*/,
-7,12, -4,7/*mean (0.153284), correlation (0.337061)*/,
6,-10, 12,8/*mean (0.154881), correlation (0.329257)*/,
-9,-1, -7,-6/*mean (0.200967), correlation (0.33312)*/,
-2,-5, 0,12/*mean (0.201518), correlation (0.340635)*/,
-12,5, -7,5/*mean (0.207805), correlation (0.335631)*/,
3,-10, 8,-13/*mean (0.224438), correlation (0.34504)*/,
-7,-7, -4,5/*mean (0.239361), correlation (0.338053)*/,
-3,-2, -1,-7/*mean (0.240744), correlation (0.344322)*/,
2,9, 5,-11/*mean (0.242949), correlation (0.34145)*/,
-11,-13, -5,-13/*mean (0.244028), correlation (0.336861)*/,
-1,6, 0,-1/*mean (0.247571), correlation (0.343684)*/,
5,-3, 5,2/*mean (0.000697256), correlation (0.357265)*/,
-4,-13, -4,12/*mean (0.00213675), correlation (0.373827)*/,
-9,-6, -9,6/*mean (0.0126856), correlation (0.373938)*/,
-12,-10, -8,-4/*mean (0.0152497), correlation (0.364237)*/,
10,2, 12,-3/*mean (0.0299933), correlation (0.345292)*/,
7,12, 12,12/*mean (0.0307242), correlation (0.366299)*/,
-7,-13, -6,5/*mean (0.0534975), correlation (0.368357)*/,
-4,9, -3,4/*mean (0.099865), correlation (0.372276)*/,
7,-1, 12,2/*mean (0.117083), correlation (0.364529)*/,
-7,6, -5,1/*mean (0.126125), correlation (0.369606)*/,
-13,11, -12,5/*mean (0.130364), correlation (0.358502)*/,
-3,7, -2,-6/*mean (0.131691), correlation (0.375531)*/,
7,-8, 12,-7/*mean (0.160166), correlation (0.379508)*/,
-13,-7, -11,-12/*mean (0.167848), correlation (0.353343)*/,
1,-3, 12,12/*mean (0.183378), correlation (0.371916)*/,
2,-6, 3,0/*mean (0.228711), correlation (0.371761)*/,
-4,3, -2,-13/*mean (0.247211), correlation (0.364063)*/,
-1,-13, 1,9/*mean (0.249325), correlation (0.378139)*/,
7,1, 8,-6/*mean (0.000652272), correlation (0.411682)*/,
1,-1, 3,12/*mean (0.00248538), correlation (0.392988)*/,
9,1, 12,6/*mean (0.0206815), correlation (0.386106)*/,
-1,-9, -1,3/*mean (0.0364485), correlation (0.410752)*/,
-13,-13, -10,5/*mean (0.0376068), correlation (0.398374)*/,
7,7, 10,12/*mean (0.0424202), correlation (0.405663)*/,
12,-5, 12,9/*mean (0.0942645), correlation (0.410422)*/,
6,3, 7,11/*mean (0.1074), correlation (0.413224)*/,
5,-13, 6,10/*mean (0.109256), correlation (0.408646)*/,
2,-12, 2,3/*mean (0.131691), correlation (0.416076)*/,
3,8, 4,-6/*mean (0.165081), correlation (0.417569)*/,
2,6, 12,-13/*mean (0.171874), correlation (0.408471)*/,
9,-12, 10,3/*mean (0.175146), correlation (0.41296)*/,
-8,4, -7,9/*mean (0.183682), correlation (0.402956)*/,
-11,12, -4,-6/*mean (0.184672), correlation (0.416125)*/,
1,12, 2,-8/*mean (0.191487), correlation (0.386696)*/,
6,-9, 7,-4/*mean (0.192668), correlation (0.394771)*/,
2,3, 3,-2/*mean (0.200157), correlation (0.408303)*/,
6,3, 11,0/*mean (0.204588), correlation (0.411762)*/,
3,-3, 8,-8/*mean (0.205904), correlation (0.416294)*/,
7,8, 9,3/*mean (0.213237), correlation (0.409306)*/,
-11,-5, -6,-4/*mean (0.243444), correlation (0.395069)*/,
-10,11, -5,10/*mean (0.247672), correlation (0.413392)*/,
-5,-8, -3,12/*mean (0.24774), correlation (0.411416)*/,
-10,5, -9,0/*mean (0.00213675), correlation (0.454003)*/,
8,-1, 12,-6/*mean (0.0293635), correlation (0.455368)*/,
4,-6, 6,-11/*mean (0.0404971), correlation (0.457393)*/,
-10,12, -8,7/*mean (0.0481107), correlation (0.448364)*/,
4,-2, 6,7/*mean (0.050641), correlation (0.455019)*/,
-2,0, -2,12/*mean (0.0525978), correlation (0.44338)*/,
-5,-8, -5,2/*mean (0.0629667), correlation (0.457096)*/,
7,-6, 10,12/*mean (0.0653846), correlation (0.445623)*/,
-9,-13, -8,-8/*mean (0.0858749), correlation (0.449789)*/,
-5,-13, -5,-2/*mean (0.122402), correlation (0.450201)*/,
8,-8, 9,-13/*mean (0.125416), correlation (0.453224)*/,
-9,-11, -9,0/*mean (0.130128), correlation (0.458724)*/,
1,-8, 1,-2/*mean (0.132467), correlation (0.440133)*/,
7,-4, 9,1/*mean (0.132692), correlation (0.454)*/,
-2,1, -1,-4/*mean (0.135695), correlation (0.455739)*/,
11,-6, 12,-11/*mean (0.142904), correlation (0.446114)*/,
-12,-9, -6,4/*mean (0.146165), correlation (0.451473)*/,
3,7, 7,12/*mean (0.147627), correlation (0.456643)*/,
5,5, 10,8/*mean (0.152901), correlation (0.455036)*/,
0,-4, 2,8/*mean (0.167083), correlation (0.459315)*/,
-9,12, -5,-13/*mean (0.173234), correlation (0.454706)*/,
0,7, 2,12/*mean (0.18312), correlation (0.433855)*/,
-1,2, 1,7/*mean (0.185504), correlation (0.443838)*/,
5,11, 7,-9/*mean (0.185706), correlation (0.451123)*/,
3,5, 6,-8/*mean (0.188968), correlation (0.455808)*/,
-13,-4, -8,9/*mean (0.191667), correlation (0.459128)*/,
-5,9, -3,-3/*mean (0.193196), correlation (0.458364)*/,
-4,-7, -3,-12/*mean (0.196536), correlation (0.455782)*/,
6,5, 8,0/*mean (0.1972), correlation (0.450481)*/,
-7,6, -6,12/*mean (0.199438), correlation (0.458156)*/,
-13,6, -5,-2/*mean (0.211224), correlation (0.449548)*/,
1,-10, 3,10/*mean (0.211718), correlation (0.440606)*/,
4,1, 8,-4/*mean (0.213034), correlation (0.443177)*/,
-2,-2, 2,-13/*mean (0.234334), correlation (0.455304)*/,
2,-12, 12,12/*mean (0.235684), correlation (0.443436)*/,
-2,-13, 0,-6/*mean (0.237674), correlation (0.452525)*/,
4,1, 9,3/*mean (0.23962), correlation (0.444824)*/,
-6,-10, -3,-5/*mean (0.248459), correlation (0.439621)*/,
-3,-13, -1,1/*mean (0.249505), correlation (0.456666)*/,
7,5, 12,-11/*mean (0.00119208), correlation (0.495466)*/,
4,-2, 5,-7/*mean (0.00372245), correlation (0.484214)*/,
-13,9, -9,-5/*mean (0.00741116), correlation (0.499854)*/,
7,1, 8,6/*mean (0.0208952), correlation (0.499773)*/,
7,-8, 7,6/*mean (0.0220085), correlation (0.501609)*/,
-7,-4, -7,1/*mean (0.0233806), correlation (0.496568)*/,
-8,11, -7,-8/*mean (0.0236505), correlation (0.489719)*/,
-13,6, -12,-8/*mean (0.0268781), correlation (0.503487)*/,
2,4, 3,9/*mean (0.0323324), correlation (0.501938)*/,
10,-5, 12,3/*mean (0.0399235), correlation (0.494029)*/,
-6,-5, -6,7/*mean (0.0420153), correlation (0.486579)*/,
8,-3, 9,-8/*mean (0.0548021), correlation (0.484237)*/,
2,-12, 2,8/*mean (0.0616622), correlation (0.496642)*/,
-11,-2, -10,3/*mean (0.0627755), correlation (0.498563)*/,
-12,-13, -7,-9/*mean (0.0829622), correlation (0.495491)*/,
-11,0, -10,-5/*mean (0.0843342), correlation (0.487146)*/,
5,-3, 11,8/*mean (0.0929937), correlation (0.502315)*/,
-2,-13, -1,12/*mean (0.113327), correlation (0.48941)*/,
-1,-8, 0,9/*mean (0.132119), correlation (0.467268)*/,
-13,-11, -12,-5/*mean (0.136269), correlation (0.498771)*/,
-10,-2, -10,11/*mean (0.142173), correlation (0.498714)*/,
-3,9, -2,-13/*mean (0.144141), correlation (0.491973)*/,
2,-3, 3,2/*mean (0.14892), correlation (0.500782)*/,
-9,-13, -4,0/*mean (0.150371), correlation (0.498211)*/,
-4,6, -3,-10/*mean (0.152159), correlation (0.495547)*/,
-4,12, -2,-7/*mean (0.156152), correlation (0.496925)*/,
-6,-11, -4,9/*mean (0.15749), correlation (0.499222)*/,
6,-3, 6,11/*mean (0.159211), correlation (0.503821)*/,
-13,11, -5,5/*mean (0.162427), correlation (0.501907)*/,
11,11, 12,6/*mean (0.16652), correlation (0.497632)*/,
7,-5, 12,-2/*mean (0.169141), correlation (0.484474)*/,
-1,12, 0,7/*mean (0.169456), correlation (0.495339)*/,
-4,-8, -3,-2/*mean (0.171457), correlation (0.487251)*/,
-7,1, -6,7/*mean (0.175), correlation (0.500024)*/,
-13,-12, -8,-13/*mean (0.175866), correlation (0.497523)*/,
-7,-2, -6,-8/*mean (0.178273), correlation (0.501854)*/,
-8,5, -6,-9/*mean (0.181107), correlation (0.494888)*/,
-5,-1, -4,5/*mean (0.190227), correlation (0.482557)*/,
-13,7, -8,10/*mean (0.196739), correlation (0.496503)*/,
1,5, 5,-13/*mean (0.19973), correlation (0.499759)*/,
1,0, 10,-13/*mean (0.204465), correlation (0.49873)*/,
9,12, 10,-1/*mean (0.209334), correlation (0.49063)*/,
5,-8, 10,-9/*mean (0.211134), correlation (0.503011)*/,
-1,11, 1,-13/*mean (0.212), correlation (0.499414)*/,
-9,-3, -6,2/*mean (0.212168), correlation (0.480739)*/,
-1,-10, 1,12/*mean (0.212731), correlation (0.502523)*/,
-13,1, -8,-10/*mean (0.21327), correlation (0.489786)*/,
8,-11, 10,-6/*mean (0.214159), correlation (0.488246)*/,
2,-13, 3,-6/*mean (0.216993), correlation (0.50287)*/,
7,-13, 12,-9/*mean (0.223639), correlation (0.470502)*/,
-10,-10, -5,-7/*mean (0.224089), correlation (0.500852)*/,
-10,-8, -8,-13/*mean (0.228666), correlation (0.502629)*/,
4,-6, 8,5/*mean (0.22906), correlation (0.498305)*/,
3,12, 8,-13/*mean (0.233378), correlation (0.503825)*/,
-4,2, -3,-3/*mean (0.234323), correlation (0.476692)*/,
5,-13, 10,-12/*mean (0.236392), correlation (0.475462)*/,
4,-13, 5,-1/*mean (0.236842), correlation (0.504132)*/,
-9,9, -4,3/*mean (0.236977), correlation (0.497739)*/,
0,3, 3,-9/*mean (0.24314), correlation (0.499398)*/,
-12,1, -6,1/*mean (0.243297), correlation (0.489447)*/,
3,2, 4,-8/*mean (0.00155196), correlation (0.553496)*/,
-10,-10, -10,9/*mean (0.00239541), correlation (0.54297)*/,
8,-13, 12,12/*mean (0.0034413), correlation (0.544361)*/,
-8,-12, -6,-5/*mean (0.003565), correlation (0.551225)*/,
2,2, 3,7/*mean (0.00835583), correlation (0.55285)*/,
10,6, 11,-8/*mean (0.00885065), correlation (0.540913)*/,
6,8, 8,-12/*mean (0.0101552), correlation (0.551085)*/,
-7,10, -6,5/*mean (0.0102227), correlation (0.533635)*/,
-3,-9, -3,9/*mean (0.0110211), correlation (0.543121)*/,
-1,-13, -1,5/*mean (0.0113473), correlation (0.550173)*/,
-3,-7, -3,4/*mean (0.0140913), correlation (0.554774)*/,
-8,-2, -8,3/*mean (0.017049), correlation (0.55461)*/,
4,2, 12,12/*mean (0.01778), correlation (0.546921)*/,
2,-5, 3,11/*mean (0.0224022), correlation (0.549667)*/,
6,-9, 11,-13/*mean (0.029161), correlation (0.546295)*/,
3,-1, 7,12/*mean (0.0303081), correlation (0.548599)*/,
11,-1, 12,4/*mean (0.0355151), correlation (0.523943)*/,
-3,0, -3,6/*mean (0.0417904), correlation (0.543395)*/,
4,-11, 4,12/*mean (0.0487292), correlation (0.542818)*/,
2,-4, 2,1/*mean (0.0575124), correlation (0.554888)*/,
-10,-6, -8,1/*mean (0.0594242), correlation (0.544026)*/,
-13,7, -11,1/*mean (0.0597391), correlation (0.550524)*/,
-13,12, -11,-13/*mean (0.0608974), correlation (0.55383)*/,
6,0, 11,-13/*mean (0.065126), correlation (0.552006)*/,
0,-1, 1,4/*mean (0.074224), correlation (0.546372)*/,
-13,3, -9,-2/*mean (0.0808592), correlation (0.554875)*/,
-9,8, -6,-3/*mean (0.0883378), correlation (0.551178)*/,
-13,-6, -8,-2/*mean (0.0901035), correlation (0.548446)*/,
5,-9, 8,10/*mean (0.0949843), correlation (0.554694)*/,
2,7, 3,-9/*mean (0.0994152), correlation (0.550979)*/,
-1,-6, -1,-1/*mean (0.10045), correlation (0.552714)*/,
9,5, 11,-2/*mean (0.100686), correlation (0.552594)*/,
11,-3, 12,-8/*mean (0.101091), correlation (0.532394)*/,
3,0, 3,5/*mean (0.101147), correlation (0.525576)*/,
-1,4, 0,10/*mean (0.105263), correlation (0.531498)*/,
3,-6, 4,5/*mean (0.110785), correlation (0.540491)*/,
-13,0, -10,5/*mean (0.112798), correlation (0.536582)*/,
5,8, 12,11/*mean (0.114181), correlation (0.555793)*/,
8,9, 9,-6/*mean (0.117431), correlation (0.553763)*/,
7,-4, 8,-12/*mean (0.118522), correlation (0.553452)*/,
-10,4, -10,9/*mean (0.12094), correlation (0.554785)*/,
7,3, 12,4/*mean (0.122582), correlation (0.555825)*/,
9,-7, 10,-2/*mean (0.124978), correlation (0.549846)*/,
7,0, 12,-2/*mean (0.127002), correlation (0.537452)*/,
-1,-6, 0,-11/*mean (0.127148), correlation (0.547401)*/
]);
var H = new jsfeat.matrix_t(3, 3, jsfeat.F32_t|jsfeat.C1_t);
var patch_img = new jsfeat.matrix_t(32, 32, jsfeat.U8_t|jsfeat.C1_t);
var rectify_patch = function(src, dst, angle, px, py, psize) {
var cosine = Math.cos(angle);
var sine = Math.sin(angle);
H.data[0] = cosine, H.data[1] = -sine, H.data[2] = (-cosine + sine ) * psize*0.5 + px,
H.data[3] = sine, H.data[4] = cosine, H.data[5] = (-sine - cosine) * psize*0.5 + py;
jsfeat.imgproc.warp_affine(src, dst, H, 128);
};
return {
describe: function(src, corners, count, descriptors) {
var DESCR_SIZE = 32; // bytes;
var i=0,b=0,px=0.0,py=0.0,angle=0.0;
var t0=0, t1=0, val=0;
var img = src.data, w = src.cols, h = src.rows;
var patch_d = patch_img.data;
var patch_off = 16*32 + 16; // center of patch
var patt=0;
if(!(descriptors.type&jsfeat.U8_t)) {
// relocate to U8 type
descriptors.type = jsfeat.U8_t;
descriptors.cols = DESCR_SIZE;
descriptors.rows = count;
descriptors.channel = 1;
descriptors.allocate();
} else {
descriptors.resize(DESCR_SIZE, count, 1);
}
var descr_d = descriptors.data;
var descr_off = 0;
for(i = 0; i < count; ++i) {
px = corners[i].x;
py = corners[i].y;
angle = corners[i].angle;
rectify_patch(src, patch_img, angle, px, py, 32);
// describe the patch
patt = 0;
for (b = 0; b < DESCR_SIZE; ++b) {
t0 = patch_d[patch_off + bit_pattern_31_[patt+1] * 32 + bit_pattern_31_[patt]]; patt += 2;
t1 = patch_d[patch_off + bit_pattern_31_[patt+1] * 32 + bit_pattern_31_[patt]]; patt += 2;
val = (t0 < t1)|0;
t0 = patch_d[patch_off + bit_pattern_31_[patt+1] * 32 + bit_pattern_31_[patt]]; patt += 2;
t1 = patch_d[patch_off + bit_pattern_31_[patt+1] * 32 + bit_pattern_31_[patt]]; patt += 2;
val |= (t0 < t1) << 1;
t0 = patch_d[patch_off + bit_pattern_31_[patt+1] * 32 + bit_pattern_31_[patt]]; patt += 2;
t1 = patch_d[patch_off + bit_pattern_31_[patt+1] * 32 + bit_pattern_31_[patt]]; patt += 2;
val |= (t0 < t1) << 2;
t0 = patch_d[patch_off + bit_pattern_31_[patt+1] * 32 + bit_pattern_31_[patt]]; patt += 2;
t1 = patch_d[patch_off + bit_pattern_31_[patt+1] * 32 + bit_pattern_31_[patt]]; patt += 2;
val |= (t0 < t1) << 3;
t0 = patch_d[patch_off + bit_pattern_31_[patt+1] * 32 + bit_pattern_31_[patt]]; patt += 2;
t1 = patch_d[patch_off + bit_pattern_31_[patt+1] * 32 + bit_pattern_31_[patt]]; patt += 2;
val |= (t0 < t1) << 4;
t0 = patch_d[patch_off + bit_pattern_31_[patt+1] * 32 + bit_pattern_31_[patt]]; patt += 2;
t1 = patch_d[patch_off + bit_pattern_31_[patt+1] * 32 + bit_pattern_31_[patt]]; patt += 2;
val |= (t0 < t1) << 5;
t0 = patch_d[patch_off + bit_pattern_31_[patt+1] * 32 + bit_pattern_31_[patt]]; patt += 2;
t1 = patch_d[patch_off + bit_pattern_31_[patt+1] * 32 + bit_pattern_31_[patt]]; patt += 2;
val |= (t0 < t1) << 6;
t0 = patch_d[patch_off + bit_pattern_31_[patt+1] * 32 + bit_pattern_31_[patt]]; patt += 2;
t1 = patch_d[patch_off + bit_pattern_31_[patt+1] * 32 + bit_pattern_31_[patt]]; patt += 2;
val |= (t0 < t1) << 7;
descr_d[descr_off+b] = val;
}
descr_off += DESCR_SIZE;
}
}
};
})();
global.orb = orb;
})(jsfeat);
/**
* @author Eugene Zatepyakin / http://inspirit.ru/
*
* this code is a rewrite from OpenCV's Lucas-Kanade optical flow implementation
*/
(function(global) {
"use strict";
//
var optical_flow_lk = (function() {
// short link to shar deriv
var scharr_deriv = jsfeat.imgproc.scharr_derivatives;
return {
track: function(prev_pyr, curr_pyr, prev_xy, curr_xy, count, win_size, max_iter, status, eps, min_eigen_threshold) {
if (typeof max_iter === "undefined") { max_iter = 30; }
if (typeof status === "undefined") { status = new Uint8Array(count); }
if (typeof eps === "undefined") { eps = 0.01; }
if (typeof min_eigen_threshold === "undefined") { min_eigen_threshold = 0.0001; }
var half_win = (win_size-1)*0.5;
var win_area = (win_size*win_size)|0;
var win_area2 = win_area << 1;
var prev_imgs = prev_pyr.data, next_imgs = curr_pyr.data;
var img_prev=prev_imgs[0].data,img_next=next_imgs[0].data;
var w0 = prev_imgs[0].cols, h0 = prev_imgs[0].rows,lw=0,lh=0;
var iwin_node = jsfeat.cache.get_buffer(win_area<<2);
var deriv_iwin_node = jsfeat.cache.get_buffer(win_area2<<2);
var deriv_lev_node = jsfeat.cache.get_buffer((h0*(w0<<1))<<2);
var deriv_m = new jsfeat.matrix_t(w0, h0, jsfeat.S32C2_t, deriv_lev_node.data);
var iwin_buf = iwin_node.i32;
var deriv_iwin = deriv_iwin_node.i32;
var deriv_lev = deriv_lev_node.i32;
var dstep=0,src=0,dsrc=0,iptr=0,diptr=0,jptr=0;
var lev_sc=0.0,prev_x=0.0,prev_y=0.0,next_x=0.0,next_y=0.0;
var prev_delta_x=0.0,prev_delta_y=0.0,delta_x=0.0,delta_y=0.0;
var iprev_x=0,iprev_y=0,inext_x=0,inext_y=0;
var i=0,j=0,x=0,y=0,level=0,ptid=0,iter=0;
var brd_tl=0,brd_r=0,brd_b=0;
var a=0.0,b=0.0,b1=0.0,b2=0.0;
// fixed point math
var W_BITS14 = 14;
var W_BITS4 = 14;
var W_BITS1m5 = W_BITS4 - 5;
var W_BITS1m51 = (1 << ((W_BITS1m5) - 1));
var W_BITS14_ = (1 << W_BITS14);
var W_BITS41 = (1 << ((W_BITS4) - 1));
var FLT_SCALE = 1.0/(1 << 20);
var iw00=0,iw01=0,iw10=0,iw11=0,ival=0,ixval=0,iyval=0;
var A11=0.0,A12=0.0,A22=0.0,D=0.0,min_eig=0.0;
var FLT_EPSILON = 0.00000011920929;
eps *= eps;
// reset status
for(; i < count; ++i) {
status[i] = 1;
}
var max_level = (prev_pyr.levels - 1)|0;
level = max_level;
for(; level >= 0; --level) {
lev_sc = (1.0/(1 << level));
lw = w0 >> level;
lh = h0 >> level;
dstep = lw << 1;
img_prev = prev_imgs[level].data;
img_next = next_imgs[level].data;
brd_r = (lw - win_size)|0;
brd_b = (lh - win_size)|0;
// calculate level derivatives
scharr_deriv(prev_imgs[level], deriv_m);
// iterate through points
for(ptid = 0; ptid < count; ++ptid) {
i = ptid << 1;
j = i + 1;
prev_x = prev_xy[i]*lev_sc;
prev_y = prev_xy[j]*lev_sc;
if( level == max_level ) {
next_x = prev_x;
next_y = prev_y;
} else {
next_x = curr_xy[i]*2.0;
next_y = curr_xy[j]*2.0;
}
curr_xy[i] = next_x;
curr_xy[j] = next_y;
prev_x -= half_win;
prev_y -= half_win;
iprev_x = prev_x|0;
iprev_y = prev_y|0;
// border check
x = (iprev_x <= brd_tl)|(iprev_x >= brd_r)|(iprev_y <= brd_tl)|(iprev_y >= brd_b);
if( x != 0 ) {
if( level == 0 ) {
status[ptid] = 0;
}
continue;
}
a = prev_x - iprev_x;
b = prev_y - iprev_y;
iw00 = (((1.0 - a)*(1.0 - b)*W_BITS14_) + 0.5)|0;
iw01 = ((a*(1.0 - b)*W_BITS14_) + 0.5)|0;
iw10 = (((1.0 - a)*b*W_BITS14_) + 0.5)|0;
iw11 = (W_BITS14_ - iw00 - iw01 - iw10);
A11 = 0.0, A12 = 0.0, A22 = 0.0;
// extract the patch from the first image, compute covariation matrix of derivatives
for( y = 0; y < win_size; ++y ) {
src = ( (y + iprev_y)*lw + iprev_x )|0;
dsrc = src << 1;
iptr = (y*win_size)|0;
diptr = iptr << 1;
for(x = 0 ; x < win_size; ++x, ++src, ++iptr, dsrc += 2) {
ival = ( (img_prev[src])*iw00 + (img_prev[src+1])*iw01 +
(img_prev[src+lw])*iw10 + (img_prev[src+lw+1])*iw11 );
ival = (((ival) + W_BITS1m51) >> (W_BITS1m5));
ixval = ( deriv_lev[dsrc]*iw00 + deriv_lev[dsrc+2]*iw01 +
deriv_lev[dsrc+dstep]*iw10 + deriv_lev[dsrc+dstep+2]*iw11 );
ixval = (((ixval) + W_BITS41) >> (W_BITS4));
iyval = ( deriv_lev[dsrc+1]*iw00 + deriv_lev[dsrc+3]*iw01 + deriv_lev[dsrc+dstep+1]*iw10 +
deriv_lev[dsrc+dstep+3]*iw11 );
iyval = (((iyval) + W_BITS41) >> (W_BITS4));
iwin_buf[iptr] = ival;
deriv_iwin[diptr++] = ixval;
deriv_iwin[diptr++] = iyval;
A11 += ixval*ixval;
A12 += ixval*iyval;
A22 += iyval*iyval;
}
}
A11 *= FLT_SCALE; A12 *= FLT_SCALE; A22 *= FLT_SCALE;
D = A11*A22 - A12*A12;
min_eig = (A22 + A11 - Math.sqrt((A11-A22)*(A11-A22) + 4.0*A12*A12)) / win_area2;
if( min_eig < min_eigen_threshold || D < FLT_EPSILON )
{
if( level == 0 ) {
status[ptid] = 0;
}
continue;
}
D = 1.0/D;
next_x -= half_win;
next_y -= half_win;
prev_delta_x = 0.0;
prev_delta_y = 0.0;
for( iter = 0; iter < max_iter; ++iter ) {
inext_x = next_x|0;
inext_y = next_y|0;
x = (inext_x <= brd_tl)|(inext_x >= brd_r)|(inext_y <= brd_tl)|(inext_y >= brd_b);
if( x != 0 ) {
if( level == 0 ) {
status[ptid] = 0;
}
break;
}
a = next_x - inext_x;
b = next_y - inext_y;
iw00 = (((1.0 - a)*(1.0 - b)*W_BITS14_) + 0.5)|0;
iw01 = ((a*(1.0 - b)*W_BITS14_) + 0.5)|0;
iw10 = (((1.0 - a)*b*W_BITS14_) + 0.5)|0;
iw11 = (W_BITS14_ - iw00 - iw01 - iw10);
b1 = 0.0, b2 = 0.0;
for( y = 0; y < win_size; ++y ) {
jptr = ( (y + inext_y)*lw + inext_x )|0;
iptr = (y*win_size)|0;
diptr = iptr << 1;
for( x = 0 ; x < win_size; ++x, ++jptr, ++iptr ) {
ival = ( (img_next[jptr])*iw00 + (img_next[jptr+1])*iw01 +
(img_next[jptr+lw])*iw10 + (img_next[jptr+lw+1])*iw11 );
ival = (((ival) + W_BITS1m51) >> (W_BITS1m5));
ival = (ival - iwin_buf[iptr]);
b1 += ival * deriv_iwin[diptr++];
b2 += ival * deriv_iwin[diptr++];
}
}
b1 *= FLT_SCALE;
b2 *= FLT_SCALE;
delta_x = ((A12*b2 - A22*b1) * D);
delta_y = ((A12*b1 - A11*b2) * D);
next_x += delta_x;
next_y += delta_y;
curr_xy[i] = next_x + half_win;
curr_xy[j] = next_y + half_win;
if( delta_x*delta_x + delta_y*delta_y <= eps ) {
break;
}
if( iter > 0 && Math.abs(delta_x + prev_delta_x) < 0.01 &&
Math.abs(delta_y + prev_delta_y) < 0.01 ) {
curr_xy[i] -= delta_x*0.5;
curr_xy[j] -= delta_y*0.5;
break;
}
prev_delta_x = delta_x;
prev_delta_y = delta_y;
}
} // points loop
} // levels loop
jsfeat.cache.put_buffer(iwin_node);
jsfeat.cache.put_buffer(deriv_iwin_node);
jsfeat.cache.put_buffer(deriv_lev_node);
}
};
})();
global.optical_flow_lk = optical_flow_lk;
})(jsfeat);
/**
* @author Eugene Zatepyakin / http://inspirit.ru/
*
* this code is a rewrite from https://github.com/mtschirs/js-objectdetect implementation
* @author Martin Tschirsich / http://www.tu-darmstadt.de/~m_t
*/
(function(global) {
"use strict";
//
var haar = (function() {
var _group_func = function(r1, r2) {
var distance = (r1.width * 0.25 + 0.5)|0;
return r2.x <= r1.x + distance &&
r2.x >= r1.x - distance &&
r2.y <= r1.y + distance &&
r2.y >= r1.y - distance &&
r2.width <= (r1.width * 1.5 + 0.5)|0 &&
(r2.width * 1.5 + 0.5)|0 >= r1.width;
};
return {
edges_density: 0.07,
detect_single_scale: function(int_sum, int_sqsum, int_tilted, int_canny_sum, width, height, scale, classifier) {
var win_w = (classifier.size[0] * scale)|0,
win_h = (classifier.size[1] * scale)|0,
step_x = (0.5 * scale + 1.5)|0,
step_y = step_x;
var i,j,k,x,y,ex=(width-win_w)|0,ey=(height-win_h)|0;
var w1=(width+1)|0,edge_dens,mean,variance,std;
var inv_area = 1.0 / (win_w * win_h);
var stages,stage,trees,tree,sn,tn,fn,found=true,stage_thresh,stage_sum,tree_sum,feature,features;
var fi_a,fi_b,fi_c,fi_d,fw,fh;
var ii_a=0,ii_b=win_w,ii_c=win_h*w1,ii_d=ii_c+win_w;
var edges_thresh = ((win_w*win_h) * 0xff * this.edges_density)|0;
// if too much gradient we also can skip
//var edges_thresh_high = ((win_w*win_h) * 0xff * 0.3)|0;
var rects = [];
for(y = 0; y < ey; y += step_y) {
ii_a = y * w1;
for(x = 0; x < ex; x += step_x, ii_a += step_x) {
mean = int_sum[ii_a]
- int_sum[ii_a+ii_b]
- int_sum[ii_a+ii_c]
+ int_sum[ii_a+ii_d];
// canny prune
if(int_canny_sum) {
edge_dens = (int_canny_sum[ii_a]
- int_canny_sum[ii_a+ii_b]
- int_canny_sum[ii_a+ii_c]
+ int_canny_sum[ii_a+ii_d]);
if(edge_dens < edges_thresh || mean < 20) {
x += step_x, ii_a += step_x;
continue;
}
}
mean *= inv_area;
variance = (int_sqsum[ii_a]
- int_sqsum[ii_a+ii_b]
- int_sqsum[ii_a+ii_c]
+ int_sqsum[ii_a+ii_d]) * inv_area - mean * mean;
std = variance > 0. ? Math.sqrt(variance) : 1;
stages = classifier.complexClassifiers;
sn = stages.length;
found = true;
for(i = 0; i < sn; ++i) {
stage = stages[i];
stage_thresh = stage.threshold;
trees = stage.simpleClassifiers;
tn = trees.length;
stage_sum = 0;
for(j = 0; j < tn; ++j) {
tree = trees[j];
tree_sum = 0;
features = tree.features;
fn = features.length;
if(tree.tilted === 1) {
for(k=0; k < fn; ++k) {
feature = features[k];
fi_a = ~~(x + feature[0] * scale) + ~~(y + feature[1] * scale) * w1;
fw = ~~(feature[2] * scale);
fh = ~~(feature[3] * scale);
fi_b = fw * w1;
fi_c = fh * w1;
tree_sum += (int_tilted[fi_a]
- int_tilted[fi_a + fw + fi_b]
- int_tilted[fi_a - fh + fi_c]
+ int_tilted[fi_a + fw - fh + fi_b + fi_c]) * feature[4];
}
} else {
for(k=0; k < fn; ++k) {
feature = features[k];
fi_a = ~~(x + feature[0] * scale) + ~~(y + feature[1] * scale) * w1;
fw = ~~(feature[2] * scale);
fh = ~~(feature[3] * scale);
fi_c = fh * w1;
tree_sum += (int_sum[fi_a]
- int_sum[fi_a+fw]
- int_sum[fi_a+fi_c]
+ int_sum[fi_a+fi_c+fw]) * feature[4];
}
}
stage_sum += (tree_sum * inv_area < tree.threshold * std) ? tree.left_val : tree.right_val;
}
if (stage_sum < stage_thresh) {
found = false;
break;
}
}
if(found) {
rects.push({"x" : x,
"y" : y,
"width" : win_w,
"height" : win_h,
"neighbor" : 1,
"confidence" : stage_sum});
x += step_x, ii_a += step_x;
}
}
}
return rects;
},
detect_multi_scale: function(int_sum, int_sqsum, int_tilted, int_canny_sum, width, height, classifier, scale_factor, scale_min) {
if (typeof scale_factor === "undefined") { scale_factor = 1.2; }
if (typeof scale_min === "undefined") { scale_min = 1.0; }
var win_w = classifier.size[0];
var win_h = classifier.size[1];
var rects = [];
while (scale_min * win_w < width && scale_min * win_h < height) {
rects = rects.concat(this.detect_single_scale(int_sum, int_sqsum, int_tilted, int_canny_sum, width, height, scale_min, classifier));
scale_min *= scale_factor;
}
return rects;
},
// OpenCV method to group detected rectangles
group_rectangles: function(rects, min_neighbors) {
if (typeof min_neighbors === "undefined") { min_neighbors = 1; }
var i, j, n = rects.length;
var node = [];
for (i = 0; i < n; ++i) {
node[i] = {"parent" : -1,
"element" : rects[i],
"rank" : 0};
}
for (i = 0; i < n; ++i) {
if (!node[i].element)
continue;
var root = i;
while (node[root].parent != -1)
root = node[root].parent;
for (j = 0; j < n; ++j) {
if( i != j && node[j].element && _group_func(node[i].element, node[j].element)) {
var root2 = j;
while (node[root2].parent != -1)
root2 = node[root2].parent;
if(root2 != root) {
if(node[root].rank > node[root2].rank)
node[root2].parent = root;
else {
node[root].parent = root2;
if (node[root].rank == node[root2].rank)
node[root2].rank++;
root = root2;
}
/* compress path from node2 to the root: */
var temp, node2 = j;
while (node[node2].parent != -1) {
temp = node2;
node2 = node[node2].parent;
node[temp].parent = root;
}
/* compress path from node to the root: */
node2 = i;
while (node[node2].parent != -1) {
temp = node2;
node2 = node[node2].parent;
node[temp].parent = root;
}
}
}
}
}
var idx_seq = [];
var class_idx = 0;
for(i = 0; i < n; i++) {
j = -1;
var node1 = i;
if(node[node1].element) {
while (node[node1].parent != -1)
node1 = node[node1].parent;
if(node[node1].rank >= 0)
node[node1].rank = ~class_idx++;
j = ~node[node1].rank;
}
idx_seq[i] = j;
}
var comps = [];
for (i = 0; i < class_idx+1; ++i) {
comps[i] = {"neighbors" : 0,
"x" : 0,
"y" : 0,
"width" : 0,
"height" : 0,
"confidence" : 0};
}
// count number of neighbors
for(i = 0; i < n; ++i) {
var r1 = rects[i];
var idx = idx_seq[i];
if (comps[idx].neighbors == 0)
comps[idx].confidence = r1.confidence;
++comps[idx].neighbors;
comps[idx].x += r1.x;
comps[idx].y += r1.y;
comps[idx].width += r1.width;
comps[idx].height += r1.height;
comps[idx].confidence = Math.max(comps[idx].confidence, r1.confidence);
}
var seq2 = [];
// calculate average bounding box
for(i = 0; i < class_idx; ++i) {
n = comps[i].neighbors;
if (n >= min_neighbors)
seq2.push({"x" : (comps[i].x * 2 + n) / (2 * n),
"y" : (comps[i].y * 2 + n) / (2 * n),
"width" : (comps[i].width * 2 + n) / (2 * n),
"height" : (comps[i].height * 2 + n) / (2 * n),
"neighbors" : comps[i].neighbors,
"confidence" : comps[i].confidence});
}
var result_seq = [];
n = seq2.length;
// filter out small face rectangles inside large face rectangles
for(i = 0; i < n; ++i) {
var r1 = seq2[i];
var flag = true;
for(j = 0; j < n; ++j) {
var r2 = seq2[j];
var distance = (r2.width * 0.25 + 0.5)|0;
if(i != j &&
r1.x >= r2.x - distance &&
r1.y >= r2.y - distance &&
r1.x + r1.width <= r2.x + r2.width + distance &&
r1.y + r1.height <= r2.y + r2.height + distance &&
(r2.neighbors > Math.max(3, r1.neighbors) || r1.neighbors < 3)) {
flag = false;
break;
}
}
if(flag)
result_seq.push(r1);
}
return result_seq;
}
};
})();
global.haar = haar;
})(jsfeat);
/**
* BBF: Brightness Binary Feature
*
* @author Eugene Zatepyakin / http://inspirit.ru/
*
* this code is a rewrite from https://github.com/liuliu/ccv implementation
* @author Liu Liu / http://liuliu.me/
*
* The original paper refers to: YEF∗ Real-Time Object Detection, Yotam Abramson and Bruno Steux
*/
(function(global) {
"use strict";
//
var bbf = (function() {
var _group_func = function(r1, r2) {
var distance = (r1.width * 0.25 + 0.5)|0;
return r2.x <= r1.x + distance &&
r2.x >= r1.x - distance &&
r2.y <= r1.y + distance &&
r2.y >= r1.y - distance &&
r2.width <= (r1.width * 1.5 + 0.5)|0 &&
(r2.width * 1.5 + 0.5)|0 >= r1.width;
};
var img_pyr = new jsfeat.pyramid_t(1);
return {
interval: 4,
scale: 1.1486,
next: 5,
scale_to: 1,
// make features local copy
// to avoid array allocation with each scale
// this is strange but array works faster than Int32 version???
prepare_cascade: function(cascade) {
var sn = cascade.stage_classifier.length;
for (var j = 0; j < sn; j++) {
var orig_feature = cascade.stage_classifier[j].feature;
var f_cnt = cascade.stage_classifier[j].count;
var feature = cascade.stage_classifier[j]._feature = new Array(f_cnt);
for (var k = 0; k < f_cnt; k++) {
feature[k] = {"size" : orig_feature[k].size,
"px" : new Array(orig_feature[k].size),
"pz" : new Array(orig_feature[k].size),
"nx" : new Array(orig_feature[k].size),
"nz" : new Array(orig_feature[k].size)};
}
}
},
build_pyramid: function(src, min_width, min_height, interval) {
if (typeof interval === "undefined") { interval = 4; }
var sw=src.cols,sh=src.rows;
var i=0,nw=0,nh=0;
var new_pyr=false;
var src0=src,src1=src;
var data_type = jsfeat.U8_t | jsfeat.C1_t;
this.interval = interval;
this.scale = Math.pow(2, 1 / (this.interval + 1));
this.next = (this.interval + 1)|0;
this.scale_to = (Math.log(Math.min(sw / min_width, sh / min_height)) / Math.log(this.scale))|0;
var pyr_l = ((this.scale_to + this.next * 2) * 4) | 0;
if(img_pyr.levels != pyr_l) {
img_pyr.levels = pyr_l;
img_pyr.data = new Array(pyr_l);
new_pyr = true;
img_pyr.data[0] = src; // first is src
}
for (i = 1; i <= this.interval; ++i) {
nw = (sw / Math.pow(this.scale, i))|0;
nh = (sh / Math.pow(this.scale, i))|0;
src0 = img_pyr.data[i<<2];
if(new_pyr || nw != src0.cols || nh != src0.rows) {
img_pyr.data[i<<2] = new jsfeat.matrix_t(nw, nh, data_type);
src0 = img_pyr.data[i<<2];
}
jsfeat.imgproc.resample(src, src0, nw, nh);
}
for (i = this.next; i < this.scale_to + this.next * 2; ++i) {
src1 = img_pyr.data[(i << 2) - (this.next << 2)];
src0 = img_pyr.data[i<<2];
nw = src1.cols >> 1;
nh = src1.rows >> 1;
if(new_pyr || nw != src0.cols || nh != src0.rows) {
img_pyr.data[i<<2] = new jsfeat.matrix_t(nw, nh, data_type);
src0 = img_pyr.data[i<<2];
}
jsfeat.imgproc.pyrdown(src1, src0);
}
for (i = this.next * 2; i < this.scale_to + this.next * 2; ++i) {
src1 = img_pyr.data[(i << 2) - (this.next << 2)];
nw = src1.cols >> 1;
nh = src1.rows >> 1;
src0 = img_pyr.data[(i<<2)+1];
if(new_pyr || nw != src0.cols || nh != src0.rows) {
img_pyr.data[(i<<2)+1] = new jsfeat.matrix_t(nw, nh, data_type);
src0 = img_pyr.data[(i<<2)+1];
}
jsfeat.imgproc.pyrdown(src1, src0, 1, 0);
//
src0 = img_pyr.data[(i<<2)+2];
if(new_pyr || nw != src0.cols || nh != src0.rows) {
img_pyr.data[(i<<2)+2] = new jsfeat.matrix_t(nw, nh, data_type);
src0 = img_pyr.data[(i<<2)+2];
}
jsfeat.imgproc.pyrdown(src1, src0, 0, 1);
//
src0 = img_pyr.data[(i<<2)+3];
if(new_pyr || nw != src0.cols || nh != src0.rows) {
img_pyr.data[(i<<2)+3] = new jsfeat.matrix_t(nw, nh, data_type);
src0 = img_pyr.data[(i<<2)+3];
}
jsfeat.imgproc.pyrdown(src1, src0, 1, 1);
}
return img_pyr;
},
detect: function(pyramid, cascade) {
var interval = this.interval;
var scale = this.scale;
var next = this.next;
var scale_upto = this.scale_to;
var i=0,j=0,k=0,n=0,x=0,y=0,q=0,sn=0,f_cnt=0,q_cnt=0,p=0,pmin=0,nmax=0,f=0,i4=0,qw=0,qh=0;
var sum=0.0, alpha, feature, orig_feature, feature_k, feature_o, flag = true, shortcut=true;
var scale_x = 1.0, scale_y = 1.0;
var dx = [0, 1, 0, 1];
var dy = [0, 0, 1, 1];
var seq = [];
var pyr=pyramid.data, bpp = 1, bpp2 = 2, bpp4 = 4;
var u8 = [], u8o = [0,0,0];
var step = [0,0,0];
var paddings = [0,0,0];
for (i = 0; i < scale_upto; i++) {
i4 = (i<<2);
qw = pyr[i4 + (next << 3)].cols - (cascade.width >> 2);
qh = pyr[i4 + (next << 3)].rows - (cascade.height >> 2);
step[0] = pyr[i4].cols * bpp;
step[1] = pyr[i4 + (next << 2)].cols * bpp;
step[2] = pyr[i4 + (next << 3)].cols * bpp;
paddings[0] = (pyr[i4].cols * bpp4) - (qw * bpp4);
paddings[1] = (pyr[i4 + (next << 2)].cols * bpp2) - (qw * bpp2);
paddings[2] = (pyr[i4 + (next << 3)].cols * bpp) - (qw * bpp);
sn = cascade.stage_classifier.length;
for (j = 0; j < sn; j++) {
orig_feature = cascade.stage_classifier[j].feature;
feature = cascade.stage_classifier[j]._feature;
f_cnt = cascade.stage_classifier[j].count;
for (k = 0; k < f_cnt; k++) {
feature_k = feature[k];
feature_o = orig_feature[k];
q_cnt = feature_o.size|0;
for (q = 0; q < q_cnt; q++) {
feature_k.px[q] = (feature_o.px[q] * bpp) + feature_o.py[q] * step[feature_o.pz[q]];
feature_k.pz[q] = feature_o.pz[q];
feature_k.nx[q] = (feature_o.nx[q] * bpp) + feature_o.ny[q] * step[feature_o.nz[q]];
feature_k.nz[q] = feature_o.nz[q];
}
}
}
u8[0] = pyr[i4].data; u8[1] = pyr[i4 + (next<<2)].data;
for (q = 0; q < 4; q++) {
u8[2] = pyr[i4 + (next<<3) + q].data;
u8o[0] = (dx[q]*bpp2) + dy[q] * (pyr[i4].cols*bpp2);
u8o[1] = (dx[q]*bpp) + dy[q] * (pyr[i4 + (next<<2)].cols*bpp);
u8o[2] = 0;
for (y = 0; y < qh; y++) {
for (x = 0; x < qw; x++) {
sum = 0;
flag = true;
sn = cascade.stage_classifier.length;
for (j = 0; j < sn; j++) {
sum = 0;
alpha = cascade.stage_classifier[j].alpha;
feature = cascade.stage_classifier[j]._feature;
f_cnt = cascade.stage_classifier[j].count;
for (k = 0; k < f_cnt; k++) {
feature_k = feature[k];
pmin = u8[feature_k.pz[0]][u8o[feature_k.pz[0]] + feature_k.px[0]];
nmax = u8[feature_k.nz[0]][u8o[feature_k.nz[0]] + feature_k.nx[0]];
if (pmin <= nmax) {
sum += alpha[k << 1];
} else {
shortcut = true;
q_cnt = feature_k.size;
for (f = 1; f < q_cnt; f++) {
if (feature_k.pz[f] >= 0) {
p = u8[feature_k.pz[f]][u8o[feature_k.pz[f]] + feature_k.px[f]];
if (p < pmin) {
if (p <= nmax) {
shortcut = false;
break;
}
pmin = p;
}
}
if (feature_k.nz[f] >= 0) {
n = u8[feature_k.nz[f]][u8o[feature_k.nz[f]] + feature_k.nx[f]];
if (n > nmax) {
if (pmin <= n) {
shortcut = false;
break;
}
nmax = n;
}
}
}
sum += (shortcut) ? alpha[(k << 1) + 1] : alpha[k << 1];
}
}
if (sum < cascade.stage_classifier[j].threshold) {
flag = false;
break;
}
}
if (flag) {
seq.push({"x" : (x * 4 + dx[q] * 2) * scale_x,
"y" : (y * 4 + dy[q] * 2) * scale_y,
"width" : cascade.width * scale_x,
"height" : cascade.height * scale_y,
"neighbor" : 1,
"confidence" : sum});
++x;
u8o[0] += bpp4;
u8o[1] += bpp2;
u8o[2] += bpp;
}
u8o[0] += bpp4;
u8o[1] += bpp2;
u8o[2] += bpp;
}
u8o[0] += paddings[0];
u8o[1] += paddings[1];
u8o[2] += paddings[2];
}
}
scale_x *= scale;
scale_y *= scale;
}
return seq;
},
// OpenCV method to group detected rectangles
group_rectangles: function(rects, min_neighbors) {
if (typeof min_neighbors === "undefined") { min_neighbors = 1; }
var i, j, n = rects.length;
var node = [];
for (i = 0; i < n; ++i) {
node[i] = {"parent" : -1,
"element" : rects[i],
"rank" : 0};
}
for (i = 0; i < n; ++i) {
if (!node[i].element)
continue;
var root = i;
while (node[root].parent != -1)
root = node[root].parent;
for (j = 0; j < n; ++j) {
if( i != j && node[j].element && _group_func(node[i].element, node[j].element)) {
var root2 = j;
while (node[root2].parent != -1)
root2 = node[root2].parent;
if(root2 != root) {
if(node[root].rank > node[root2].rank)
node[root2].parent = root;
else {
node[root].parent = root2;
if (node[root].rank == node[root2].rank)
node[root2].rank++;
root = root2;
}
/* compress path from node2 to the root: */
var temp, node2 = j;
while (node[node2].parent != -1) {
temp = node2;
node2 = node[node2].parent;
node[temp].parent = root;
}
/* compress path from node to the root: */
node2 = i;
while (node[node2].parent != -1) {
temp = node2;
node2 = node[node2].parent;
node[temp].parent = root;
}
}
}
}
}
var idx_seq = [];
var class_idx = 0;
for(i = 0; i < n; i++) {
j = -1;
var node1 = i;
if(node[node1].element) {
while (node[node1].parent != -1)
node1 = node[node1].parent;
if(node[node1].rank >= 0)
node[node1].rank = ~class_idx++;
j = ~node[node1].rank;
}
idx_seq[i] = j;
}
var comps = [];
for (i = 0; i < class_idx+1; ++i) {
comps[i] = {"neighbors" : 0,
"x" : 0,
"y" : 0,
"width" : 0,
"height" : 0,
"confidence" : 0};
}
// count number of neighbors
for(i = 0; i < n; ++i) {
var r1 = rects[i];
var idx = idx_seq[i];
if (comps[idx].neighbors == 0)
comps[idx].confidence = r1.confidence;
++comps[idx].neighbors;
comps[idx].x += r1.x;
comps[idx].y += r1.y;
comps[idx].width += r1.width;
comps[idx].height += r1.height;
comps[idx].confidence = Math.max(comps[idx].confidence, r1.confidence);
}
var seq2 = [];
// calculate average bounding box
for(i = 0; i < class_idx; ++i) {
n = comps[i].neighbors;
if (n >= min_neighbors)
seq2.push({"x" : (comps[i].x * 2 + n) / (2 * n),
"y" : (comps[i].y * 2 + n) / (2 * n),
"width" : (comps[i].width * 2 + n) / (2 * n),
"height" : (comps[i].height * 2 + n) / (2 * n),
"neighbors" : comps[i].neighbors,
"confidence" : comps[i].confidence});
}
var result_seq = [];
n = seq2.length;
// filter out small face rectangles inside large face rectangles
for(i = 0; i < n; ++i) {
var r1 = seq2[i];
var flag = true;
for(j = 0; j < n; ++j) {
var r2 = seq2[j];
var distance = (r2.width * 0.25 + 0.5)|0;
if(i != j &&
r1.x >= r2.x - distance &&
r1.y >= r2.y - distance &&
r1.x + r1.width <= r2.x + r2.width + distance &&
r1.y + r1.height <= r2.y + r2.height + distance &&
(r2.neighbors > Math.max(3, r1.neighbors) || r1.neighbors < 3)) {
flag = false;
break;
}
}
if(flag)
result_seq.push(r1);
}
return result_seq;
}
};
})();
global.bbf = bbf;
})(jsfeat);
/**
* @author Eugene Zatepyakin / http://inspirit.ru/
*/
(function(lib) {
"use strict";
{
// in commonjs, or when AMD wrapping has been applied, define its namespaces as exports
module.exports = lib;
}
})(jsfeat);
});
var findFaceWorker = function(e) {
var window = self;
var jsfeat=jsfeat||{REVISION:"ALPHA"};(function(r){var o=1.192092896e-7;var l=1e-37;var m=256,i=512,h=1024,x=2048,w=4096;var A=1,n=2,b=3,p=4;var z=new Int32Array([-1,1,4,-1,4,-1,-1,-1,8,-1,-1,-1,-1,-1,-1,-1,8]);var y=(function(){return function(B){return(B&65280)}})();var k=(function(){return function(B){return(B&255)}})();var c=(function(){return function(B){return z[(B&65280)>>8]}})();var a=0;var f=1;var e=2;var u=3;var d=1;var s=1;var g=2;var v=(function(){function B(D,C){this.size=((D+7)|0)&-8;if(typeof C==="undefined"){this.buffer=new ArrayBuffer(this.size);}else{this.buffer=C;this.size=C.length;}this.u8=new Uint8Array(this.buffer);this.i32=new Int32Array(this.buffer);this.f32=new Float32Array(this.buffer);this.f64=new Float64Array(this.buffer);}return B})();var q=(function(){function B(F,D,E,C){this.type=y(E)|0;this.channel=k(E)|0;this.cols=F|0;this.rows=D|0;if(typeof C==="undefined"){this.allocate();}else{this.buffer=C;this.data=this.type&m?this.buffer.u8:(this.type&i?this.buffer.i32:(this.type&h?this.buffer.f32:this.buffer.f64));}}B.prototype.allocate=function(){delete this.data;delete this.buffer;this.buffer=new v((this.cols*c(this.type)*this.channel)*this.rows);this.data=this.type&m?this.buffer.u8:(this.type&i?this.buffer.i32:(this.type&h?this.buffer.f32:this.buffer.f64));};B.prototype.copy_to=function(D){var C=D.data,G=this.data;var E=0,F=(this.cols*this.rows*this.channel)|0;for(;E<F-4;E+=4){C[E]=G[E];C[E+1]=G[E+1];C[E+2]=G[E+2];C[E+3]=G[E+3];}for(;E<F;++E){C[E]=G[E];}};B.prototype.resize=function(F,D,C){if(typeof C==="undefined"){C=this.channel;}var E=(F*c(this.type)*C)*D;if(E>this.buffer.size){this.cols=F;this.rows=D;this.channel=C;this.allocate();}else{this.cols=F;this.rows=D;this.channel=C;}};return B})();var t=(function(){function B(C){this.levels=C|0;this.data=new Array(C);this.pyrdown=jsfeat.imgproc.pyrdown;}B.prototype.allocate=function(C,E,F){var D=this.levels;while(--D>=0){this.data[D]=new q(C>>D,E>>D,F);}};B.prototype.build=function(F,E){if(typeof E==="undefined"){E=true;}var H=2,D=F,C=this.data[0];if(!E){var G=F.cols*F.rows;while(--G>=0){C.data[G]=F.data[G];}}C=this.data[1];this.pyrdown(D,C);for(;H<this.levels;++H){D=C;C=this.data[H];this.pyrdown(D,C);}};return B})();var j=(function(){function B(C,G,E,F,D){if(typeof C==="undefined"){C=0;}if(typeof G==="undefined"){G=0;}if(typeof E==="undefined"){E=0;}if(typeof F==="undefined"){F=0;}if(typeof D==="undefined"){D=-1;}this.x=C;this.y=G;this.score=E;this.level=F;this.angle=D;}return B})();r.U8_t=m;r.S32_t=i;r.F32_t=h;r.S64_t=x;r.F64_t=w;r.C1_t=A;r.C2_t=n;r.C3_t=b;r.C4_t=p;r.U8C1_t=m|A;r.U8C3_t=m|b;r.U8C4_t=m|p;r.F32C1_t=h|A;r.F32C2_t=h|n;r.S32C1_t=i|A;r.S32C2_t=i|n;r.EPSILON=o;r.FLT_MIN=l;r.COLOR_RGBA2GRAY=a;r.COLOR_RGB2GRAY=f;r.COLOR_BGRA2GRAY=e;r.COLOR_BGR2GRAY=u;r.BOX_BLUR_NOSCALE=d;r.SVD_U_T=s;r.SVD_V_T=g;r.get_data_type=y;r.get_channel=k;r.get_data_type_size=c;r.data_t=v;r.matrix_t=q;r.pyramid_t=t;r.keypoint_t=j;})(jsfeat);(function(b){var a=(function(){var f=(function(){function g(h){this.next=null;this.data=new jsfeat.data_t(h);this.size=this.data.size;this.buffer=this.data.buffer;this.u8=this.data.u8;this.i32=this.data.i32;this.f32=this.data.f32;this.f64=this.data.f64;}g.prototype.resize=function(h){delete this.data;this.data=new jsfeat.data_t(h);this.size=this.data.size;this.buffer=this.data.buffer;this.u8=this.data.u8;this.i32=this.data.i32;this.f32=this.data.f32;this.f64=this.data.f64;};return g})();var e,c;var d=0;return{allocate:function(g,k){e=c=new f(k);for(var h=0;h<g;++h){var j=new f(k);c=c.next=j;d++;}},get_buffer:function(g){var h=e;e=e.next;d--;if(g>h.size){h.resize(g);}return h},put_buffer:function(g){c=c.next=g;d++;}}})();b.cache=a;a.allocate(30,640*4);})(jsfeat);(function(b){var a=(function(){var c=new Int32Array(48*2);return{get_gaussian_kernel:function(p,m,e,l){var f=0,j=0,o=0,n=0,d=0;var g=0;var h=jsfeat.cache.get_buffer(p<<2);var k=h.f32;if((p&1)==1&&p<=7&&m<=0){switch(p>>1){case 0:k[0]=1;g=1;break;case 1:k[0]=0.25,k[1]=0.5,k[2]=0.25;g=0.25+0.5+0.25;break;case 2:k[0]=0.0625,k[1]=0.25,k[2]=0.375,k[3]=0.25,k[4]=0.0625;g=0.0625
jsfeat.haar.frontalface = 'FRONTALFACE_PLACEHOLDER';
var imageData = e.data.imageData,
w = e.data.w,
h = e.data.h,
videoWidth = e.data.videoWidth,
params = e.data.params;
var img_u8 = new jsfeat.matrix_t(w, h, jsfeat.U8_t | jsfeat.C1_t),
edg = new jsfeat.matrix_t(w, h, jsfeat.U8_t | jsfeat.C1_t),
ii_sum = new Int32Array((w+1)*(h+1)),
ii_sqsum = new Int32Array((w+1)*(h+1)),
ii_tilted = new Int32Array((w+1)*(h+1)),
ii_canny = new Int32Array((w+1)*(h+1));
var classifier = jsfeat.haar.frontalface;
jsfeat.imgproc.grayscale(imageData.data, w, h, img_u8);
// possible params
if (params.equalizeHistogram) {
jsfeat.imgproc.equalize_histogram(img_u8, img_u8);
}
//jsfeat.imgproc.gaussian_blur(img_u8, img_u8, 3);
jsfeat.imgproc.compute_integral_image(img_u8, ii_sum, ii_sqsum, classifier.tilted ? ii_tilted : null);
if(params.useCanny) {
jsfeat.imgproc.canny(img_u8, edg, 10, 50);
jsfeat.imgproc.compute_integral_image(edg, ii_canny, null, null);
}
jsfeat.haar.edgesDensity = params.edgesDensity;
var rects = jsfeat.haar.detect_multi_scale(ii_sum, ii_sqsum, ii_tilted, params.useCanny? ii_canny : null, img_u8.cols, img_u8.rows, classifier, params.scaleFactor, params.minScale);
rects = jsfeat.haar.group_rectangles(rects, params.min_neighbors);
for (var i = rects.length-1;i >= 0;i--) {
if (rects[i].confidence < params.confidenceThreshold) {
rects.splice(i,1);
}
}
var rl = rects.length;
if (rl == 0) {
self.postMessage({
faces: []
});
} else {
var best = rects[0];
for (var i = 1;i < rl;i++) {
if (rects[i].neighbors > best.neighbors) {
best = rects[i];
} else if (rects[i].neighbors == best.neighbors) {
// if (rects[i].width > best.width) best = rects[i]; // use biggest rect
if (rects[i].confidence > best.confidence) best = rects[i]; // use most confident rect
}
}
var sc = videoWidth / img_u8.cols;
best.x = (best.x*sc)|0;
best.y = (best.y*sc)|0;
best.width = (best.width*sc)|0;
best.height = (best.height*sc)|0;
self.postMessage({
faces: [best]
});
}
};
// import { drawDetection, drawFacialPoints, drawBoundingBox } from './utils/debugging.js';
/**
* this cascade is derived from https://github.com/mtschirs/js-objectdetect implementation
* @author Martin Tschirsich / http://www.tu-darmstadt.de/~m_t
*/
jsfeat_1.haar.frontalface = {complexClassifiers:[{simpleClassifiers:[{features:[[3,7,14,4,-1.],[3,9,14,2,2.]],threshold:4.0142e-003,right_val:0.83781,left_val:0.033794},{features:[[1,2,18,4,-1.],[7,2,6,4,3.]],threshold:0.015151,right_val:0.74888,left_val:0.15141},{features:[[1,7,15,9,-1.],[1,10,15,3,3.]],threshold:4.211e-003,right_val:0.63748,left_val:0.090049}],threshold:0.82269},{simpleClassifiers:[{features:[[5,6,2,6,-1.],[5,9,2,3,2.]],threshold:1.6227e-003,right_val:0.71109,left_val:0.069309},{features:[[7,5,6,3,-1.],[9,5,2,3,3.]],threshold:2.2907e-003,right_val:0.66687,left_val:0.17958},{features:[[4,0,12,9,-1.],[4,3,12,3,3.]],threshold:5.0026e-003,right_val:0.6554,left_val:0.16937},{features:[[6,9,10,8,-1.],[6,13,10,4,2.]],threshold:7.966e-003,right_val:0.091415,left_val:0.58663},{features:[[3,6,14,8,-1.],[3,10,14,4,2.]],threshold:-3.5227e-003,right_val:0.60319,left_val:0.14132},{features:[[14,1,6,10,-1.],[14,1,3,10,2.]],threshold:0.036668,right_val:0.79203,left_val:0.36757},{features:[[7,8,5,12,-1.],[7,12,5,4,3.]],threshold:9.3361e-003,right_val:0.20885,left_val:0.61614},{features:[[1,1,18,3,-1.],[7,1,6,3,3.]],threshold:8.6961e-003,right_val:0.63603,left_val:0.28362},{features:[[1,8,17,2,-1.],[1,9,17,1,2.]],threshold:1.1489e-003,right_val:0.58007,left_val:0.22236},{features:[[16,6,4,2,-1.],[16,7,4,1,2.]],threshold:-2.1485e-003,right_val:0.57871,left_val:0.24065},{features:[[5,17,2,2,-1.],[5,18,2,1,2.]],threshold:2.1219e-003,right_val:0.13622,left_val:0.55597},{features:[[14,2,6,12,-1.],[14,2,3,12,2.]],threshold:-0.093949,right_val:0.47177,left_val:0.85027},{features:[[4,0,4,12,-1.],[4,0,2,6,2.],[6,6,2,6,2.]],threshold:1.3778e-003,right_val:0.28345,left_val:0.59937},{features:[[2,11,18,8,-1.],[8,11,6,8,3.]],threshold:0.073063,right_val:0.706,left_val:0.43419},{features:[[5,7,10,2,-1.],[5,8,10,1,2.]],threshold:3.6767e-004,right_val:0.60516,left_val:0.30279},{features:[[15,11,5,3,-1.],[15,12,5,1,3.]],threshold:-6.048e-003,right_val:0.56753,left_val:0.17984}],threshold:6.9566},{simpleClassifiers:[{features:[[5,3,10,9,-1.],[5,6,10,3,3.]],threshold:-0.016511,right_val:0.14249,left_val:0.66442},{features:[[9,4,2,14,-1.],[9,11,2,7,2.]],threshold:2.7052e-003,right_val:0.12885,left_val:0.63254},{features:[[3,5,4,12,-1.],[3,9,4,4,3.]],threshold:2.807e-003,right_val:0.61932,left_val:0.12403},{features:[[4,5,12,5,-1.],[8,5,4,5,3.]],threshold:-1.5402e-003,right_val:0.567,left_val:0.14321},{features:[[5,6,10,8,-1.],[5,10,10,4,2.]],threshold:-5.6386e-004,right_val:0.59052,left_val:0.16574},{features:[[8,0,6,9,-1.],[8,3,6,3,3.]],threshold:1.9254e-003,right_val:0.57388,left_val:0.26955},{features:[[9,12,1,8,-1.],[9,16,1,4,2.]],threshold:-5.0215e-003,right_val:0.57828,left_val:0.18935},{features:[[0,7,20,6,-1.],[0,9,20,2,3.]],threshold:2.6365e-003,right_val:0.56954,left_val:0.23093},{features:[[7,0,6,17,-1.],[9,0,2,17,3.]],threshold:-1.5128e-003,right_val:0.59566,left_val:0.27596},{features:[[9,0,6,4,-1.],[11,0,2,4,3.]],threshold:-0.010157,right_val:0.5522,left_val:0.17325},{features:[[5,1,6,4,-1.],[7,1,2,4,3.]],threshold:-0.011954,right_val:0.5559,left_val:0.13394},{features:[[12,1,6,16,-1.],[14,1,2,16,3.]],threshold:4.8859e-003,right_val:0.61888,left_val:0.36287},{features:[[0,5,18,8,-1.],[0,5,9,4,2.],[9,9,9,4,2.]],threshold:-0.080133,right_val:0.54759,left_val:0.091211},{features:[[8,15,10,4,-1.],[13,15,5,2,2.],[8,17,5,2,2.]],threshold:1.0643e-003,right_val:0.57114,left_val:0.37151},{features:[[3,1,4,8,-1.],[3,1,2,4,2.],[5,5,2,4,2.]],threshold:-1.3419e-003,right_val:0.33181,left_val:0.59533},{features:[[3,6,14,10,-1.],[10,6,7,5,2.],[3,11,7,5,2.]],threshold:-0.054601,right_val:0.56028,left_val:0.18441},{features:[[2,1,6,16,-1.],[4,1,2,16,3.]],threshold:2.9072e-003,right_val:0.61317,left_val:0.35942},{features:[[0,18,20,2,-1.],[0,19,20,1,2.]],threshold:7.4719e-004,right_val:0.34596,left_val:0.59944},{features:[[8,13,4,3,-1.],[8,14,4,1,3.]],threshold:4.3014e-003,right_val:0.69908,left_val:0.41727},{features:[[9,14,2,3,-1.],[9,15,2,1,3.]],threshold:4.5018e-003,right_val:0.78015,left_val:0.45097},{features:[[0,12,9,6,-1.],[0,14,9,2,3
var faceDetection = function(pdmModel, params) {
// processes an image, detects a face and returns the initial face parameters for clmtrackr
// calls a callback function when it's done
// optionally uses web workers
if (params === undefined) params = {};
if (params.workSize === undefined) params.workSize = 200;
if (params.minScale === undefined) params.minScale = 2;
if (params.scaleFactor === undefined) params.scaleFactor = 1.15;
if (params.useCanny === undefined) params.useCanny = false;
if (params.edgesDensity === undefined) params.edgesDensity = 0.13;
if (params.equalizeHistogram === undefined) params.equalizeHistogram = false;
if (params.min_neighbors === undefined) params.min_neighbors = 2;
if (params.confidenceThreshold === undefined) params.confidenceThreshold = 106.1;
if (params.useWebWorkers === undefined) params.useWebWorkers = true;
// disable web workers if not exists
if (!window.Worker) params.useWebWorkers = false;
var msxmin, msymin, msymax;
var msmodelheight;
var element;
var model = pdmModel;
var mosseFilter = mosse.mosseFilter;
var left_eye_filter = mosse.filters.left_eye_filter;
var right_eye_filter = mosse.filters.right_eye_filter;
var nose_filter = mosse.filters.nose_filter;
var mossef_lefteye, mossef_righteye, mossef_nose;
var right_eye_position = [0.0,0.0];
var left_eye_position = [0.0,0.0];
var nose_position = [0.0,0.0];
if (model.hints && mosseFilter && left_eye_filter && right_eye_filter && nose_filter) {
mossef_lefteye = new mosseFilter();
mossef_lefteye.load(left_eye_filter);
mossef_righteye = new mosseFilter();
mossef_righteye.load(right_eye_filter);
mossef_nose = new mosseFilter();
mossef_nose.load(nose_filter);
} else {
console.log('MOSSE filters not found, using rough approximation for initialization.');
}
// load mean shape
var meanShape = model.shapeModel.meanShape;
var numPatches = model.patchModel.numPatches;
// get max and mins, width and height of meanshape
msymax = 0;
msxmin = msymin = 1000000;
for (var i = 0;i < numPatches;i++) {
if (meanShape[i][0] < msxmin) msxmin = meanShape[i][0];
if (meanShape[i][1] < msymin) msymin = meanShape[i][1];
if (meanShape[i][1] > msymax) msymax = meanShape[i][1];
}
msmodelheight = msymax-msymin;
var jf = new jsfeat_face(params);
this.init = function(video) {
element = video;
jf.init(element);
};
var getBoundingBox = function(box) {
return new Promise(function(resolve, reject) {
if (box) {
resolve({x : box[0], y : box[1], width : box[2], height : box[3]});
} else {
resolve(jf.findFace());
}
});
};
var getFinegrainedPosition = function(candidate) {
var translateX, translateY, scaling, rotation;
var x = candidate.x;
var y = candidate.y;
var w = candidate.width;
var h = candidate.height;
// var debugCC = document.getElementById('overlay2').getContext('2d')
if (model.hints && mosseFilter && left_eye_filter && right_eye_filter && nose_filter) {
var noseFilterWidth = w * 4.5/10;
var eyeFilterWidth = w * 6/10;
// detect position of eyes and nose via mosse filter
var nose_result = mossef_nose.track(element, Math.round(x+(w/2)-(noseFilterWidth/2)), Math.round(y+h*(5/8)-(noseFilterWidth/2)), noseFilterWidth, noseFilterWidth, false);
var right_result = mossef_righteye.track(element, Math.round(x+(w*3/4)-(eyeFilterWidth/2)), Math.round(y+h*(2/5)-(eyeFilterWidth/2)), eyeFilterWidth, eyeFilterWidth, false);
var left_result = mossef_lefteye.track(element, Math.round(x+(w/4)-(eyeFilterWidth/2)), Math.round(y+h*(2/5)-(eyeFilterWidth/2)), eyeFilterWidth, eyeFilterWidth, false);
right_eye_position[0] = Math.round(x+(w*3/4)-(eyeFilterWidth/2))+right_result[0];
right_eye_position[1] = Math.round(y+h*(2/5)-(eyeFilterWidth/2))+right_result[1];
left_eye_position[0] = Math.round(x+(w/4)-(eyeFilterWidth/2))+left_result[0];
left_eye_position[1] = Math.round(y+h*(2/5)-(eyeFilterWidth/2))+left_result[1];
nose_position[0] = Math.round(x+(w/2)-(noseFilterWidth/2))+nose_result[0];
nose_position[1] = Math.round(y+h*(5/8)-(noseFilterWidth/2))+nose_result[1];
// drawDetection(debugCC, candidate, [left_eye_position, right_eye_positions, nose_position]);
// get eye and nose positions of model
var lep = model.hints.leftEye;
var rep = model.hints.rightEye;
var mep = model.hints.nose;
// get scaling, rotation, etc. via procrustes analysis
var procrustes_params = procrustes([left_eye_position, right_eye_position, nose_position], [lep, rep, mep]);
translateX = procrustes_params[0];
translateY = procrustes_params[1];
scaling = procrustes_params[2];
rotation = procrustes_params[3];
// drawFacialPoints(debugCC, [lep, rep, mep], procrustes_params);
} else {
// drawBoundingBox(debugCC, [x,y,w,h]);
scaling = w/msmodelheight;
rotation = 0;
translateX = x-(msxmin*scaling)+0.1*w;
translateY = y-(msymin*scaling)+0.25*h;
}
return [scaling, rotation, translateX, translateY];
};
// get initial starting point for model
this.getInitialPosition = function(box) {
return new Promise(function(resolve, reject) {
getBoundingBox(box)
.then(getFinegrainedPosition)
.then(resolve)
.catch(reject);
});
};
// procrustes analysis
function procrustes(template, shape) {
// assume template and shape is a vector of x,y-coordinates
//i.e. template = [[x1,y1], [x2,y2], [x3,y3]];
var templateClone = [];
var shapeClone = [];
for (var i = 0;i < template.length;i++) {
templateClone[i] = [template[i][0], template[i][1]];
}
for (var i = 0;i < shape.length;i++) {
shapeClone[i] = [shape[i][0], shape[i][1]];
}
shape = shapeClone;
template = templateClone;
// calculate translation
var templateMean = [0.0, 0.0];
for (var i = 0;i < template.length;i++) {
templateMean[0] += template[i][0];
templateMean[1] += template[i][1];
}
templateMean[0] /= template.length;
templateMean[1] /= template.length;
var shapeMean = [0.0, 0.0];
for (var i = 0;i < shape.length;i++) {
shapeMean[0] += shape[i][0];
shapeMean[1] += shape[i][1];
}
shapeMean[0] /= shape.length;
shapeMean[1] /= shape.length;
var translationX = templateMean[0] - shapeMean[0];
var translationY = templateMean[1] - shapeMean[1];
// centralize
for (var i = 0;i < shape.length;i++) {
shape[i][0] -= shapeMean[0];
shape[i][1] -= shapeMean[1];
}
for (var i = 0;i < template.length;i++) {
template[i][0] -= templateMean[0];
template[i][1] -= templateMean[1];
}
// scaling
var scaleS = 0.0;
for (var i = 0;i < shape.length;i++) {
scaleS += ((shape[i][0])*(shape[i][0]));
scaleS += ((shape[i][1])*(shape[i][1]));
}
scaleS = Math.sqrt(scaleS/shape.length);
var scaleT = 0.0;
for (var i = 0;i < template.length;i++) {
scaleT += ((template[i][0])*(template[i][0]));
scaleT += ((template[i][1])*(template[i][1]));
}
scaleT = Math.sqrt(scaleT/template.length);
var scaling = scaleT/scaleS;
for (var i = 0;i < shape.length;i++) {
shape[i][0] *= scaling;
shape[i][1] *= scaling;
}
// rotation
var top = 0.0;
var bottom = 0.0;
for (var i = 0;i < shape.length;i++) {
top += (shape[i][0]*template[i][1] - shape[i][1]*template[i][0]);
bottom += (shape[i][0]*template[i][0] + shape[i][1]*template[i][1]);
}
var rotation = Math.atan(top/bottom);
translationX += (shapeMean[0]-(scaling*Math.cos(-rotation)*shapeMean[0])-(scaling*shapeMean[1]*Math.sin(-rotation)));
translationY += (shapeMean[1]+(scaling*Math.sin(-rotation)*shapeMean[0])-(scaling*shapeMean[1]*Math.cos(-rotation)));
return [translationX, translationY, scaling, rotation];
}
};
// simple wrapper for jsfeat face detector that can run as a webworker
var jsfeat_face = function(parameters) {
var params = parameters;
var maxWorkSize = params.workSize;
var useWebWorkers = params.useWebWorkers;
var work_canvas = document.createElement('canvas');
var work_ctx = work_canvas.getContext('2d');
var videoWidth, videoHeight, scale, video, w, h;
var img_u8, edg, ii_sum, ii_sqsum, ii_tilted, ii_canny, classifier;
var worker;
if (useWebWorkers) {
Worker.createURL = function(func_or_string) {
var str = (typeof func_or_string === 'function')?func_or_string.toString():func_or_string;
str = str.replace("'FRONTALFACE_PLACEHOLDER'", JSON.stringify(jsfeat_1.haar.frontalface));
var blob = new Blob(['\'use strict\';\nself.onmessage ='+str], { type: 'text/javascript' });
return window.URL.createObjectURL(blob);
};
Worker.create = function(func_or_string) {
return new Worker(Worker.createURL(func_or_string));
};
worker = Worker.create(findFaceWorker);
}
this.init = function(element) {
video = element;
videoWidth = video.width;
videoHeight = video.height;
// scale down canvas we do detection on (to reduce noisy detections)
scale = Math.min(maxWorkSize/videoWidth, maxWorkSize/videoHeight);
w = (videoWidth*scale)|0;
h = (videoHeight*scale)|0;
work_canvas.height = h;
work_canvas.width = w;
if (!useWebWorkers) {
img_u8 = new jsfeat_1.matrix_t(w, h, jsfeat_1.U8_t | jsfeat_1.C1_t);
edg = new jsfeat_1.matrix_t(w, h, jsfeat_1.U8_t | jsfeat_1.C1_t);
ii_sum = new Int32Array((w+1)*(h+1));
ii_sqsum = new Int32Array((w+1)*(h+1));
ii_tilted = new Int32Array((w+1)*(h+1));
ii_canny = new Int32Array((w+1)*(h+1));
classifier = jsfeat_1.haar.frontalface;
}
};
this.findFace = function () {
work_ctx.drawImage(video, 0, 0, work_canvas.width, work_canvas.height);
var imageData = work_ctx.getImageData(0, 0, work_canvas.width, work_canvas.height);
return new Promise(function(resolve, reject) {
if (useWebWorkers) {
worker.addEventListener('message', function (e) {
if (e.data.faces.length > 0) {
resolve(e.data.faces[0]);
} else {
reject();
}
}.bind(this), false);
worker.postMessage({
w: work_canvas.width,
h: work_canvas.height,
videoWidth: videoWidth,
imageData:imageData,
params: params
});
} else {
jsfeat_1.imgproc.grayscale(imageData.data, work_canvas.width, work_canvas.height, img_u8);
// possible params
if(params.equalizeHistogram) {
jsfeat_1.imgproc.equalize_histogram(img_u8, img_u8);
}
//jsfeat.imgproc.gaussian_blur(img_u8, img_u8, 3);
jsfeat_1.imgproc.compute_integral_image(img_u8, ii_sum, ii_sqsum, classifier.tilted ? ii_tilted : null);
if(params.useCanny) {
jsfeat_1.imgproc.canny(img_u8, edg, 10, 50);
jsfeat_1.imgproc.compute_integral_image(edg, ii_canny, null, null);
}
jsfeat_1.haar.edgesDensity = params.edgesDensity;
var rects = jsfeat_1.haar.detect_multi_scale(ii_sum, ii_sqsum, ii_tilted, params.useCanny? ii_canny : null, img_u8.cols, img_u8.rows, classifier, params.scaleFactor, params.minScale);
rects = jsfeat_1.haar.group_rectangles(rects, params.min_neighbors);
for (var i = rects.length-1;i >= 0;i--) {
if (rects[i].confidence < params.confidenceThreshold) {
rects.splice(i,1);
}
}
var rl = rects.length;
if (rl == 0) {
reject();
} else {
var best = rects[0];
for (var i = 1; i < rl; i++) {
if (rects[i].neighbors > best.neighbors) {
best = rects[i];
} else if (rects[i].neighbors == best.neighbors) {
// if (rects[i].width > best.width) best = rects[i]; // use biggest rect
if (rects[i].confidence > best.confidence) best = rects[i]; // use most confident rect
}
}
var sc = videoWidth / img_u8.cols;
best.x = (best.x*sc)|0;
best.y = (best.y*sc)|0;
best.width = (best.width*sc)|0;
best.height = (best.height*sc)|0;
resolve(best);
}
}
});
};
};
/**
* Fast Fourier Transform
* 1D-FFT/IFFT, 2D-FFT/IFFT (radix-2)
*
* @author ryo / github.com/wellflat
* Based on https://github.com/wellflat/javascript-labs with some tiny optimizations
*/
function FFT$1() {
var _n = 0, // order
_bitrev = null, // bit reversal table
_cstb = null; // sin/cos table
var _tre, _tim;
this.init = function (n) {
if(n !== 0 && (n & (n - 1)) === 0) {
_n = n;
_setVariables();
_makeBitReversal();
_makeCosSinTable();
} else {
throw new Error('init: radix-2 required');
}
};
// 1D-FFT
this.fft1d = function (re, im) {
fft(re, im, 1);
};
// 1D-IFFT
this.ifft1d = function (re, im) {
var n = 1/_n;
fft(re, im, -1);
for(var i=0; i<_n; i++) {
re[i] *= n;
im[i] *= n;
}
};
// 2D-FFT
this.fft2d = function (re, im) {
var i = 0;
// x-axis
for(var y=0; y<_n; y++) {
i = y*_n;
for(var x1=0; x1<_n; x1++) {
_tre[x1] = re[x1 + i];
_tim[x1] = im[x1 + i];
}
this.fft1d(_tre, _tim);
for(var x2=0; x2<_n; x2++) {
re[x2 + i] = _tre[x2];
im[x2 + i] = _tim[x2];
}
}
// y-axis
for(var x=0; x<_n; x++) {
for(var y1=0; y1<_n; y1++) {
i = x + y1*_n;
_tre[y1] = re[i];
_tim[y1] = im[i];
}
this.fft1d(_tre, _tim);
for(var y2=0; y2<_n; y2++) {
i = x + y2*_n;
re[i] = _tre[y2];
im[i] = _tim[y2];
}
}
};
// 2D-IFFT
this.ifft2d = function (re, im) {
var i = 0;
// x-axis
for(var y=0; y<_n; y++) {
i = y*_n;
for(var x1=0; x1<_n; x1++) {
_tre[x1] = re[x1 + i];
_tim[x1] = im[x1 + i];
}
this.ifft1d(_tre, _tim);
for(var x2=0; x2<_n; x2++) {
re[x2 + i] = _tre[x2];
im[x2 + i] = _tim[x2];
}
}
// y-axis
for(var x=0; x<_n; x++) {
for(var y1=0; y1<_n; y1++) {
i = x + y1*_n;
_tre[y1] = re[i];
_tim[y1] = im[i];
}
this.ifft1d(_tre, _tim);
for(var y2=0; y2<_n; y2++) {
i = x + y2*_n;
re[i] = _tre[y2];
im[i] = _tim[y2];
}
}
};
// 2D-IFFT, real-valued
// only outputs the real valued part
this.real_ifft2d = function (re, im) {
var i2;
var i = 0;
// x-axis
for(var y=0; y<_n; y++) {
i = y*_n;
for(var x1=0; x1<_n; x1++) {
_tre[x1] = re[x1 + i];
_tim[x1] = im[x1 + i];
}
this.ifft1d(_tre, _tim);
for(var x2=0; x2<_n; x2++) {
re[x2 + i] = _tre[x2];
im[x2 + i] = _tim[x2];
}
}
// y-axis
var halfn = _n/2;
var rowIdx = 0;
for(var x=0; x<_n; x+=2) {
//untangle
i = x;
i2 = x+1;
_tre[0] = re[0 + i];
_tim[0] = re[0 + i2];
_tre[_n/2] = re[(halfn*_n) + i];
_tim[_n/2] = re[(halfn*_n) + i2];
for (var x2=1;x2<halfn;x2++) {
rowIdx = x2*_n;
_tre[x2] = re[rowIdx+i] - im[rowIdx + i2];
_tre[_n - x2] = re[rowIdx+i] + im[rowIdx + i2];
_tim[x2] = im[rowIdx+i] + re[rowIdx+i2];
_tim[_n - x2] = re[rowIdx+i2] - im[rowIdx+i];
}
this.ifft1d(_tre, _tim);
for(var y2=0; y2<_n; y2++) {
i = x + y2*_n;
i2 = (x + 1) + y2*_n;
re[i] = _tre[y2];
re[i2] = _tim[y2];
}
}
};
// 2D-FFT, real-valued only
// ignores the imaginary input
// see:
// http://www.inf.fu-berlin.de/lehre/SS12/SP-Par/download/fft1.pdf
// http://cnx.org/content/m12021/latest/
// http://images.apple.com/acg/pdf/g4fft.pdf
// http://www.ti.com/lit/an/spra291/spra291.pdf
this.real_fft2d = function (re, im) {
var i = 0, i2 = 0;
// x-axis
for(var y=0; y<_n; y += 2) {
i = y*_n;
i2 = (y+1)*_n;
// tangle
for(var x1=0; x1<_n; x1++) {
_tre[x1] = re[x1 + i];
_tim[x1] = re[x1 + i2];
}
this.fft1d(_tre, _tim);
// untangle
re[0 + i] = _tre[0];
re[0 + i2] = _tim[0];
im[0 + i] = 0;
im[0 + i2] = 0;
re[_n/2 + i] = _tre[_n/2];
re[_n/2 + i2] = _tim[_n/2];
im[_n/2 + i] = 0;
im[_n/2 + i2] = 0;
for(var x2=1;x2<(_n/2);x2++) {
re[x2 + i] = 0.5 * (_tre[x2] + _tre[_n - x2]);
im[x2 + i] = 0.5 * (_tim[x2] - _tim[_n - x2]);
re[x2 + i2] = 0.5 * (_tim[x2] + _tim[_n - x2]);
im[x2 + i2] = -0.5 * (_tre[x2] - _tre[_n - x2]);
re[(_n-x2) + i] = re[x2 + i];
im[(_n-x2) + i] = -im[x2 + i];
re[(_n-x2) + i2] = re[x2 + i2];
im[(_n-x2) + i2] = -im[x2 + i2];
}
}
// y-axis
for(var x=0; x<_n; x++) {
for(var y1=0; y1<_n; y1++) {
i = x + y1*_n;
_tre[y1] = re[i];
_tim[y1] = im[i];
}
this.fft1d(_tre, _tim);
for(var y2=0; y2<_n; y2++) {
i = x + y2*_n;
re[i] = _tre[y2];
im[i] = _tim[y2];
}
}
};
// core operation of FFT
function fft(re, im, inv) {
var d, h, ik, m, tmp, wr, wi, xr, xi,
n4 = _n >> 2;
// bit reversal
for(var l=0; l<_n; l++) {
m = _bitrev[l];
if(l < m) {
tmp = re[l];
re[l] = re[m];
re[m] = tmp;
tmp = im[l];
im[l] = im[m];
im[m] = tmp;
}
}
// butterfly operation
//butfly(re,im,inv,n4);
for(var k=1; k<_n; k<<=1) {
h = 0;
d = _n/(k << 1);
for(var j=0; j<k; j++) {
wr = _cstb[h + n4];
wi = inv*_cstb[h];
for(var i=j; i<_n; i+=(k<<1)) {
ik = i + k;
xr = wr*re[ik] + wi*im[ik];
xi = wr*im[ik] - wi*re[ik];
re[ik] = re[i] - xr;
re[i] += xr;
im[ik] = im[i] - xi;
im[i] += xi;
}
h += d;
}
}
}
function _setVariables() {
if(typeof Uint8Array !== 'undefined') {
_bitrev = new Uint8Array(_n);
} else {
_bitrev = new Array(_n);
}
if(typeof Float64Array !== 'undefined') {
_cstb = new Float64Array(_n*1.25);
_tre = new Float64Array(_n);
_tim = new Float64Array(_n);
} else {
_cstb = new Array(_n*1.25);
_tre = new Array(_n);
_tim = new Array(_n);
}
}
// make bit reversal table
function _makeBitReversal() {
var i = 0,
j = 0,
k = 0;
_bitrev[0] = 0;
while(++i < _n) {
k = _n >> 1;
while(k <= j) {
j -= k;
k >>= 1;
}
j += k;
_bitrev[i] = j;
}
}
// make trigonometric function table
function _makeCosSinTable() {
var n2 = _n >> 1,
n4 = _n >> 2,
n8 = _n >> 3,
n2p4 = n2 + n4,
t = Math.sin(Math.PI/_n),
dc = 2*t*t,
ds = Math.sqrt(dc*(2 - dc)),
c = _cstb[n4] = 1,
s = _cstb[0] = 0;
t = 2*dc;
for(var i=1; i<n8; i++) {
c -= dc;
dc += t*c;
s += ds;
ds -= t*s;
_cstb[i] = s;
_cstb[n4 - i] = c;
}
if(n8 !== 0) {
_cstb[n8] = Math.sqrt(0.5);
}
for(var j=0; j<n4; j++) {
_cstb[n2 - j] = _cstb[j];
}
for(var k=0; k<n2p4; k++) {
_cstb[k + n2] = -_cstb[k];
}
}
}
var svmFilter = function() {
var _fft, fft_filters, responses, biases;
var fft_size, filterLength, filter_width, search_width, num_patches;
var temp_imag_part, temp_real_part;
// fft function
this.fft_inplace = function(array, _im_part) {
// in-place
if (typeof _im_part == 'undefined') {
_im_part = temp_imag_part;
}
for (var i = 0;i < filterLength;i++) {
_im_part[i] = 0.0;
}
_fft.real_fft2d(array,_im_part);
return [array, _im_part];
};
this.ifft = function(rn, cn) {
// in-place
_fft.real_ifft2d(rn, cn);
return rn;
};
var complex_mult_inplace = function(cn1, cn2) {
// in-place, cn1 is the one modified
var temp1, temp2;
for (var r = 0;r < filterLength;r++) {
temp1 = (cn1[0][r]*cn2[0][r]) - (cn1[1][r]*cn2[1][r]);
temp2 = (cn1[0][r]*cn2[1][r]) + (cn1[1][r]*cn2[0][r]);
cn1[0][r] = temp1;
cn1[1][r] = temp2;
}
};
this.init = function(filter_input, bias_input, numPatches, filterWidth, searchWidth) {
// calculate needed size of fft (has to be power of two)
fft_size = upperPowerOfTwo(filterWidth-1+searchWidth);
filterLength = fft_size*fft_size;
_fft = new FFT$1();
_fft.init(fft_size);
fft_filters = Array(numPatches);
var fft_filter;
var edge = (filterWidth-1)/2;
for (var i = 0;i < numPatches;i++) {
var flar_fi0 = new Float64Array(filterLength);
var flar_fi1 = new Float64Array(filterLength);
// load filter
var xOffset, yOffset;
for (var j = 0;j < filterWidth;j++) {
for (var k = 0;k < filterWidth;k++) {
// TODO : rotate filter
xOffset = k < edge ? (fft_size-edge) : (-edge);
yOffset = j < edge ? (fft_size-edge) : (-edge);
flar_fi0[k+xOffset+((j+yOffset)*fft_size)] = filter_input[i][(filterWidth-1-j)+((filterWidth-1-k)*filterWidth)];
/*xOffset = k < edge ? (fft_size-edge) : (-edge);
yOffset = j < edge ? (fft_size-edge) : (-edge);
flar_fi0[k+xOffset+((j+yOffset)*fft_size)] = filter_input[i][k+(j*filterWidth)];*/
//console.log(k + ','+ j+':' + (k+xOffset+((j+yOffset)*fft_size)))
}
}
// fft it and store
fft_filter = this.fft_inplace(flar_fi0, flar_fi1);
fft_filters[i] = fft_filter;
}
// set up biases
biases = new Float64Array(numPatches);
for (var i = 0;i < numPatches;i++) {
biases[i] = bias_input[i];
}
responses = Array(numPatches);
temp_imag_part = Array(numPatches);
for (var i = 0;i < numPatches;i++) {
responses[i] = new Float64Array(searchWidth*searchWidth);
temp_imag_part[i] = new Float64Array(searchWidth*searchWidth);
}
temp_real_part = new Float64Array(filterLength);
num_patches = numPatches;
filter_width = filterWidth;
search_width = searchWidth;
};
this.getResponses = function(patches) {
var response, edge;
var patch_width = filter_width-1+search_width;
for (var i = 0;i < num_patches;i++) {
// reset zeroes in temp_real_part
for (var j = 0;j < fft_size*fft_size;j++) {
temp_real_part[j] = 0.0;
}
// normalize patches to 0-1
patches[i] = normalizePatches(patches[i]);
// patch must be padded (with zeroes) to match fft size
for (var j = 0;j < patch_width;j++) {
for (var k = 0;k < patch_width;k++) {
temp_real_part[j + (fft_size*k)] = patches[i][k + (patch_width*j)];
}
}
//drawData(document.getElementById('sketch').getContext('2d'), temp_real_part, 32, 32, false, 0, 0);
// fft it
response = this.fft_inplace(temp_real_part);
// multiply pointwise with filter
complex_mult_inplace(response, fft_filters[i]);
// inverse fft it
response = this.ifft(response[0], response[1]);
// crop out edges
edge = (filter_width-1)/2;
for (var j = 0;j < search_width;j++) {
for (var k = 0;k < search_width;k++) {
responses[i][j + (k*search_width)] = response[edge + k + ((j+edge)*(fft_size))];
}
}
// add bias
for (var j = 0;j < search_width*search_width;j++) {
responses[i][j] += biases[i];
}
// logistic transformation
responses[i] = logisticResponse(responses[i]);
/*responses[i] = new Float64Array(32*32)
for (var j = 0;j < 32;j++) {
for (var k = 0;k < 32;k++) {
responses[i][k + (j*(32))] = response[k + (j*(32))]
}
}*/
// normalization?
inplaceNormalizeFilterMatrix(responses[i]);
}
return responses;
};
var normalizePatches = function(patch) {
var patch_width = filter_width-1+search_width;
var max = 0;
var min = 1000;
var value;
for (var j = 0;j < patch_width;j++) {
for (var k = 0;k < patch_width;k++) {
value = patch[k + (patch_width*j)];
if (value < min) {
min = value;
}
if (value > max) {
max = value;
}
}
}
var scale = max-min;
for (var j = 0;j < patch_width;j++) {
for (var k = 0;k < patch_width;k++) {
patch[k + (patch_width*j)] = (patch[k + (patch_width*j)]-min)/scale;
}
}
return patch;
};
var logisticResponse = function(response) {
// create probability by doing logistic transformation
for (var j = 0;j < search_width;j++) {
for (var k = 0;k < search_width;k++) {
response[j + (k*search_width)] = 1.0/(1.0 + Math.exp(- (response[j + (k*search_width)] - 1.0 )));
}
}
return response;
};
var upperPowerOfTwo = function(x) {
x--;
x |= x >> 1;
x |= x >> 2;
x |= x >> 4;
x |= x >> 8;
x |= x >> 16;
x++;
return x;
};
var inplaceNormalizeFilterMatrix = function(response) {
// normalize responses to lie within [0,1]
var msize = response.length;
var max = 0;
var min = 1;
for (var i = 0;i < msize;i++) {
max = response[i] > max ? response[i] : max;
min = response[i] < min ? response[i] : min;
}
var dist = max-min;
if (dist == 0) {
//console.log('a patchresponse was monotone, causing normalization to fail. Leaving it unchanged.');
} else {
for (var i = 0;i < msize;i++) {
response[i] = (response[i]-min)/dist;
}
}
};
};
var webglUtils = createCommonjsModule(function (module, exports) {
// This code is based on webgl-utils.js authored by Gregg Tavares, license below:
/*
* Copyright (c) 2011, Gregg Tavares
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are
* met:
*
* * Redistributions of source code must retain the above copyright notice,
* this list of conditions and the following disclaimer.
*
* * Redistributions in binary form must reproduce the above copyright notice,
* this list of conditions and the following disclaimer in the documentation
* and/or other materials provided with the distribution.
*
* * Neither the name of greggman.com nor the names of its contributors
* may be used to endorse or promote products derived from this software
* without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS
* IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
* THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
* LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
* NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
(function(){
var LOGGING_ENABLED = true;
/**
* Wrapped logging function.
* @param {string} msg The message to log.
*/
const log = function (msg) {
if (!LOGGING_ENABLED) { return; }
if (window.console && window.console.log) {
window.console.log(msg);
}
};
/**
* Wrapped logging function.
* @param {string} msg The message to log.
*/
const error = function (msg) {
if (!LOGGING_ENABLED) { return; }
if (window.console) {
if (window.console.error) {
window.console.error(msg);
} else if (window.console.log) {
window.console.log(msg);
}
}
throw msg;
};
/**
* Turn off all logging.
*/
const loggingOff = function () {
LOGGING_ENABLED = false;
};
/**
* Check if the page is embedded.
* @return {boolean} True of we are in an iframe
*/
const isInIFrame = function () {
return window !== window.top;
};
/**
* Converts a WebGL enum to a string
* @param {!WebGLContext} gl The WebGLContext to use.
* @param {number} value The enum value.
* @return {string} The enum as a string.
*/
const glEnumToString = function (gl, value) {
for (var p in gl) {
if (gl[p] === value) {
return p;
}
}
return '0x' + value.toString(16);
};
/**
* Creates the HTLM for a failure message
* @param {string} canvasContainerId id of container of th
* canvas.
* @return {string} The html.
*/
const makeFailHTML = function (msg) {
return '' +
'<table style="background-color: #8CE; width: 100%; height: 100%;"><tr>' +
'<td align="center">' +
'<div style="display: table-cell; vertical-align: middle;">' +
'<div style="">' + msg + '</div>' +
'</div>' +
'</td></tr></table>';
};
/**
* Mesasge for getting a webgl browser
* @type {string}
*/
// const GET_A_WEBGL_BROWSER = '' +
// 'This page requires a browser that supports WebGL.<br/>' +
// '<a href="http://get.webgl.org">Click here to upgrade your browser.</a>';
/**
* Mesasge for need better hardware
* @type {string}
*/
// const OTHER_PROBLEM = '' +
// "It doesn't appear your computer can support WebGL.<br/>" +
// '<a href="http://get.webgl.org/troubleshooting/">Click here for more information.</a>';
/**
* Creates a webgl context. If creation fails it will
* change the contents of the container of the <canvas>
* tag to an error message with the correct links for WebGL.
* @param {Element} canvas. The canvas element to create a
* context from.
* @param {WebGLContextCreationAttirbutes} optAttribs Any
* creation attributes you want to pass in.
* @return {WebGLRenderingContext} The created context.
*/
const setupWebGL = function (canvas, optAttribs) {
// const showLink = function (str) {
// var container = canvas.parentNode;
// if (container) {
// container.innerHTML = makeFailHTML(str);
// }
// };
if (!window.WebGLRenderingContext) {
// showLink(GET_A_WEBGL_BROWSER);
return null;
}
var context = create3DContext(canvas, optAttribs);
if (!context) {
// showLink(OTHER_PROBLEM);
return null;
}
return context;
};
/**
* Creates a webgl context.
* @param {!Canvas} canvas The canvas tag to get context
* from. If one is not passed in one will be created.
* @return {!WebGLContext} The created context.
*/
const create3DContext = function (canvas, optAttribs) {
var names = ['webgl', 'experimental-webgl'];
var context = null;
for (var ii = 0; ii < names.length; ++ii) {
try {
context = canvas.getContext(names[ii], optAttribs);
} catch (e) {}
if (context) {
break;
}
}
return context;
};
const updateCSSIfInIFrame = function () {
if (isInIFrame()) {
document.body.className = 'iframe';
}
};
/**
* Gets a WebGL context.
* makes its backing store the size it is displayed.
*/
const getWebGLContext = function (canvas) {
if (isInIFrame()) {
updateCSSIfInIFrame();
// make the canvas backing store the size it's displayed.
canvas.width = canvas.clientWidth;
canvas.height = canvas.clientHeight;
}
var gl = setupWebGL(canvas);
return gl;
};
/**
* Loads a shader.
* @param {!WebGLContext} gl The WebGLContext to use.
* @param {string} shaderSource The shader source.
* @param {number} shaderType The type of shader.
* @param {function(string): void) optErrorCallback callback for errors.
* @return {!WebGLShader} The created shader.
*/
const loadShader = function (gl, shaderSource, shaderType, optErrorCallback) {
var errFn = optErrorCallback || error;
// Create the shader object
var shader = gl.createShader(shaderType);
// Load the shader source
gl.shaderSource(shader, shaderSource);
// Compile the shader
gl.compileShader(shader);
// Check the compile status
var compiled = gl.getShaderParameter(shader, gl.COMPILE_STATUS);
if (!compiled) {
// Something went wrong during compilation; get the error
var lastError = gl.getShaderInfoLog(shader);
errFn("*** Error compiling shader '" + shader + "':" + lastError);
gl.deleteShader(shader);
return null;
}
return shader;
};
/**
* Creates a program, attaches shaders, binds attrib locations, links the
* program and calls useProgram.
* @param {!Array.<!WebGLShader>} shaders The shaders to attach
* @param {!Array.<string>} optAttribs The attribs names.
* @param {!Array.<number>} optLocations The locations for the attribs.
*/
const loadProgram = function (gl, shaders, optAttribs, optLocations) {
var program = gl.createProgram();
for (var i = 0; i < shaders.length; ++i) {
gl.attachShader(program, shaders[i]);
}
if (optAttribs) {
for (var i = 0; i < optAttribs.length; ++i) {
gl.bindAttribLocation(
program,
optLocations ? optLocations[i] : i,
optAttribs[i]);
}
}
gl.linkProgram(program);
// Check the link status
const linked = gl.getProgramParameter(program, gl.LINK_STATUS);
if (!linked) {
// something went wrong with the link
const lastError = gl.getProgramInfoLog(program);
error('Error in program linking:' + lastError);
gl.deleteProgram(program);
return null;
}
return program;
};
/**
* Loads a shader from a script tag.
* @param {!WebGLContext} gl The WebGLContext to use.
* @param {string} scriptId The id of the script tag.
* @param {number} optShaderType The type of shader. If not passed in it will
* be derived from the type of the script tag.
* @param {function(string): void) optErrorCallback callback for errors.
* @return {!WebGLShader} The created shader.
*/
const createShaderFromScript = function (
gl, scriptId, optShaderType, optErrorCallback
) {
var shaderSource = '';
var shaderType;
var shaderScript = document.getElementById(scriptId);
if (!shaderScript) {
throw new Error('*** Error: unknown script element' + scriptId);
}
shaderSource = shaderScript.text;
if (!optShaderType) {
if (shaderScript.type === 'x-shader/x-vertex') {
shaderType = gl.VERTEX_SHADER;
} else if (shaderScript.type === 'x-shader/x-fragment') {
shaderType = gl.FRAGMENT_SHADER;
} else if (
shaderType !== gl.VERTEX_SHADER &&
shaderType !== gl.FRAGMENT_SHADER
) {
throw new Error('*** Error: unknown shader type');
}
}
return loadShader(
gl,
shaderSource,
optShaderType || shaderType,
optErrorCallback
);
};
{
module.exports = {
setupWebGL : setupWebGL,
createProgram : loadProgram,
createShaderFromScript : createShaderFromScript,
getWebGLContext : getWebGLContext,
loadShader : loadShader
};
}
}());
});
var webglUtils_1 = webglUtils.setupWebGL;
var webglUtils_2 = webglUtils.createProgram;
var webglUtils_5 = webglUtils.loadShader;
var webglFilter = function() {
/*
* Textures:
* 0 : raw filter
* 1 : patches
* 2 : finished response
* 3 : grad/lbp treated patches
* 4 : sobel filter
* 5 : lbp filter
*
* Routing:
* ( ) 0/4/5 --\
* ( ) _\|
* 1 ----> ( ---------->3 ) ----------> 2
* lbpResponse/ patchResponse
* gradientResponse
*/
var gl, canvas;
var filterWidth, filterHeight, patchWidth, patchHeight, numPatches, canvasWidth, canvasHeight;
var patchResponseProgram, patchDrawProgram;
var fbo, numBlocks, patchTex;
var drawRectBuffer, drawLayerBuffer, drawImageBuffer, rttTexture;
var texCoordBuffer, texCoordLocation, apositionBuffer;
var newCanvasWidth, newCanvasBlockHeight, newCanvasHeight;
var drawOutRectangles, drawOutImages, drawOutLayer;
var patchCells, textureWidth, textureHeight, patchSize, patchArray;
var biases;
var lbpResponseProgram;
var lbpTexCoordLocation, lbpTexCoordBuffer, lbpPositionLocation, lbpAPositionBuffer;
var gradientResponseProgram;
var gbo, gradTexCoordLocation, gradTexCoordBuffer, gradPositionLocation, gradAPositionBuffer;
var lbpInit = false;
var sobelInit = false;
var rawInit = false;
var lbpResponseVS = [
'attribute vec2 a_texCoord;',
'attribute vec2 a_position;',
'',
'varying vec2 v_texCoord;',
'',
'void main() {',
' // transform coordinates to regular coordinates',
' gl_Position = vec4(a_position,0.0,1.0);',
' ',
' // pass the texCoord to the fragment shader',
' v_texCoord = a_texCoord;',
'}'
].join('\n');
var lbpResponseFS;
var gradientResponseVS = [
'attribute vec2 a_texCoord;',
'attribute vec2 a_position;',
'',
'varying vec2 v_texCoord;',
'',
'void main() {',
' // transform coordinates to regular coordinates',
' gl_Position = vec4(a_position,0.0,1.0);',
' ',
' // pass the texCoord to the fragment shader',
' v_texCoord = a_texCoord;',
'}'
].join('\n');
var gradientResponseFS;
var patchResponseVS;
var patchResponseFS;
var drawResponsesVS = [
'attribute vec2 a_texCoord_draw;',
'attribute vec2 a_position_draw;',
'attribute float a_patchChoice_draw;',
'',
'uniform vec2 u_resolutiondraw;',
'',
'varying vec2 v_texCoord;',
'varying float v_select;',
'',
'void main() {',
' // convert the rectangle from pixels to 0.0 to 1.0',
' vec2 zeroToOne = a_position_draw / u_resolutiondraw;',
'',
' // convert from 0->1 to 0->2',
' vec2 zeroToTwo = zeroToOne * 2.0;',
'',
' // convert from 0->2 to -1->+1 (clipspace)',
' vec2 clipSpace = zeroToTwo - 1.0;',
' ',
' // transform coordinates to regular coordinates',
' gl_Position = vec4(clipSpace * vec2(1.0, 1.0), 0, 1);',
'',
' // pass the texCoord to the fragment shader',
' v_texCoord = a_texCoord_draw;',
' ',
' v_select = a_patchChoice_draw;',
'}'
].join('\n');
var drawResponsesFS = [
'precision mediump float;',
'',
'// our responses',
'uniform sampler2D u_responses;',
'',
'// the texCoords passed in from the vertex shader.',
'varying vec2 v_texCoord;',
'varying float v_select;',
'',
'const vec4 bit_shift = vec4(256.0*256.0*256.0, 256.0*256.0, 256.0, 1.0);',
'const vec4 bit_mask = vec4(0.0, 1.0/256.0, 1.0/256.0, 1.0/256.0);',
'',
'// packing code from here http://stackoverflow.com/questions/9882716/packing-float-into-vec4-how-does-this-code-work',
'void main() {',
' vec4 colorSum = texture2D(u_responses, v_texCoord);',
' float value = 0.0;',
' if (v_select < 0.1) {',
' value = colorSum[0];',
' } else if (v_select > 0.9 && v_select < 1.1) {',
' value = colorSum[1];',
' } else if (v_select > 1.9 && v_select < 2.1) {',
' value = colorSum[2];',
' } else if (v_select > 2.9 && v_select < 3.1) {',
' value = colorSum[3];',
' } else {',
' value = 1.0;',
' }',
' ',
' vec4 res = fract(value * bit_shift);',
' res -= res.xxyz * bit_mask;',
' ',
' //gl_FragColor = vec4(value, value, value, value);',
' //gl_FragColor = vec4(1.0, value, 1.0, 1.0);',
' gl_FragColor = res;',
'}'
].join('\n');
this.init = function(filters, bias, nP, pW, pH, fW, fH) {
// we assume filterVector goes from left to right, rowwise, i.e. row-major order
if (fW != fH) {
alert('filter width and height must be same size!');
return;
}
// if filter width is not odd, alert
if (fW % 2 == 0 || fH % 2 == 0) {
alert('filters used in svm must be of odd dimensions!');
return;
}
// setup variables
biases = bias;
filterWidth = fW;
filterHeight = fH;
patchWidth = pW;
patchHeight = pH;
numPatches = nP;
numBlocks = Math.floor(numPatches / 4) + Math.ceil((numPatches % 4)/4);
canvasWidth = patchWidth;
canvasHeight = patchHeight*numBlocks;
newCanvasWidth = patchWidth-filterWidth+1;
newCanvasBlockHeight = patchHeight-filterWidth+1;
newCanvasHeight = newCanvasBlockHeight*numPatches;
patchCells = (Math.floor(numPatches / 4) + Math.ceil((numPatches % 4)/4));
textureWidth = patchWidth;
textureHeight = patchHeight*patchCells;
patchSize = patchWidth*patchHeight;
patchArray = new Float32Array(patchSize*patchCells*4);
var opp = [1/patchWidth, 1/(patchHeight*numBlocks)];
// write out shaders
patchResponseFS = [
'precision mediump float;',
'',
'const vec2 u_onePixelPatches = vec2('+(1/patchWidth).toFixed(10)+','+(1/(patchHeight*numBlocks)).toFixed(10)+');',
'const vec2 u_onePixelFilters = vec2('+(1/filterWidth).toFixed(10)+','+(1/(filterHeight*numBlocks)).toFixed(10)+');',
'const float u_halffilterwidth = '+((filterWidth-1.0)/2).toFixed(1)+';',
'const float u_halffilterheight = '+((filterHeight-1.0)/2).toFixed(1)+';',
'',
'// our patches',
'uniform sampler2D u_patches;',
'// our filters',
'uniform sampler2D u_filters;',
'',
'// the texCoords passed in from the vertex shader.',
'varying vec2 v_texCoord;',
'varying vec2 v_texCoordFilters; // this should give us correct filter',
'',
'void main() {',
' vec4 colorSum = vec4(0.0, 0.0, 0.0, 0.0);',
' vec4 maxn = vec4(0.0, 0.0, 0.0, 0.0);',
' vec4 minn = vec4(256.0, 256.0, 256.0, 256.0);',
' vec4 scale = vec4(0.0, 0.0, 0.0, 0.0);',
' vec4 patchValue = vec4(0.0, 0.0, 0.0, 0.0);',
' vec4 filterValue = vec4(0.0, 0.0, 0.0, 0.0);',
' vec4 filterTemp = vec4(0.0, 0.0, 0.0, 0.0);',
' for (int w = 0;w < '+filterWidth+';w++) {',
' for (int h = 0;h < '+filterHeight+';h++) {',
' patchValue = texture2D(u_patches, v_texCoord + u_onePixelPatches * vec2(float(w)-u_halffilterwidth, float(h)-u_halffilterheight));',
' filterValue = texture2D(u_filters, v_texCoordFilters + u_onePixelFilters * vec2(float(w)-u_halffilterwidth, float(h)-u_halffilterheight));',
' maxn = max(patchValue, maxn);',
' minn = min(patchValue, minn);',
' colorSum += patchValue*filterValue;',
' filterTemp += filterValue;',
' } ',
' }',
' scale = maxn-minn;',
' colorSum = (colorSum-(minn*filterTemp))/scale;',
' // logistic transformation',
' colorSum = 1.0/(1.0 + exp(- (colorSum) ));',
' gl_FragColor = colorSum;',
'}'
].join('\n');
patchResponseVS = [
'attribute vec2 a_texCoord;',
'attribute vec2 a_position;',
'',
'const vec2 u_resolution = vec2('+canvasWidth.toFixed(1)+','+canvasHeight.toFixed(1)+');',
'const float u_patchHeight = '+(1/numBlocks).toFixed(10)+';',
'const float u_filterHeight = '+(1/numBlocks).toFixed(10)+';',
'const vec2 u_midpoint = vec2(0.5 ,'+(1/(numBlocks*2)).toFixed(10)+');',
'',
'varying vec2 v_texCoord;',
'varying vec2 v_texCoordFilters;',
'',
'void main() {',
' // convert the rectangle from pixels to 0.0 to 1.0',
' vec2 zeroToOne = a_position / u_resolution;',
'',
' // convert from 0->1 to 0->2',
' vec2 zeroToTwo = zeroToOne * 2.0;',
'',
' // convert from 0->2 to -1->+1 (clipspace)',
' vec2 clipSpace = zeroToTwo - 1.0;',
' ',
' // transform coordinates to regular coordinates',
' gl_Position = vec4(clipSpace * vec2(1.0, 1.0), 0, 1);',
' ',
' // pass the texCoord to the fragment shader',
' v_texCoord = a_texCoord;',
' ',
' // set the filtertexture coordinate based on number filter to use',
' v_texCoordFilters = u_midpoint + vec2(0.0, u_filterHeight * floor(a_texCoord[1]/u_patchHeight));',
'}'
].join('\n');
if ('lbp' in filters) {
// lbpResponseFragment
lbpResponseFS = [
'precision mediump float;',
'',
'uniform vec2 u_onePixelPatches;',
'',
'// our patches',
'uniform sampler2D u_patches;',
'',
'// the texCoords passed in from the vertex shader.',
'varying vec2 v_texCoord;',
'',
'void main() {',
' vec4 topLeft = texture2D(u_patches, v_texCoord + vec2(-'+opp[0].toFixed(5)+', -'+opp[1].toFixed(5)+'));',
' vec4 topMid = texture2D(u_patches, v_texCoord + vec2(0.0, -'+opp[1].toFixed(5)+'));',
' vec4 topRight = texture2D(u_patches, v_texCoord + vec2('+opp[0].toFixed(5)+', -'+opp[1].toFixed(5)+'));',
' vec4 midLeft = texture2D(u_patches, v_texCoord + vec2(-'+opp[0].toFixed(5)+', 0.0));',
' vec4 midMid = texture2D(u_patches, v_texCoord);',
' vec4 midRight = texture2D(u_patches, v_texCoord + vec2('+opp[0].toFixed(5)+', 0.0));',
' vec4 bottomLeft = texture2D(u_patches, v_texCoord + vec2(-'+opp[0].toFixed(5)+', '+opp[1].toFixed(5)+'));',
' vec4 bottomMid = texture2D(u_patches, v_texCoord + vec2(0.0, '+opp[1].toFixed(5)+'));',
' vec4 bottomRight = texture2D(u_patches, v_texCoord + vec2('+opp[0].toFixed(5)+', '+opp[1].toFixed(5)+'));',
' vec4 lbp = step(midMid, midRight)*1.0 + step(midMid, topRight)*2.0 + step(midMid, topMid)*4.0;',
' lbp = lbp + step(midMid, topLeft)*8.0 + step(midMid, midLeft)*16.0 + step(midMid, bottomLeft)*32.0;',
' lbp = lbp + step(midMid, bottomMid)*64.0 + step(midMid, bottomRight)*128.0;',
' gl_FragColor = lbp;',
'}'
].join('\n');
}
if ('sobel' in filters) {
// gradResponseFragment
gradientResponseFS = [
'precision mediump float;',
'',
'uniform vec2 u_onePixelPatches;',
'',
'// our patches',
'uniform sampler2D u_patches;',
'',
'// the texCoords passed in from the vertex shader.',
'varying vec2 v_texCoord;',
'',
'void main() {',
' vec4 bottomLeft = texture2D(u_patches, v_texCoord + vec2(-'+opp[0].toFixed(5)+', '+opp[1].toFixed(5)+'));',
' vec4 bottomRight = texture2D(u_patches, v_texCoord + vec2('+opp[0].toFixed(5)+', '+opp[1].toFixed(5)+'));',
' vec4 topLeft = texture2D(u_patches, v_texCoord + vec2(-'+opp[0].toFixed(5)+', -'+opp[1].toFixed(5)+'));',
' vec4 topRight = texture2D(u_patches, v_texCoord + vec2('+opp[0].toFixed(5)+', -'+opp[1].toFixed(5)+'));',
' vec4 dx = (',
' bottomLeft +',
' (texture2D(u_patches, v_texCoord + vec2(-'+opp[0].toFixed(5)+', 0.0))*vec4(2.0,2.0,2.0,2.0)) +',
' topLeft -',
' bottomRight -',
' (texture2D(u_patches, v_texCoord + vec2('+opp[0].toFixed(5)+', 0.0))*vec4(2.0,2.0,2.0,2.0)) -',
' topRight)/4.0;',
' vec4 dy = (',
' bottomLeft +',
' (texture2D(u_patches, v_texCoord + vec2(0.0, '+opp[1].toFixed(5)+'))*vec4(2.0,2.0,2.0,2.0)) +',
' bottomRight -',
' topLeft -',
' (texture2D(u_patches, v_texCoord + vec2(0.0, -'+opp[1].toFixed(5)+'))*vec4(2.0,2.0,2.0,2.0)) -',
' topRight)/4.0;',
' vec4 gradient = sqrt((dx*dx) + (dy*dy));',
' gl_FragColor = gradient;',
'}'
].join('\n');
}
//create webglcanvas
canvas = document.createElement('canvas');
canvas.setAttribute('width', (patchWidth-filterWidth+1)+'px');
canvas.setAttribute('height', ((patchHeight-filterHeight+1)*numPatches)+'px');
canvas.setAttribute('id', 'renderCanvas');
canvas.setAttribute('style', 'display:none;');
//document.body.appendChild(canvas);
gl = webglUtils_1(canvas, {
premultipliedAlpha: false,
preserveDrawingBuffer : true,
antialias : false
});
// check for float textures support and fail if not
if (!gl.getExtension('OES_texture_float')) {
alert('Your graphics card does not support floating point textures! :(');
return;
}
/** insert filters into textures **/
if ('raw' in filters) {
insertFilter(filters['raw'], gl.TEXTURE0);
rawInit = true;
}
if ('sobel' in filters) {
insertFilter(filters['sobel'], gl.TEXTURE4);
sobelInit = true;
}
if ('lbp' in filters) {
insertFilter(filters['lbp'], gl.TEXTURE5);
lbpInit = true;
}
/** calculate vertices for calculating responses **/
// vertex rectangles to draw out
var rectangles = [];
var halfFilter = (filterWidth-1)/2;
var yOffset;
for (var i = 0;i < numBlocks;i++) {
yOffset = i*patchHeight;
//first triangle
rectangles = rectangles.concat([
halfFilter, yOffset+halfFilter,
patchWidth-halfFilter, yOffset+halfFilter,
halfFilter, yOffset+patchHeight-halfFilter
]);
//second triangle
rectangles = rectangles.concat([
halfFilter, yOffset+patchHeight-halfFilter,
patchWidth-halfFilter, yOffset+halfFilter,
patchWidth-halfFilter, yOffset+patchHeight-halfFilter
]);
}
rectangles = new Float32Array(rectangles);
// image rectangles to draw out
var irectangles = [];
for (var i = 0;i < rectangles.length;i++) {
if (i % 2 == 0) {
irectangles[i] = rectangles[i]/canvasWidth;
} else {
irectangles[i] = rectangles[i]/canvasHeight;
}
}
irectangles = new Float32Array(irectangles);
if ('lbp' in filters || 'sobel' in filters) {
var topCoord = 1.0 - 2/(patchHeight*numBlocks);
var bottomCoord = 1.0 - 2/numBlocks + 2/(patchHeight*numBlocks);
var yOffset;
// calculate position of vertex rectangles for gradient/lbp program
var gradRectangles = [];
for (var i = 0;i < numBlocks;i++) {
yOffset = i * (2/numBlocks);
//first triangle
gradRectangles = gradRectangles.concat([
-1.0, topCoord - yOffset,
1.0, topCoord - yOffset,
-1.0, bottomCoord - yOffset
]);
//second triangle
gradRectangles = gradRectangles.concat([
-1.0, bottomCoord - yOffset,
1.0, topCoord - yOffset,
1.0, bottomCoord - yOffset
]);
}
gradRectangles = new Float32Array(gradRectangles);
topCoord = 1.0 - 1/(patchHeight*numBlocks);
bottomCoord = 1.0 - 1/numBlocks + 1/(patchHeight*numBlocks);
// calculate position of image rectangles to draw out
var gradIRectangles = [];
for (var i = 0;i < numBlocks;i++) {
yOffset = i * (1/numBlocks);
//first triangle
gradIRectangles = gradIRectangles.concat([
0.0, topCoord - yOffset,
1.0, topCoord - yOffset,
0.0, bottomCoord - yOffset
]);
//second triangle
gradIRectangles = gradIRectangles.concat([
0.0, bottomCoord - yOffset,
1.0, topCoord - yOffset,
1.0, bottomCoord - yOffset
]);
}
gradIRectangles = new Float32Array(gradIRectangles);
}
// vertices for drawing out responses
// drawOutRectangles
drawOutRectangles = new Float32Array(12*numPatches);
var yOffset, indexOffset;
for (var i = 0;i < numPatches;i++) {
yOffset = i*newCanvasBlockHeight;
indexOffset = i*12;
//first triangle
drawOutRectangles[indexOffset] = 0.0;
drawOutRectangles[indexOffset+1] = yOffset;
drawOutRectangles[indexOffset+2] = newCanvasWidth;
drawOutRectangles[indexOffset+3] = yOffset;
drawOutRectangles[indexOffset+4] = 0.0;
drawOutRectangles[indexOffset+5] = yOffset+newCanvasBlockHeight;
//second triangle
drawOutRectangles[indexOffset+6] = 0.0;
drawOutRectangles[indexOffset+7] = yOffset+newCanvasBlockHeight;
drawOutRectangles[indexOffset+8] = newCanvasWidth;
drawOutRectangles[indexOffset+9] = yOffset;
drawOutRectangles[indexOffset+10] = newCanvasWidth;
drawOutRectangles[indexOffset+11] = yOffset+newCanvasBlockHeight;
}
// images
drawOutImages = new Float32Array(numPatches*12);
var halfFilterWidth = ((filterWidth-1)/2)/patchWidth;
var halfFilterHeight = ((filterWidth-1)/2)/(patchHeight*patchCells);
var patchHeightT = patchHeight / (patchHeight*patchCells);
for (var i = 0;i < numPatches;i++) {
yOffset = Math.floor(i / 4)*patchHeightT;
indexOffset = i*12;
//first triangle
drawOutImages[indexOffset] = halfFilterWidth;
drawOutImages[indexOffset+1] = yOffset+halfFilterHeight;
drawOutImages[indexOffset+2] = 1.0-halfFilterWidth;
drawOutImages[indexOffset+3] = yOffset+halfFilterHeight;
drawOutImages[indexOffset+4] = halfFilterWidth;
drawOutImages[indexOffset+5] = yOffset+patchHeightT-halfFilterHeight;
//second triangle
drawOutImages[indexOffset+6] = halfFilterWidth;
drawOutImages[indexOffset+7] = yOffset+patchHeightT-halfFilterHeight;
drawOutImages[indexOffset+8] = 1.0-halfFilterWidth;
drawOutImages[indexOffset+9] = yOffset+halfFilterHeight;
drawOutImages[indexOffset+10] = 1.0-halfFilterWidth;
drawOutImages[indexOffset+11] = yOffset+patchHeightT-halfFilterHeight;
}
// layer
drawOutLayer = new Float32Array(numPatches*6);
var layernum;
for (var i = 0;i < numPatches;i++) {
layernum = i % 4;
indexOffset = i*6;
drawOutLayer[indexOffset] = layernum;
drawOutLayer[indexOffset+1] = layernum;
drawOutLayer[indexOffset+2] = layernum;
drawOutLayer[indexOffset+3] = layernum;
drawOutLayer[indexOffset+4] = layernum;
drawOutLayer[indexOffset+5] = layernum;
}
/** set up programs and load attributes etc **/
if ('sobel' in filters) {
var grVertexShader = webglUtils_5(gl, gradientResponseVS, gl.VERTEX_SHADER);
var grFragmentShader = webglUtils_5(gl, gradientResponseFS, gl.FRAGMENT_SHADER);
gradientResponseProgram = webglUtils_2(gl, [grVertexShader, grFragmentShader]);
gl.useProgram(gradientResponseProgram);
// set up vertices with rectangles
gradPositionLocation = gl.getAttribLocation(gradientResponseProgram, 'a_position');
gradAPositionBuffer = gl.createBuffer();
gl.bindBuffer(gl.ARRAY_BUFFER, gradAPositionBuffer);
gl.bufferData(gl.ARRAY_BUFFER, gradRectangles, gl.STATIC_DRAW);
gl.enableVertexAttribArray(gradPositionLocation);
gl.vertexAttribPointer(gradPositionLocation, 2, gl.FLOAT, false, 0, 0);
// set up texture positions
gradTexCoordLocation = gl.getAttribLocation(gradientResponseProgram, 'a_texCoord');
gradTexCoordBuffer = gl.createBuffer();
gl.bindBuffer(gl.ARRAY_BUFFER, gradTexCoordBuffer);
gl.bufferData(gl.ARRAY_BUFFER, gradIRectangles, gl.STATIC_DRAW);
gl.enableVertexAttribArray(gradTexCoordLocation);
gl.vertexAttribPointer(gradTexCoordLocation, 2, gl.FLOAT, false, 0, 0);
// set up patches texture in gradientResponseProgram
gl.uniform1i(gl.getUniformLocation(gradientResponseProgram, 'u_patches'), 1);
}
if ('lbp' in filters) {
var lbpVertexShader = webglUtils_5(gl, lbpResponseVS, gl.VERTEX_SHADER);
var lbpFragmentShader = webglUtils_5(gl, lbpResponseFS, gl.FRAGMENT_SHADER);
lbpResponseProgram = webglUtils_2(gl, [lbpVertexShader, lbpFragmentShader]);
gl.useProgram(lbpResponseProgram);
// set up vertices with rectangles
lbpPositionLocation = gl.getAttribLocation(lbpResponseProgram, 'a_position');
lbpAPositionBuffer = gl.createBuffer();
gl.bindBuffer(gl.ARRAY_BUFFER, lbpAPositionBuffer);
gl.bufferData(gl.ARRAY_BUFFER, gradRectangles, gl.STATIC_DRAW);
gl.enableVertexAttribArray(lbpPositionLocation);
gl.vertexAttribPointer(lbpPositionLocation, 2, gl.FLOAT, false, 0, 0);
// set up texture positions
gradTexCoordLocation = gl.getAttribLocation(lbpResponseProgram, 'a_texCoord');
lbpTexCoordBuffer = gl.createBuffer();
gl.bindBuffer(gl.ARRAY_BUFFER, lbpTexCoordBuffer);
gl.bufferData(gl.ARRAY_BUFFER, gradIRectangles, gl.STATIC_DRAW);
gl.enableVertexAttribArray(lbpTexCoordLocation);
gl.vertexAttribPointer(lbpTexCoordLocation, 2, gl.FLOAT, false, 0, 0);
// set up patches texture in lbpResponseProgram
gl.uniform1i(gl.getUniformLocation(lbpResponseProgram, 'u_patches'), 1);
}
// setup patchdraw program
var drVertexShader = webglUtils_5(gl, drawResponsesVS, gl.VERTEX_SHADER);
var drFragmentShader = webglUtils_5(gl, drawResponsesFS, gl.FRAGMENT_SHADER);
patchDrawProgram = webglUtils_2(gl, [drVertexShader, drFragmentShader]);
gl.useProgram(patchDrawProgram);
// set the resolution/dimension of the canvas
var resolutionLocation = gl.getUniformLocation(patchDrawProgram, 'u_resolutiondraw');
gl.uniform2f(resolutionLocation, newCanvasWidth, newCanvasHeight);
// set u_responses
var responsesLocation = gl.getUniformLocation(patchDrawProgram, 'u_responses');
gl.uniform1i(responsesLocation, 2);
// setup patchresponse program
var prVertexShader = webglUtils_5(gl, patchResponseVS, gl.VERTEX_SHADER);
var prFragmentShader = webglUtils_5(gl, patchResponseFS, gl.FRAGMENT_SHADER);
patchResponseProgram = webglUtils_2(gl, [prVertexShader, prFragmentShader]);
gl.useProgram(patchResponseProgram);
// set up vertices with rectangles
var positionLocation = gl.getAttribLocation(patchResponseProgram, 'a_position');
apositionBuffer = gl.createBuffer();
gl.bindBuffer(gl.ARRAY_BUFFER, apositionBuffer);
gl.bufferData(gl.ARRAY_BUFFER, rectangles, gl.STATIC_DRAW);
gl.enableVertexAttribArray(positionLocation);
gl.vertexAttribPointer(positionLocation, 2, gl.FLOAT, false, 0, 0);
// set up texture positions
texCoordLocation = gl.getAttribLocation(patchResponseProgram, 'a_texCoord');
texCoordBuffer = gl.createBuffer();
gl.bindBuffer(gl.ARRAY_BUFFER, texCoordBuffer);
gl.bufferData(gl.ARRAY_BUFFER, irectangles, gl.STATIC_DRAW);
gl.enableVertexAttribArray(texCoordLocation);
gl.vertexAttribPointer(texCoordLocation, 2, gl.FLOAT, false, 0, 0);
if ('lbp' in filters || 'sobel' in filters) {
// set up gradient/lbp buffer (also used for lbp)
gl.activeTexture(gl.TEXTURE3);
var gradients = gl.createTexture();
gl.bindTexture(gl.TEXTURE_2D, gradients);
gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, patchWidth, patchHeight*numBlocks, 0, gl.RGBA, gl.FLOAT, null);
gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);
gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);
gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.NEAREST);
gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.NEAREST);
// set up gradient/lbp framebuffer
gbo = gl.createFramebuffer();
gl.bindFramebuffer(gl.FRAMEBUFFER, gbo);
gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, gradients, 0);
}
// set up buffer to draw to
gl.activeTexture(gl.TEXTURE2);
rttTexture = gl.createTexture();
gl.bindTexture(gl.TEXTURE_2D, rttTexture);
gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);
gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);
gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.NEAREST);
gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.NEAREST);
gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, patchWidth, patchHeight*numBlocks, 0, gl.RGBA, gl.FLOAT, null);
// set up response framebuffer
fbo = gl.createFramebuffer();
gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);
gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, rttTexture, 0);
gl.viewport(0, 0, patchWidth, patchHeight*numBlocks);
/* initialize some textures and buffers used later on */
patchTex = gl.createTexture();
drawRectBuffer = gl.createBuffer();
drawImageBuffer = gl.createBuffer();
drawLayerBuffer = gl.createBuffer();
};
this.getRawResponses = function(patches) {
// TODO: check patches correct length/dimension
insertPatches(patches);
// switch to correct program
gl.useProgram(patchResponseProgram);
// set u_patches to point to texture 1
gl.uniform1i(gl.getUniformLocation(patchResponseProgram, 'u_patches'), 1);
// set u_filters to point to correct filter
gl.uniform1i(gl.getUniformLocation(patchResponseProgram, 'u_filters'), 0);
// set up vertices with rectangles
var positionLocation = gl.getAttribLocation(patchResponseProgram, 'a_position');
gl.bindBuffer(gl.ARRAY_BUFFER, apositionBuffer);
gl.enableVertexAttribArray(positionLocation);
gl.vertexAttribPointer(positionLocation, 2, gl.FLOAT, false, 0, 0);
// set up texture positions
var texCoordLocation = gl.getAttribLocation(patchResponseProgram, 'a_texCoord');
gl.bindBuffer(gl.ARRAY_BUFFER, texCoordBuffer);
gl.enableVertexAttribArray(texCoordLocation);
gl.vertexAttribPointer(texCoordLocation, 2, gl.FLOAT, false, 0, 0);
// set framebuffer to the original one if not already using it
gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);
gl.viewport(0, 0, patchWidth, patchHeight*numBlocks);
gl.clearColor(0.0, 0.0, 0.0, 1.0);
gl.clear(gl.COLOR_BUFFER_BIT|gl.DEPTH_BUFFER);
// draw to framebuffer
gl.drawArrays(gl.TRIANGLES, 0, patchCells*6);
//gl.finish();
var responses = drawOut('raw');
return responses;
};
this.getSobelResponses = function(patches) {
// check that it is initialized
if (!sobelInit) return;
insertPatches(patches);
/* do sobel filter on patches */
// switch to correct program
gl.useProgram(gradientResponseProgram);
// set up vertices with rectangles
var gradPositionLocation = gl.getAttribLocation(gradientResponseProgram, 'a_position');
gl.bindBuffer(gl.ARRAY_BUFFER, gradAPositionBuffer);
gl.enableVertexAttribArray(gradPositionLocation);
gl.vertexAttribPointer(gradPositionLocation, 2, gl.FLOAT, false, 0, 0);
// set up texture positions
var gradTexCoordLocation = gl.getAttribLocation(gradientResponseProgram, 'a_texCoord');
gl.bindBuffer(gl.ARRAY_BUFFER, gradTexCoordBuffer);
gl.enableVertexAttribArray(gradTexCoordLocation);
gl.vertexAttribPointer(gradTexCoordLocation, 2, gl.FLOAT, false, 0, 0);
// set framebuffer to the original one if not already using it
gl.bindFramebuffer(gl.FRAMEBUFFER, gbo);
gl.viewport(0, 0, patchWidth, patchHeight*numBlocks);
gl.clearColor(0.0, 0.0, 0.0, 1.0);
gl.clear(gl.COLOR_BUFFER_BIT|gl.DEPTH_BUFFER);
// draw to framebuffer
gl.drawArrays(gl.TRIANGLES, 0, patchCells*6);
/* calculate responses */
gl.useProgram(patchResponseProgram);
// set patches and filters to point to correct textures
gl.uniform1i(gl.getUniformLocation(patchResponseProgram, 'u_filters'), 4);
gl.uniform1i(gl.getUniformLocation(patchResponseProgram, 'u_patches'), 3);
var positionLocation = gl.getAttribLocation(patchResponseProgram, 'a_position');
gl.bindBuffer(gl.ARRAY_BUFFER, apositionBuffer);
gl.enableVertexAttribArray(positionLocation);
gl.vertexAttribPointer(positionLocation, 2, gl.FLOAT, false, 0, 0);
// set up texture positions
var texCoordLocation = gl.getAttribLocation(patchResponseProgram, 'a_texCoord');
gl.bindBuffer(gl.ARRAY_BUFFER, texCoordBuffer);
gl.enableVertexAttribArray(texCoordLocation);
gl.vertexAttribPointer(texCoordLocation, 2, gl.FLOAT, false, 0, 0);
gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);
gl.viewport(0, 0, patchWidth, patchHeight*numBlocks);
gl.clearColor(0.0, 0.0, 0.0, 1.0);
gl.clear(gl.COLOR_BUFFER_BIT|gl.DEPTH_BUFFER);
// draw to framebuffer
gl.drawArrays(gl.TRIANGLES, 0, patchCells*6);
/* get the responses */
var responses = drawOut('sobel');
return responses;
};
this.getLBPResponses = function(patches) {
// check that it is initialized
if (!lbpInit) return;
insertPatches(patches);
/* do sobel filter on patches */
// switch to correct program
gl.useProgram(lbpResponseProgram);
// set up vertices with rectangles
var lbpPositionLocation = gl.getAttribLocation(lbpResponseProgram, 'a_position');
gl.bindBuffer(gl.ARRAY_BUFFER, lbpAPositionBuffer);
gl.enableVertexAttribArray(lbpPositionLocation);
gl.vertexAttribPointer(lbpPositionLocation, 2, gl.FLOAT, false, 0, 0);
// set up texture positions
var lbpTexCoordLocation = gl.getAttribLocation(lbpResponseProgram, 'a_texCoord');
gl.bindBuffer(gl.ARRAY_BUFFER, lbpTexCoordBuffer);
gl.enableVertexAttribArray(lbpTexCoordLocation);
gl.vertexAttribPointer(lbpTexCoordLocation, 2, gl.FLOAT, false, 0, 0);
// set framebuffer to the original one if not already using it
gl.bindFramebuffer(gl.FRAMEBUFFER, gbo);
gl.viewport(0, 0, patchWidth, patchHeight*numBlocks);
gl.clearColor(0.0, 0.0, 0.0, 1.0);
gl.clear(gl.COLOR_BUFFER_BIT|gl.DEPTH_BUFFER);
// draw to framebuffer
gl.drawArrays(gl.TRIANGLES, 0, patchCells*6);
/* calculate responses */
gl.useProgram(patchResponseProgram);
gl.uniform1i(gl.getUniformLocation(patchResponseProgram, 'u_filters'), 5);
gl.uniform1i(gl.getUniformLocation(patchResponseProgram, 'u_patches'), 3);
var positionLocation = gl.getAttribLocation(patchResponseProgram, 'a_position');
gl.bindBuffer(gl.ARRAY_BUFFER, apositionBuffer);
gl.enableVertexAttribArray(positionLocation);
gl.vertexAttribPointer(positionLocation, 2, gl.FLOAT, false, 0, 0);
// set up texture positions
var texCoordLocation = gl.getAttribLocation(patchResponseProgram, 'a_texCoord');
gl.bindBuffer(gl.ARRAY_BUFFER, texCoordBuffer);
gl.enableVertexAttribArray(texCoordLocation);
gl.vertexAttribPointer(texCoordLocation, 2, gl.FLOAT, false, 0, 0);
gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);
gl.viewport(0, 0, patchWidth, patchHeight*numBlocks);
gl.clearColor(0.0, 0.0, 0.0, 1.0);
gl.clear(gl.COLOR_BUFFER_BIT|gl.DEPTH_BUFFER);
// draw to framebuffer
gl.drawArrays(gl.TRIANGLES, 0, patchCells*6);
/* get the responses */
var responses = drawOut('lbp');
return responses;
};
var insertPatches = function(patches) {
// pass patches into texture, each patch in either r, g, b or a
var patchArrayIndex = 0;
var patchesIndex1 = 0;
var patchesIndex2 = 0;
for (var i = 0;i < patchCells;i++) {
for (var j = 0;j < patchHeight;j++) {
for (var k = 0;k < patchWidth;k++) {
patchesIndex1 = i*4;
patchesIndex2 = (j*patchWidth) + k;
patchArrayIndex = ((patchSize*i) + patchesIndex2)*4;
//set r with first patch
if (patchesIndex1 < numPatches) {
patchArray[patchArrayIndex] = patches[patchesIndex1][patchesIndex2];
} else {
patchArray[patchArrayIndex] = 0;
}
//set g with 2nd patch
if (patchesIndex1+1 < numPatches) {
patchArray[patchArrayIndex + 1] = patches[patchesIndex1+1][patchesIndex2];
} else {
patchArray[patchArrayIndex + 1] = 0;
}
//set b with 3rd patch
if (patchesIndex1+2 < numPatches) {
patchArray[patchArrayIndex + 2] = patches[patchesIndex1+2][patchesIndex2];
} else {
patchArray[patchArrayIndex + 2] = 0;
}
//set a with 4th patch
if (patchesIndex1+3 < numPatches) {
patchArray[patchArrayIndex + 3] = patches[patchesIndex1+3][patchesIndex2];
} else {
patchArray[patchArrayIndex + 3] = 0;
}
}
}
}
// pass texture into an uniform
gl.activeTexture(gl.TEXTURE1);
gl.bindTexture(gl.TEXTURE_2D, patchTex);
gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, textureWidth, textureHeight, 0, gl.RGBA, gl.FLOAT, patchArray);
gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);
gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);
gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.NEAREST);
gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.NEAREST);
};
var insertFilter = function(filter, textureNum) {
var filterSize = filterWidth*filterHeight;
var filterArray = new Float32Array(filterSize*(numBlocks)*4);
for (var i = 0;i < numBlocks;i++) {
for (var j = 0;j < filterHeight;j++) {
for (var k = 0;k < filterWidth;k++) {
//set r with first filter
if (i*4 < filter.length) {
filterArray[((filterSize*i) + (j*filterWidth) + k)*4] = filter[i*4][(j*filterWidth) + k];
} else {
filterArray[((filterSize*i) + (j*filterWidth) + k)*4] = 0;
}
//set g with 2nd filter
if ((i*4 + 1) < filter.length) {
filterArray[((filterSize*i) + (j*filterWidth) + k)*4 + 1] = filter[(i*4)+1][(j*filterWidth) + k];
} else {
filterArray[((filterSize*i) + (j*filterWidth) + k)*4 + 1] = 0;
}
//set b with 3rd filter
if ((i*4 + 2) < filter.length) {
filterArray[((filterSize*i) + (j*filterWidth) + k)*4 + 2] = filter[(i*4)+2][(j*filterWidth) + k];
} else {
filterArray[((filterSize*i) + (j*filterWidth) + k)*4 + 2] = 0;
}
//set a with 4th filter
if ((i*4 + 3) < filter.length) {
filterArray[((filterSize*i) + (j*filterWidth) + k)*4 + 3] = filter[(i*4)+3][(j*filterWidth) + k];
} else {
filterArray[((filterSize*i) + (j*filterWidth) + k)*4 + 3] = 0;
}
}
}
}
gl.activeTexture(textureNum);
var filterTexture = gl.createTexture();
gl.bindTexture(gl.TEXTURE_2D, filterTexture);
gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, filterWidth, filterHeight*numBlocks, 0, gl.RGBA, gl.FLOAT, filterArray);
gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);
gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);
gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.NEAREST);
gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.NEAREST);
};
var drawOut = function(type) {
// switch programs
gl.useProgram(patchDrawProgram);
// bind canvas buffer
gl.bindFramebuffer(gl.FRAMEBUFFER, null);
gl.viewport(0, 0, newCanvasWidth, newCanvasHeight);
gl.clearColor(0.0, 0.0, 0.0, 1.0);
gl.clear(gl.COLOR_BUFFER_BIT|gl.DEPTH_BUFFER);
gl.bindBuffer(gl.ARRAY_BUFFER, drawRectBuffer);
gl.bufferData(
gl.ARRAY_BUFFER,
drawOutRectangles,
gl.STATIC_DRAW);
var positionLocation = gl.getAttribLocation(patchDrawProgram, 'a_position_draw');
gl.enableVertexAttribArray(positionLocation);
gl.vertexAttribPointer(positionLocation, 2, gl.FLOAT, false, 0, 0);
gl.bindBuffer(gl.ARRAY_BUFFER, drawImageBuffer);
gl.bufferData(
gl.ARRAY_BUFFER,
drawOutImages,
gl.STATIC_DRAW);
var textureLocation = gl.getAttribLocation(patchDrawProgram, 'a_texCoord_draw');
gl.enableVertexAttribArray(textureLocation);
gl.vertexAttribPointer(textureLocation, 2, gl.FLOAT, false, 0, 0);
gl.bindBuffer(gl.ARRAY_BUFFER, drawLayerBuffer);
gl.bufferData(
gl.ARRAY_BUFFER,
drawOutLayer,
gl.STATIC_DRAW);
var layerLocation = gl.getAttribLocation(patchDrawProgram, 'a_patchChoice_draw');
gl.enableVertexAttribArray(layerLocation);
gl.vertexAttribPointer(layerLocation, 1, gl.FLOAT, false, 0, 0);
// draw out
gl.drawArrays(gl.TRIANGLES, 0, numPatches*6);
var responses = getOutput();
responses = unpackToFloat(responses);
responses = splitArray(responses, numPatches);
responses = addBias(responses, biases[type]);
// normalize responses to lie within [0,1]
var rl = responses.length;
for (var i = 0;i < rl;i++) {
responses[i] = normalizeFilterMatrix(responses[i]);
}
return responses;
};
var addBias = function(responses, bias) {
// do a little trick to add bias in the logit function
var biasMult;
for (var i = 0;i < responses.length;i++) {
biasMult = Math.exp(bias[i]);
for (var j = 0;j < responses[i].length;j++) {
responses[i][j] = 1/(1+((1-responses[i][j])/(responses[i][j]*biasMult)));
}
}
return responses;
};
var splitArray = function(array, parts) {
var sp = [];
var al = array.length;
var splitlength = al/parts;
var ta = [];
for (var i = 0;i < al;i++) {
if (i % splitlength == 0) {
if (i != 0) {
sp.push(ta);
}
ta = [];
}
ta.push(array[i]);
}
sp.push(ta);
return sp;
};
var getOutput = function() {
// get data
var pixelValues = new Uint8Array(4*canvas.width*canvas.height);
gl.readPixels(0, 0, canvas.width, canvas.height, gl.RGBA, gl.UNSIGNED_BYTE, pixelValues);
return pixelValues;
};
var unpackToFloat = function(array) {
// convert packed floats to proper floats : see http://stackoverflow.com/questions/9882716/packing-float-into-vec4-how-does-this-code-work
var newArray = [];
var al = array.length;
for (var i = 0;i < al;i+=4) {
newArray[(i / 4) >> 0] = ((array[i]/(256*256*256*256))+(array[i+1]/(256*256*256))+(array[i+2]/(256*256))+(array[i+3]/256));
}
return newArray;
};
var normalizeFilterMatrix = function(response) {
// normalize responses to lie within [0,1]
var msize = response.length;
var max = 0;
var min = 1;
for (var i = 0;i < msize;i++) {
max = response[i] > max ? response[i] : max;
min = response[i] < min ? response[i] : min;
}
var dist = max-min;
if (dist == 0) {
//console.log('a patchresponse was monotone, causing normalization to fail. Leaving it unchanged.');
response = response.map(function() {return 1});
} else {
for (var i = 0;i < msize;i++) {
response[i] = (response[i]-min)/dist;
}
}
return response;
};
};
var mosseFilterResponses = function() {
var filters = [];
var responses = [];
var num_Patches = 0;
this.init = function(filter_input, numPatches, filterWidth, filterHeight) {
// load filters, make fft ready
for (var i = 0;i < numPatches;i++) {
var temp = {};
temp.width = filterWidth;
temp.height = filterHeight;
var filterLength = filterWidth*filterHeight;
var flar_fi0 = new Float64Array(filterLength);
var flar_fi1 = new Float64Array(filterLength);
for (var j = 0;j < filterLength;j++) {
flar_fi0[j] = filter_input[i][0][j];
flar_fi1[j] = filter_input[i][1][j];
}
temp.real = flar_fi0;
temp.imag = flar_fi1;
filters[i] = new mosse.mosseFilter();
filters[i].load(temp);
}
num_Patches = numPatches;
};
this.getResponses = function(patches) {
for (var i = 0;i < num_Patches;i++) {
responses[i] = filters[i].getResponse(patches[i]);
//responses[i] = logisticResponse(responses[i]);
responses[i] = normalizeFilterMatrix(responses[i]);
}
return responses;
};
var logisticResponse = function(response) {
// create probability by doing logistic transformation
var filter_size = response.length;
for (var j = 0;j < filter_size;j++) {
response[j] = 1.0/(1.0 + Math.exp(- (response[j]-1.0) ));
}
return response;
};
var normalizeFilterMatrix = function(response) {
// normalize responses to lie within [0,1]
var msize = response.length;
var max = 0;
var min = 1;
for (var i = 0;i < msize;i++) {
max = response[i] > max ? response[i] : max;
min = response[i] < min ? response[i] : min;
}
var dist = max-min;
if (dist == 0) {
console.log('a patchresponse was monotone, causing normalization to fail. Leaving it unchanged.');
response = response.map(function() {return 1});
} else {
for (var i = 0;i < msize;i++) {
response[i] = (response[i]-min)/dist;
}
}
return response;
};
};
var model_pca_20_svm = createCommonjsModule(function (module, exports) {
(function (global) {
'use strict';
var pModel = {
"scoring": {
"size": [20, 22],
"bias": -1.3971,
"coef": [-0.019443, -0.0084627, -0.005644, -0.0030633, 0.0050582, 0.0038672, 0.0073781, 0.0084088, 0.002108, 0.0088022, 0.0084634, 0.0091342, 0.0021678, 0.0057906, 0.010027, 0.010018, 0.011075, -0.00061696, -0.006084, -0.0094488, -0.012441, -0.003865, -0.0003105, 0.0031879, 0.0078183, 0.01096, 0.012101, 0.012289, 0.012872, 0.01342, 0.012863, 0.01257, 0.014429, 0.013339, 0.013248, 0.012998, 0.0080562, 0.001467, -0.011928, -0.0097909, -0.019951, -0.014602, -0.013175, -0.0060515, -0.0010407, 0.0054651, 0.010449, 0.014061, 0.015918, 0.016361, 0.021757, 0.017301, 0.014195, 0.012452, 0.010454, 0.0040883, -0.0014194, -0.0038499, -0.01077, -0.011758, -0.0046927, -0.0022134, -0.0039804, -0.012187, -0.011887, -0.0081984, 0.0028354, 0.007082, 0.012238, 0.016348, 0.02098, 0.017313, 0.011865, 0.0072371, 0.0028788, -0.0074673, -0.012293, -0.014834, -0.0083886, -0.0012772, -0.0043238, -0.00079996, -0.0090447, -0.015715, -0.016374, -0.018048, -0.012034, -0.007243, 0.00051252, 0.013092, 0.01857, 0.013099, 0.00085916, -0.0064555, -0.014574, -0.018222, -0.01806, -0.016666, -0.016743, -0.012862, -0.037409, -0.02683, -0.036693, -0.034788, -0.021885, -0.024485, -0.028069, -0.018632, 0.00033863, 0.015591, 0.021179, 0.015184, 0.0029429, -0.014375, -0.025568, -0.025718, -0.023219, -0.043064, -0.042245, -0.040561, -0.029282, -0.037097, -0.050209, -0.043175, -0.038799, -0.037913, -0.024597, -0.013392, 0.0026176, 0.01616, 0.02195, 0.018825, 0.0069274, -0.00671, -0.018259, -0.03115, -0.030987, -0.033628, -0.043437, -0.034535, -0.0027688, -0.0045493, -0.0029637, -0.0034067, -0.0058159, -0.0050003, -0.0052189, -0.0035094, 0.0048076, 0.01523, 0.017877, 0.01506, 0.0068301, -0.00074735, -0.0047129, -0.0020172, -0.0028734, -3.2165e-05, 0.0052576, 0.0043529, 0.016946, 0.015931, 0.013752, 0.01013, 0.0080481, 0.006654, 0.0068325, 0.0069577, 0.0040399, 0.011715, 0.01744, 0.014274, 0.0061486, 0.0064501, 0.0064155, 0.0087973, 0.0085371, 0.0087282, 0.011783, 0.016747, 0.022118, 0.020836, 0.018312, 0.015898, 0.017833, 0.015566, 0.014049, 0.0092416, 0.0081518, 0.011231, 0.012568, 0.012112, 0.0098382, 0.0073612, 0.0095541, 0.011728, 0.018126, 0.019469, 0.017399, 0.021144, 0.021132, 0.019499, 0.019593, 0.020281, 0.017451, 0.014159, 0.0062291, 0.0038367, 0.0070206, 0.0096561, 0.011406, 0.0073274, 0.0046726, 0.0052536, 0.00018758, 0.0081524, 0.01276, 0.0216, 0.023303, 0.023746, 0.018231, 0.020013, 0.019842, 0.0188, 0.010638, 0.00047498, -0.0071779, -0.0013493, 0.0015382, 0.0026092, 0.00054047, -0.00049664, -0.00046203, -0.005244, -0.0052152, -0.010003, 0.0014386, 0.012845, 0.020828, 0.023738, 0.015717, 0.016381, 0.014903, 0.007373, 0.0019356, -0.0062, -0.0091165, -0.008811, -0.01485, -0.0020888, 0.0052141, 0.0010527, -0.010322, -0.016208, -0.012439, -0.013087, -0.002797, 0.0023632, 0.011157, 0.018369, 0.0095224, 0.010552, 0.0065611, -0.0015315, -0.0032492, -0.003133, -0.00092774, -0.0020969, -0.0027526, 0.00094388, 5.9164e-05, -0.0017255, -0.0034421, -0.0045774, -0.0025305, -0.00038216, 0.00057079, 0.0031326, 0.0060238, 0.011585, 0.0016263, 0.0032288, 0.0012533, 0.00062748, 0.0023767, 0.0028182, 0.0023771, -0.0033403, -0.0048954, 0.0030747, 0.0062649, 0.0050231, 0.00044658, -0.0048271, -0.0040237, 0.0024988, 0.005458, 0.007288, 0.003601, 0.010569, -0.0045837, 0.00057936, 0.0010299, 0.0030015, 0.0036675, 0.0044718, 0.0068927, 0.0039124, 0.0071394, 0.010304, 0.012609, 0.0089589, 0.0086038, 0.0055408, 0.0046722, 0.0047921, 0.0058818, 0.0056047, 0.0054112, 0.0073265, -0.0027342, -0.0027247, -0.00349, -0.0079957, -0.0040761, -0.0020778, -0.0028479, -0.0039663, -0.0026161, 0.00092611, 0.0017427, 0.00055187, -0.0013723, -0.0045996, -0.0042015, -0.0054722, -0.0023417, -0.0025441, -0.0078778, 5.3403e-05, 0.0046873, 0.0021888, 0.0013036, -0.0013698, -0.015805, -0.016268, -0.018901, -0.017659, -0.011813, -0.0034436, -0.0023483, -0.0050111, -0.0050922, -0.015031, -0.020198, -0.021621, -0.018586, -0.018724, -0.0055723, 0.006448, 0.0026823, 0.006001, 0.0039986, 0.0050813, -0.0059114, -0.027746, -0.029251, -0.023067, -0.01721, -0.015963, -0.021075, -0.023667, -0.020006, -0.01
},
"path": {
"normal": [
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14],
[15, 16, 17, 18],
[19, 20, 21, 22],
[23, 63, 24, 64, 25, 65, 26, 66, 23],
[28, 67, 29, 68, 30, 69, 31, 70, 28],
[34, 35, 36, 42, 37, 43, 38, 39, 40],
[33, 41, 62],
[44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 44, 56, 57, 58, 50, 59, 60, 61, 44],
27, 32
],
"vertices": [
// jawline
[0,1,23,0],
[1,23,66,1],
[1,2,66,1],
[2,66,26,2],
[2,26,35,2],
[2,35,36,2],
[2,36,3,2],
[36,44,45,36],
[3,4,44,3],
[3,44,36,3],
[4,44,55,4],
[4,5,55,4],
[5,55,54,5],
[5,6,54,5],
[6,53,54,6],
[6,7,53,6],
[7,8,53,7],
[8,52,53,8],
[8,9,52,8],
[9,51,52,9],
[9,10,51,9],
[10,50,51,10],
[10,11,50,10],
[11,38,50,11],
[11,12,38,11],
[12,38,39,12],
[12,31,39,12],
[12,31,70,12],
[12,13,70,12],
[13,28,70,13],
[13,14,28,13],
// right eyebrow
[14,15,28,14],
[15,28,67,15],
[15,16,67,15],
[16,67,29,16],
[16,17,29,16],
[17,68,29,17],
[17,18,68,17],
[18,68,30,18],
[18,30,33,18],
// below eyes
[30,40,69,30],
[39,40,69,39],
[39,31,69,39],
[26,65,35,26],
[34,35,65,34],
[25,34,65,25],
// left eyebrow
[22,25,33,22],
[22,25,64,22],
[21,22,64,21],
[21,24,64,21],
[20,21,24,20],
[20,24,63,20],
[19,20,63,19],
[19,23,63,19],
[19,23,0,19],
// below nose
[36,45,46,36],
[36,42,46,36],
[42,37,46,42],
[37,46,47,37],
[46,37,47,46],
[37,47,48,37],
[38,48,49,38],
[37,43,48,37],
[43,38,48,43],
[38,49,50,38],
// nose region
[22,18,33,22],
[40,41,30,40],
[25,33,41,25],
[33,41,30,33],
[25,34,41,25],
[41,40,62,41],
[34,41,62,34],
[34,35,62,34],
[35,36,62,35],
[36,42,62,36],
[42,37,62,42],
[37,43,62,37],
[43,38,62,43],
[38,39,62,38],
[39,40,62,39],
// mouth
[44,45,61,44],
[45,46,61,45],
[46,47,61,46],
[47,61,60,47],
[47,59,60,47],
[47,48,59,47],
[48,49,59,48],
[49,50,59,49],
[50,51,58,50],
[51,52,58,51],
[52,57,58,52],
[52,53,57,52],
[53,54,57,53],
[54,56,57,54],
[54,55,56,54],
[44,55,56,44],
// left eye
[23,63,27,23],
[63,24,27,63],
[24,64,27,24],
[64,25,27,64],
[25,65,27,25],
[65,26,27,65],
[26,66,27,26],
[66,23,27,66],
// right eye
[28,67,32,28],
[67,29,32,67],
[29,68,32,29],
[68,30,32,68],
[30,69,32,30],
[69,31,32,69],
[31,70,32,31],
[28,32,70,28]
]
},
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"patchType": "SVM",
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[-0.0021943, 0.014673, 0.029772, 0.032615, -0.070295, 0.11259, -0.099269, 0.067977, -0.030442, -0.007886, 0.04335, -0.085123, -0.024236, 0.010448, 0.034458, -0.043729, -0.1042, 0.051653, -0.0020921, -0.13234],
[-0.004206, -0.036745, -0.07115, -0.055276, 0.11733, 0.12551, 0.026702, 0.098002, -0.032058, -0.004739, -0.10681, 0.00206, 0.030173, 0.081617, -0.060518, 0.076499, 0.010561, -0.048468, 0.0058355, -0.010407],
[-0.0044632, -0.00045295, 0.035713, 0.033808, -0.072124, 0.10251, -0.12265, 0.11181, -0.025714, -0.01886, 0.019241, -0.11285, -0.030121, 0.016747, 0.051984, -0.066147, -0.080512, 0.05543, -0.0091079, -0.1189],
[0.0019322, 0.029684, 0.074829, 0.061405, -0.11987, -0.12601, -0.036896, 0.077821, 0.038016, 0.0025971, 0.11579, -0.0007963, -0.013184, 0.098763, 0.04888, 0.099412, -0.014125, 0.04046, 0.0050852, -0.0021232],
[0.008396, -0.0058529, 0.042436, 0.073379, -0.029941, 0.087214, -0.11961, -0.12223, -0.079091, -0.079083, -0.017226, 0.11592, -0.085628, -0.018604, -0.004207, 0.068773, 0.14025, -0.081846, -0.0022209, 0.13007],
[0.014309, 0.014541, 0.05766, 0.046001, -0.08229, -0.08098, -0.026049, 0.079252, -0.024628, -0.025998, 0.070828, 0.013827, -0.0084475, 0.1061, -0.049312, 0.11165, 0.1053, 0.036343, 0.0098152, 0.10895],
[0.0013644, 0.0083593, 0.036153, 0.070909, -0.032101, 0.089224, -0.094876, -0.070176, -0.07845, -0.059264, 0.020187, 0.082243, -0.073071, -0.038616, -0.036995, 0.04263, 0.093939, -0.062508, -0.0011506, 0.10336],
[0.0060632, 0.020549, 0.053291, 0.04572, -0.079355, -0.087939, -0.0085831, 0.1014, -0.0058532, -0.0054453, 0.098074, 0.0093178, 0.0072056, 0.082593, -0.046292, 0.098917, 0.078372, 0.028835, 0.0086953, 0.092038],
[0.0019571, 0.013874, 0.027695, 0.030838, -0.067223, 0.11615, -0.099008, -0.072025, -0.030235, -0.0076776, 0.039519, 0.084822, -0.024539, -0.013711, 0.036309, 0.039865, -0.10737, 0.050557, 0.0017511, -0.13607],
[-0.004027, 0.036698, 0.072501, 0.056564, -0.12008, -0.12138, -0.031511, 0.093524, 0.031021, 0.0039927, 0.10749, 0.0065019, -0.031336, 0.080895, 0.062517, 0.079044, -0.013723, 0.050613, 0.0061896, 0.0057174],
[0.0046253, -0.0018994, 0.032883, 0.031605, -0.067448, 0.10737, -0.1215, -0.11558, -0.026956, -0.019032, 0.01502, 0.11268, -0.02891, -0.019948, 0.04956, 0.063084, -0.080034, 0.053478, 0.0088711, -0.11922]
],
"numEvalues": 20,
"eigenValues": [
448.26,
152.88,
77.079,
38.34,
27.754,
15.293,
13.086,
10.197,
7.2365,
6.5965,
5.7389,
5.6223,
4.6227,
4.3931,
3.9714,
3.5791,
3.4264,
3.0788,
2.6396,
2.4414
],
"numPtsPerSample": 71,
"nonRegularizedVectors": [0],
"meanShape": [
[25.011, 34.815],
[24.382, 45.627],
[25.831, 56.165],
[28.675, 66.696],
[33.598, 75.549],
[40.333, 82.562],
[48.359, 88],
[57.764, 89.783],
[67.091, 87.631],
[74.897, 81.881],
[81.35, 74.609],
[85.921, 65.568],
[88.348, 54.934],
[89.382, 44.347],
[88.327, 33.568],
[81.567, 27.445],
[76.62, 25.173],
[69.154, 25.747],
[63.337, 27.341],
[31.525, 28.43],
[36.379, 25.966],
[43.862, 26.245],
[49.736, 27.609],
[35.982, 35.443],
[41.743, 32.491],
[48.057, 35.383],
[41.828, 37.011],
[41.961, 34.611],
[77.389, 34.628],
[71.516, 31.905],
[65.321, 35.043],
[71.61, 36.424],
[71.382, 34.031],
[56.646, 33.009],
[50.194, 46.941],
[47.457, 51.771],
[50.073, 55.035],
[57.101, 56.145],
[64.081, 54.759],
[66.566, 51.395],
[63.641, 46.676],
[56.826, 42.172],
[52.142, 53.256],
[61.943, 53.063],
[45.091, 66.457],
[49.307, 63.536],
[54.022, 62.36],
[57.236, 62.972],
[60.423, 62.234],
[65.181, 63.223],
[69.509, 65.977],
[66.693, 69.861],
[62.797, 72.43],
[57.439, 73.279],
[52.051, 72.642],
[48.057, 70.228],
[51.313, 68.335],
[57.355, 69.042],
[63.365, 68.097],
[63.303, 65.106],
[57.283, 65.373],
[51.258, 65.343],
[56.997, 50.867],
[38.345, 33.38],
[45.432, 33.213],
[45.103, 36.388],
[38.617, 36.562],
[74.947, 32.659],
[67.858, 32.771],
[68.312, 35.931],
[74.8, 35.849]
]
},
"hints": {
"rightEye": [71.382, 34.031],
"leftEye": [41.961, 34.611],
"nose": [56.997, 50.867]
}
};
// CommonJS and Node.js module support
{
// Support Node.js specific `module.exports` (which can be a function)
if ('object' !== 'undefined' && module.exports) {
exports = module.exports = pModel;
}
// But always support CommonJS module 1.1.1 spec (`exports` cannot be a function)
exports.pModel = pModel;
}
})(commonjsGlobal);
});
// webgl setup tests
/*
* Test whether we can render to floating point texture
*/
var canRenderToFloatTexture = function(webGLContext) {
var renderingSupported = false;
var gl = webGLContext;
// setup the texture
var texture = gl.createTexture();
gl.bindTexture(gl.TEXTURE_2D, texture);
gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, 2, 2, 0, gl.RGBA, gl.FLOAT, null);
gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.NEAREST);
gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.NEAREST);
// setup the framebuffer
var framebuffer = gl.createFramebuffer();
gl.bindFramebuffer(gl.FRAMEBUFFER, framebuffer);
gl.framebufferTexture2D(
gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);
// check the framebuffer
var check = gl.checkFramebufferStatus(gl.FRAMEBUFFER);
if (check == gl.FRAMEBUFFER_COMPLETE) {
renderingSupported = true;
}
// cleanup
gl.deleteTexture(texture);
gl.deleteFramebuffer(framebuffer);
gl.bindTexture(gl.TEXTURE_2D, null);
gl.bindFramebuffer(gl.FRAMEBUFFER, null);
return renderingSupported
};
var version = "1.1.2";
/**
* clmtrackr library (https://www.github.com/auduno/clmtrackr/)
*
* Copyright (c) 2013, Audun Mathias Øygard
*
* Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
*/
//import { drawPatches } from './utils.debugging.js';
var DEFAULT_MODEL = model_pca_20_svm;
// polyfills
raf_1.polyfill();
if (!window.Promise) window.Promise = promise;
var clm = {
tracker : function(params) {
if (!params) params = {};
if (params.constantVelocity === undefined) params.constantVelocity = true;
if (params.searchWindow === undefined) params.searchWindow = 11;
if (params.useWebGL === undefined) params.useWebGL = true;
if (params.scoreThreshold === undefined) params.scoreThreshold = 0.5;
if (params.stopOnConvergence === undefined) params.stopOnConvergence = false;
if (params.weightPoints === undefined) params.weightPoints = undefined;
if (params.sharpenResponse === undefined) params.sharpenResponse = false;
if (params.faceDetection === undefined) params.faceDetection = {};
if (params.eventDispatcher === undefined) params.eventDispatcher = document;
if (params.maxIterationsPerAnimFrame === undefined) params.maxIterationsPerAnimFrame = 3;
/** @type {Number} Minimum convergence before firing `clmtrackrConverged` event. */
var convergenceThreshold = 0.5;
var numPatches, patchSize, numParameters, patchType;
var gaussianPD;
var eigenVectors, eigenValues;
var sketchCC, sketchW, sketchH, sketchCanvas;
var weights, model, biases;
var sobelInit = false;
var lbpInit = false;
var currentParameters = [];
var currentPositions = [];
var previousParameters = [];
var previousPositions = [];
var patches = [];
var responses = [];
var meanShape = [];
var responseMode = 'single';
var responseList = ['raw'];
var responseIndex = 0;
/*
It's possible to experiment with the sequence of variances used for the finding the maximum in the KDE.
This sequence is pretty arbitrary, but was found to be okay using some manual testing.
*/
var varianceSeq = [10,5,1];
//var varianceSeq = [3,1.5,0.75];
//var varianceSeq = [6,3,0.75];
var PDMVariance = 0.7;
var relaxation = 0.1;
var first = true;
var detectingFace = false;
var convergenceLimit = 0.01;
var searchWindow;
var modelWidth, modelHeight;
var halfSearchWindow, vecProbs, responsePixels;
if(typeof Float64Array !== 'undefined') {
var updatePosition = new Float64Array(2);
var vecpos = new Float64Array(2);
} else {
var updatePosition = new Array(2);
var vecpos = new Array(2);
}
var pw, pl, pdataLength;
var facecheck_count = 0;
var webglFi, svmFi, mosseCalc;
var scoringCanvas = document.createElement('canvas');
var scoringContext = scoringCanvas.getContext('2d');
var msxmin, msymin, msxmax, msymax;
var msmodelwidth, msmodelheight;
var scoringWeights, scoringBias;
var scoringHistory = [];
var meanscore = 0;
var runnerTimeout, runnerElement, runnerBox;
var pointWeights;
var halfPI = Math.PI/2;
var faceDetector;
/*
* load model data, initialize filters, etc.
*
* @param <Object> pdm model object
*/
this.init = function(pdmmodel) {
// default model is pca 20 svm model
if (pdmmodel === undefined) pdmmodel = DEFAULT_MODEL;
model = pdmmodel;
// load from model
patchType = model.patchModel.patchType;
numPatches = model.patchModel.numPatches;
patchSize = model.patchModel.patchSize[0];
if (patchType == 'MOSSE') {
searchWindow = patchSize;
} else {
searchWindow = params.searchWindow;
}
numParameters = model.shapeModel.numEvalues;
modelWidth = model.patchModel.canvasSize[0];
modelHeight = model.patchModel.canvasSize[1];
// set up canvas to work on
sketchCanvas = document.createElement('canvas');
sketchCC = sketchCanvas.getContext('2d');
sketchW = sketchCanvas.width = modelWidth + (searchWindow-1) + patchSize-1;
sketchH = sketchCanvas.height = modelHeight + (searchWindow-1) + patchSize-1;
// load eigenvectors
eigenVectors = numeric1_2_6.rep([numPatches*2,numParameters],0.0);
for (var i = 0;i < numPatches*2;i++) {
for (var j = 0;j < numParameters;j++) {
eigenVectors[i][j] = model.shapeModel.eigenVectors[i][j];
}
}
// load mean shape
for (var i = 0; i < numPatches;i++) {
meanShape[i] = [model.shapeModel.meanShape[i][0], model.shapeModel.meanShape[i][1]];
}
// get max and mins, width and height of meanshape
msxmax = msymax = 0;
msxmin = msymin = 1000000;
for (var i = 0;i < numPatches;i++) {
if (meanShape[i][0] < msxmin) msxmin = meanShape[i][0];
if (meanShape[i][1] < msymin) msymin = meanShape[i][1];
if (meanShape[i][0] > msxmax) msxmax = meanShape[i][0];
if (meanShape[i][1] > msymax) msymax = meanShape[i][1];
}
msmodelwidth = msxmax-msxmin;
msmodelheight = msymax-msymin;
// get scoringweights if they exist
if (model.scoring) {
scoringWeights = new Float64Array(model.scoring.coef);
scoringBias = model.scoring.bias;
scoringCanvas.width = model.scoring.size[0];
scoringCanvas.height = model.scoring.size[1];
}
// load eigenvalues
eigenValues = model.shapeModel.eigenValues;
weights = model.patchModel.weights;
biases = model.patchModel.bias;
// precalculate gaussianPriorDiagonal
gaussianPD = numeric1_2_6.rep([numParameters+4, numParameters+4],0);
// set values and append manual inverse
for (var i = 0;i < numParameters;i++) {
if (model.shapeModel.nonRegularizedVectors.indexOf(i) >= 0) {
gaussianPD[i+4][i+4] = 1/10000000;
} else {
gaussianPD[i+4][i+4] = 1/eigenValues[i];
}
}
for (var i = 0;i < numParameters+4;i++) {
currentParameters[i] = 0;
}
if (patchType == 'SVM') {
var webGLContext;
var webGLTestCanvas = document.createElement('canvas');
if (window.WebGLRenderingContext) {
webGLContext = webGLTestCanvas.getContext('webgl') || webGLTestCanvas.getContext('experimental-webgl');
if (!webGLContext || !webGLContext.getExtension('OES_texture_float')) {
webGLContext = null;
} else {
// test whether it's possible to render to float texture
if (!canRenderToFloatTexture(webGLContext)) {
webGLContext = null;
}
}
}
if (webGLContext && params.useWebGL && (typeof(webglFilter) !== 'undefined')) {
webglFi = new webglFilter();
try {
webglFi.init(weights, biases, numPatches, searchWindow+patchSize-1, searchWindow+patchSize-1, patchSize, patchSize);
if ('lbp' in weights) lbpInit = true;
if ('sobel' in weights) sobelInit = true;
}
catch(err) {
console.error(err);
alert('There was a problem setting up webGL programs, falling back to slightly slower javascript version. :(');
webglFi = undefined;
svmFi = new svmFilter();
svmFi.init(weights['raw'], biases['raw'], numPatches, patchSize, searchWindow);
}
} else if (typeof(svmFilter) !== 'undefined') {
// use fft convolution if no webGL is available
svmFi = new svmFilter();
svmFi.init(weights['raw'], biases['raw'], numPatches, patchSize, searchWindow);
} else {
throw new Error('Could not initiate filters, please make sure that svmfilter.js or svmfilter_conv_js.js is loaded.');
}
} else if (patchType == 'MOSSE') {
mosseCalc = new mosseFilterResponses();
mosseCalc.init(weights, numPatches, patchSize, patchSize);
}
if (patchType == 'SVM') {
pw = pl = patchSize+searchWindow-1;
} else {
pw = pl = searchWindow;
}
pdataLength = pw*pl;
halfSearchWindow = (searchWindow-1)/2;
responsePixels = searchWindow*searchWindow;
if(typeof Float64Array !== 'undefined') {
vecProbs = new Float64Array(responsePixels);
for (var i = 0;i < numPatches;i++) {
patches[i] = new Float64Array(pdataLength);
}
} else {
vecProbs = new Array(responsePixels);
for (var i = 0;i < numPatches;i++) {
patches[i] = new Array(pdataLength);
}
}
if (params.weightPoints) {
// weighting of points
pointWeights = [];
for (var i = 0;i < numPatches;i++) {
if (i in params.weightPoints) {
pointWeights[(i*2)] = params.weightPoints[i];
pointWeights[(i*2)+1] = params.weightPoints[i];
} else {
pointWeights[(i*2)] = 1;
pointWeights[(i*2)+1] = 1;
}
}
pointWeights = numeric1_2_6.diag(pointWeights);
}
faceDetector = new faceDetection(model, params.faceDetection);
};
/*
* starts the tracker to run on a regular interval
*/
this.start = function(element, box) {
// check if model is initalized, else return false
if (typeof(model) === 'undefined') {
console.log('tracker needs to be initalized before starting to track.');
return false;
}
//check if a runnerelement already exists, if not, use passed parameters
if (typeof(runnerElement) === 'undefined') {
runnerElement = element;
runnerBox = box;
}
faceDetector.init(element);
// start named timeout function
runnerTimeout = requestAnimationFrame(runnerFunction);
};
var runnerFunction = function() {
runnerTimeout = requestAnimationFrame(runnerFunction);
// schedule as many iterations as we can during each request
var startTime = (new Date()).getTime();
var run_counter = 0;
while ((((new Date()).getTime() - startTime) < 16)
&& run_counter < params.maxIterationsPerAnimFrame) {
var tracking = this.track(runnerElement, runnerBox);
if (!tracking) break;
run_counter++;
}
}.bind(this);
/*
* stop the running tracker
*/
this.stop = function() {
// stop the running tracker if any exists
cancelAnimationFrame(runnerTimeout);
};
/*
* element : canvas or video element
* TODO: should be able to take img element as well
*/
this.track = function(element, box) {
emitEvent('clmtrackrBeforeTrack', params.eventDispatcher);
var scaling, translateX, translateY, rotation;
var ptch, px, py;
if (first) {
if (!detectingFace) {
detectingFace = true;
// this returns a Promise
faceDetector.getInitialPosition(box)
.then(function (result) {
scaling = result[0];
rotation = result[1];
translateX = result[2];
translateY = result[3];
currentParameters[0] = (scaling*Math.cos(rotation))-1;
currentParameters[1] = (scaling*Math.sin(rotation));
currentParameters[2] = translateX;
currentParameters[3] = translateY;
currentPositions = calculatePositions(currentParameters, true);
first = false;
detectingFace = false;
})
.catch(function (error) {
// send an event on no face found
emitEvent('clmtrackrNotFound', params.eventDispatcher);
detectingFace = false;
});
}
return false;
} else {
facecheck_count += 1;
if (params.constantVelocity) {
// calculate where to get patches via constant velocity prediction
if (previousParameters.length >= 2) {
for (var i = 0;i < currentParameters.length;i++) {
currentParameters[i] = (relaxation)*previousParameters[1][i] + (1-relaxation)*((2*previousParameters[1][i]) - previousParameters[0][i]);
//currentParameters[i] = (3*previousParameters[2][i]) - (3*previousParameters[1][i]) + previousParameters[0][i];
}
}
}
// change translation, rotation and scale parameters
rotation = halfPI - Math.atan((currentParameters[0]+1)/currentParameters[1]);
if (rotation > halfPI) {
rotation -= Math.PI;
}
scaling = currentParameters[1] / Math.sin(rotation);
translateX = currentParameters[2];
translateY = currentParameters[3];
}
// copy canvas to a new dirty canvas
sketchCC.save();
// clear canvas
sketchCC.clearRect(0, 0, sketchW, sketchH);
sketchCC.scale(1/scaling, 1/scaling);
sketchCC.rotate(-rotation);
sketchCC.translate(-translateX, -translateY);
sketchCC.drawImage(element, 0, 0, element.width, element.height);
sketchCC.restore();
// get cropped images around new points based on model parameters (not scaled and translated)
var patchPositions = calculatePositions(currentParameters, false);
// check whether tracking is ok
if (scoringWeights && (facecheck_count % 10 == 0)) {
if (!checkTracking()) {
// reset all parameters
resetParameters();
// send event to signal that tracking was lost
emitEvent('clmtrackrLost', params.eventDispatcher);
return false;
}
}
var pdata, pmatrix, grayscaleColor;
for (var i = 0; i < numPatches; i++) {
px = patchPositions[i][0]-(pw/2);
py = patchPositions[i][1]-(pl/2);
ptch = sketchCC.getImageData(Math.round(px), Math.round(py), pw, pl);
pdata = ptch.data;
// convert to grayscale
pmatrix = patches[i];
for (var j = 0;j < pdataLength;j++) {
grayscaleColor = pdata[j*4]*0.3 + pdata[(j*4)+1]*0.59 + pdata[(j*4)+2]*0.11;
pmatrix[j] = grayscaleColor;
}
}
// draw weights for debugging
//drawPatches(sketchCC, weights, patchSize, patchPositions, function(x) {return x*2000+127});
// draw patches for debugging
//drawPatches(sketchCC, patches, pw, patchPositions, false, [27,32,44,50]);
if (patchType == 'SVM') {
if (typeof(webglFi) !== 'undefined') {
responses = getWebGLResponses(patches);
} else if (typeof(svmFi) !== 'undefined') {
responses = svmFi.getResponses(patches);
} else {
throw new Error('SVM-filters do not seem to be initiated properly.');
}
} else if (patchType == 'MOSSE') {
responses = mosseCalc.getResponses(patches);
}
// option to increase sharpness of responses
if (params.sharpenResponse) {
for (var i = 0;i < numPatches;i++) {
for (var j = 0;j < responses[i].length;j++) {
responses[i][j] = Math.pow(responses[i][j], params.sharpenResponse);
}
}
}
// draw responses for debugging
//drawPatches(sketchCC, responses, searchWindow, patchPositions, function(x) {return x*255});
// iterate until convergence or max 10, 20 iterations?:
var originalPositions = currentPositions;
var jac;
var meanshiftVectors = [];
for (var i = 0; i < varianceSeq.length; i++) {
// calculate jacobian
jac = createJacobian(currentParameters, eigenVectors);
// for debugging
//var debugMVs = [];
var opj0, opj1;
for (var j = 0;j < numPatches;j++) {
opj0 = originalPositions[j][0]-((searchWindow-1)*scaling/2);
opj1 = originalPositions[j][1]-((searchWindow-1)*scaling/2);
// calculate PI x gaussians
var vpsum = gpopt(searchWindow, currentPositions[j], updatePosition, vecProbs, responses, opj0, opj1, j, varianceSeq[i], scaling);
// calculate meanshift-vector
gpopt2(searchWindow, vecpos, updatePosition, vecProbs, vpsum, opj0, opj1, scaling);
//var debugMatrixMV = gpopt2(searchWindow, vecpos, updatePosition, vecProbs, vpsum, opj0, opj1);
meanshiftVectors[j] = [vecpos[0] - currentPositions[j][0], vecpos[1] - currentPositions[j][1]];
//debugMVs[j] = debugMatrixMV;
}
// draw meanshiftVector for debugging
//drawPatches(sketchCC, debugMVs, searchWindow, patchPositions, function(x) {return x*255*500});
var meanShiftVector = numeric1_2_6.rep([numPatches*2, 1],0.0);
for (var k = 0;k < numPatches;k++) {
meanShiftVector[k*2][0] = meanshiftVectors[k][0];
meanShiftVector[(k*2)+1][0] = meanshiftVectors[k][1];
}
// compute pdm parameter update
//var prior = numeric.mul(gaussianPD, PDMVariance);
var prior = numeric1_2_6.mul(gaussianPD, varianceSeq[i]);
var jtj;
if (params.weightPoints) {
jtj = numeric1_2_6.dot(numeric1_2_6.transpose(jac), numeric1_2_6.dot(pointWeights, jac));
} else {
jtj = numeric1_2_6.dot(numeric1_2_6.transpose(jac), jac);
}
var cpMatrix = numeric1_2_6.rep([numParameters+4, 1],0.0);
for (var l = 0;l < (numParameters+4);l++) {
cpMatrix[l][0] = currentParameters[l];
}
var priorP = numeric1_2_6.dot(prior, cpMatrix);
var jtv;
if (params.weightPoints) {
jtv = numeric1_2_6.dot(numeric1_2_6.transpose(jac), numeric1_2_6.dot(pointWeights, meanShiftVector));
} else {
jtv = numeric1_2_6.dot(numeric1_2_6.transpose(jac), meanShiftVector);
}
var paramUpdateLeft = numeric1_2_6.add(prior, jtj);
var paramUpdateRight = numeric1_2_6.sub(priorP, jtv);
var paramUpdate = numeric1_2_6.dot(numeric1_2_6.inv(paramUpdateLeft), paramUpdateRight);
//var paramUpdate = numeric.solve(paramUpdateLeft, paramUpdateRight, true);
var oldPositions = currentPositions;
// update estimated parameters
for (var k = 0;k < numParameters+4;k++) {
currentParameters[k] -= paramUpdate[k];
}
// clipping of parameters if they're too high
var clip;
for (var k = 0;k < numParameters;k++) {
clip = Math.abs(3*Math.sqrt(eigenValues[k]));
if (Math.abs(currentParameters[k+4]) > clip) {
if (currentParameters[k+4] > 0) {
currentParameters[k+4] = clip;
} else {
currentParameters[k+4] = -clip;
}
}
}
// update current coordinates
currentPositions = calculatePositions(currentParameters, true);
// check if converged
// calculate norm of parameterdifference
var positionNorm = 0;
var pnsq_x, pnsq_y;
for (var k = 0;k < currentPositions.length;k++) {
pnsq_x = (currentPositions[k][0]-oldPositions[k][0]);
pnsq_y = (currentPositions[k][1]-oldPositions[k][1]);
positionNorm += ((pnsq_x*pnsq_x) + (pnsq_y*pnsq_y));
}
// if norm < limit, then break
if (positionNorm < convergenceLimit) {
break;
}
}
if (params.constantVelocity) {
// add current parameter to array of previous parameters
previousParameters.push(currentParameters.slice());
if (previousParameters.length == 3) {
previousParameters.shift();
}
}
// store positions, for checking convergence
if (previousPositions.length == 10) {
previousPositions.shift();
}
previousPositions.push(currentPositions.slice(0));
// send an event on each iteration
emitEvent('clmtrackrIteration', params.eventDispatcher);
// we must get a score before we can say we've converged
if (scoringHistory.length >= 5 && this.getConvergence() < convergenceThreshold) {
if (params.stopOnConvergence) {
this.stop();
}
emitEvent('clmtrackrConverged', params.eventDispatcher);
}
// return new points
return currentPositions;
};
function resetParameters() {
first = true;
scoringHistory = [];
previousParameters = [];
currentPositions = [];
previousPositions = [];
for (var i = 0;i < currentParameters.length;i++) {
currentParameters[i] = 0;
}
}
/*
* reset tracking, so that track() will start a new detection
*/
this.reset = function() {
resetParameters();
runnerElement = undefined;
runnerBox = undefined;
};
/*
* draw model on given canvas
*/
this.draw = function(canvas, pv, path) {
// if no previous points, just draw in the middle of canvas
var params;
if (pv === undefined) {
params = currentParameters.slice(0);
} else {
params = pv.slice(0);
}
var cc = canvas.getContext('2d');
cc.fillStyle = 'rgb(200,200,200)';
cc.strokeStyle = 'rgb(130,255,50)';
//cc.lineWidth = 1;
var paths;
if (path === undefined) {
paths = model.path.normal;
} else {
paths = model.path[path];
}
for (var i = 0;i < paths.length;i++) {
if (typeof(paths[i]) == 'number') {
drawPoint(cc, paths[i], params);
} else {
drawPath(cc, paths[i], params);
}
}
};
/*
* get the score of the current model fit
* (based on svm of face according to current model)
*/
this.getScore = function() {
return meanscore;
};
/*
* calculate positions based on parameters
*/
this.calculatePositions = function(parameters) {
return calculatePositions(parameters, true);
};
/*
* get coordinates of current model fit
*/
this.getCurrentPosition = function() {
if (first) {
return false;
} else {
return currentPositions;
}
};
/*
* get parameters of current model fit
*/
this.getCurrentParameters = function() {
return currentParameters;
};
/*
* Get the average of recent model movements
* Used for checking whether model fit has converged
*/
this.getConvergence = function() {
if (previousPositions.length < 10) return 999999;
var prevX = 0.0;
var prevY = 0.0;
var currX = 0.0;
var currY = 0.0;
// average 5 previous positions
for (var i = 0;i < 5;i++) {
for (var j = 0;j < numPatches;j++) {
prevX += previousPositions[i][j][0];
prevY += previousPositions[i][j][1];
}
}
prevX /= 5;
prevY /= 5;
// average 5 positions before that
for (var i = 5;i < 10;i++) {
for (var j = 0;j < numPatches;j++) {
currX += previousPositions[i][j][0];
currY += previousPositions[i][j][1];
}
}
currX /= 5;
currY /= 5;
// calculate difference
var diffX = currX-prevX;
var diffY = currY-prevY;
var msavg = ((diffX*diffX) + (diffY*diffY));
msavg /= previousPositions.length;
return msavg;
};
/*
* Set response mode (only useful if webGL is available)
* mode : either "single", "blend" or "cycle"
* list : array of values "raw", "sobel", "lbp"
*/
this.setResponseMode = function(mode, list) {
// clmtrackr must be initialized with model first
if (typeof(model) === 'undefined') {
console.log('Clmtrackr has not been initialized with a model yet. No changes made.');
return;
}
// must check whether webGL or not
if (typeof(webglFi) === 'undefined') {
console.log('Responsemodes are only allowed when using webGL. In pure JS, only "raw" mode is available.');
return;
}
if (['single', 'blend', 'cycle'].indexOf(mode) < 0) {
console.log('Tried to set an unknown responsemode : "'+mode+'". No changes made.');
return;
}
if (!(list instanceof Array)) {
console.log('List in setResponseMode must be an array of strings! No changes made.');
return;
} else {
for (var i = 0;i < list.length;i++) {
if (['raw', 'sobel', 'lbp'].indexOf(list[i]) < 0) {
console.log('Unknown element in responsemode list : "'+list[i]+'". No changes made.');
}
// check whether filters are initialized
if (list[i] == 'sobel' && sobelInit == false) {
console.log('The sobel filters have not been initialized! No changes made.');
}
if (list[i] == 'lbp' && lbpInit == false) {
console.log('The LBP filters have not been initialized! No changes made.');
}
}
}
// reset index
responseIndex = 0;
responseMode = mode;
responseList = list;
};
var getWebGLResponsesType = function(type, patches) {
if (type == 'lbp') {
return webglFi.getLBPResponses(patches);
} else if (type == 'raw') {
return webglFi.getRawResponses(patches);
} else if (type == 'sobel') {
return webglFi.getSobelResponses(patches);
}
};
var getWebGLResponses = function(patches) {
if (responseMode == 'single') {
return getWebGLResponsesType(responseList[0], patches);
} else if (responseMode == 'cycle') {
var response = getWebGLResponsesType(responseList[responseIndex], patches);
responseIndex++;
if (responseIndex >= responseList.length) responseIndex = 0;
return response;
} else {
// blend
var responses = [];
for (var i = 0;i < responseList.length;i++) {
responses[i] = getWebGLResponsesType(responseList[i], patches);
}
var blendedResponses = [];
var searchWindowSize = searchWindow * searchWindow;
for (var i = 0;i < numPatches;i++) {
var response = Array(searchWindowSize);
for (var k = 0;k < searchWindowSize;k++) response[k] = 0;
for (var j = 0;j < responseList.length;j++) {
for (var k = 0;k < searchWindowSize;k++) {
response[k] += (responses[j][i][k]/responseList.length);
}
}
blendedResponses[i] = response;
}
return blendedResponses;
}
};
// generates the jacobian matrix used for optimization calculations
var createJacobian = function(parameters, eigenVectors) {
var jacobian = numeric1_2_6.rep([2*numPatches, numParameters+4],0.0);
var j0,j1;
for (var i = 0;i < numPatches;i ++) {
// 1
j0 = meanShape[i][0];
j1 = meanShape[i][1];
for (var p = 0;p < numParameters;p++) {
j0 += parameters[p+4]*eigenVectors[i*2][p];
j1 += parameters[p+4]*eigenVectors[(i*2)+1][p];
}
jacobian[i*2][0] = j0;
jacobian[(i*2)+1][0] = j1;
// 2
j0 = meanShape[i][1];
j1 = meanShape[i][0];
for (var p = 0;p < numParameters;p++) {
j0 += parameters[p+4]*eigenVectors[(i*2)+1][p];
j1 += parameters[p+4]*eigenVectors[i*2][p];
}
jacobian[i*2][1] = -j0;
jacobian[(i*2)+1][1] = j1;
// 3
jacobian[i*2][2] = 1;
jacobian[(i*2)+1][2] = 0;
// 4
jacobian[i*2][3] = 0;
jacobian[(i*2)+1][3] = 1;
// the rest
for (var j = 0;j < numParameters;j++) {
j0 = parameters[0]*eigenVectors[i*2][j] - parameters[1]*eigenVectors[(i*2)+1][j] + eigenVectors[i*2][j];
j1 = parameters[0]*eigenVectors[(i*2)+1][j] + parameters[1]*eigenVectors[i*2][j] + eigenVectors[(i*2)+1][j];
jacobian[i*2][j+4] = j0;
jacobian[(i*2)+1][j+4] = j1;
}
}
return jacobian;
};
// calculate positions from parameters
var calculatePositions = function(parameters, useTransforms) {
var x, y, a, b;
var numParameters = parameters.length;
var positions = [];
for (var i = 0;i < numPatches;i++) {
x = meanShape[i][0];
y = meanShape[i][1];
for (var j = 0;j < numParameters-4;j++) {
x += model.shapeModel.eigenVectors[(i*2)][j]*parameters[j+4];
y += model.shapeModel.eigenVectors[(i*2)+1][j]*parameters[j+4];
}
if (useTransforms) {
a = parameters[0]*x - parameters[1]*y + parameters[2];
b = parameters[0]*y + parameters[1]*x + parameters[3];
x += a;
y += b;
}
positions[i] = [x,y];
}
return positions;
};
// part one of meanshift calculation
var gpopt = function(responseWidth, currentPositionsj, updatePosition, vecProbs, responses, opj0, opj1, j, variance, scaling) {
var pos_idx = 0;
var vpsum = 0;
var dx, dy;
for (var k = 0;k < responseWidth;k++) {
updatePosition[1] = opj1+(k*scaling);
for (var l = 0;l < responseWidth;l++) {
updatePosition[0] = opj0+(l*scaling);
dx = currentPositionsj[0] - updatePosition[0];
dy = currentPositionsj[1] - updatePosition[1];
vecProbs[pos_idx] = responses[j][pos_idx] * Math.exp(-0.5*((dx*dx)+(dy*dy))/(variance*scaling));
vpsum += vecProbs[pos_idx];
pos_idx++;
}
}
return vpsum;
};
// part two of meanshift calculation
var gpopt2 = function(responseWidth, vecpos, updatePosition, vecProbs, vpsum, opj0, opj1, scaling) {
//for debugging
//var vecmatrix = [];
var pos_idx = 0;
var vecsum = 0;
vecpos[0] = 0;
vecpos[1] = 0;
for (var k = 0;k < responseWidth;k++) {
updatePosition[1] = opj1+(k*scaling);
for (var l = 0;l < responseWidth;l++) {
updatePosition[0] = opj0+(l*scaling);
vecsum = vecProbs[pos_idx]/vpsum;
//vecmatrix[k*responseWidth + l] = vecsum;
vecpos[0] += vecsum*updatePosition[0];
vecpos[1] += vecsum*updatePosition[1];
pos_idx++;
}
}
//return vecmatrix;
};
// calculate score of current fit
var checkTracking = function() {
var trackingImgW = 20;
var trackingImgH = 22;
scoringContext.drawImage(sketchCanvas, Math.round(msxmin+(msmodelwidth/4.5)), Math.round(msymin-(msmodelheight/12)), Math.round(msmodelwidth-(msmodelwidth*2/4.5)), Math.round(msmodelheight-(msmodelheight/12)), 0, 0, trackingImgW, trackingImgH);
// getImageData of canvas
var imgData = scoringContext.getImageData(0,0,trackingImgW,trackingImgH);
// convert data to grayscale
var trackingImgSize = trackingImgW * trackingImgH;
var scoringData = new Array(trackingImgSize);
var scdata = imgData.data;
var scmax = 0;
for (var i = 0;i < trackingImgSize;i++) {
scoringData[i] = scdata[i*4]*0.3 + scdata[(i*4)+1]*0.59 + scdata[(i*4)+2]*0.11;
scoringData[i] = Math.log(scoringData[i]+1);
if (scoringData[i] > scmax) scmax = scoringData[i];
}
if (scmax > 0) {
// normalize & multiply by svmFilter
var mean = 0;
for (var i = 0;i < trackingImgSize;i++) {
mean += scoringData[i];
}
mean /= trackingImgSize;
var sd = 0;
for (var i = 0;i < trackingImgSize;i++) {
sd += (scoringData[i]-mean)*(scoringData[i]-mean);
}
sd /= trackingImgSize;
sd = Math.sqrt(sd);
var score = 0;
for (var i = 0;i < trackingImgSize;i++) {
scoringData[i] = (scoringData[i]-mean)/sd;
score += (scoringData[i])*scoringWeights[i];
}
score += scoringBias;
score = 1/(1+Math.exp(-score));
if (scoringHistory.length == 5) {
scoringHistory.shift();
}
scoringHistory.push(score);
if (scoringHistory.length > 4) {
// get average
meanscore = 0;
for (var i = 0;i < 5;i++) {
meanscore += scoringHistory[i];
}
meanscore /= 5;
// if below threshold, then reset (return false)
if (meanscore < params.scoreThreshold) return false;
}
}
return true;
};
// draw a parametrized line on a canvas
var drawPath = function(canvasContext, path, dp) {
canvasContext.beginPath();
var i, x, y, a, b;
for (var p = 0;p < path.length;p++) {
i = path[p]*2;
x = meanShape[i/2][0];
y = meanShape[i/2][1];
for (var j = 0;j < numParameters;j++) {
x += model.shapeModel.eigenVectors[i][j]*dp[j+4];
y += model.shapeModel.eigenVectors[i+1][j]*dp[j+4];
}
a = dp[0]*x - dp[1]*y + dp[2];
b = dp[0]*y + dp[1]*x + dp[3];
x += a;
y += b;
if (i == 0) {
canvasContext.moveTo(x,y);
} else {
canvasContext.lineTo(x,y);
}
}
canvasContext.moveTo(0,0);
canvasContext.closePath();
canvasContext.stroke();
};
// draw a point on a canvas
function drawPoint(canvasContext, point, dp) {
var i, x, y, a, b;
i = point*2;
x = meanShape[i/2][0];
y = meanShape[i/2][1];
for (var j = 0;j < numParameters;j++) {
x += model.shapeModel.eigenVectors[i][j]*dp[j+4];
y += model.shapeModel.eigenVectors[i+1][j]*dp[j+4];
}
a = dp[0]*x - dp[1]*y + dp[2];
b = dp[0]*y + dp[1]*x + dp[3];
x += a;
y += b;
canvasContext.beginPath();
canvasContext.arc(x, y, 1, 0, Math.PI*2, true);
canvasContext.closePath();
canvasContext.fill();
}
return true;
},
version : version
};
return clm;
})));