diff --git a/ethertools/dac3.py b/ethertools/dac3.py
new file mode 100755
index 0000000..325672b
--- /dev/null
+++ b/ethertools/dac3.py
@@ -0,0 +1,235 @@
+# j4cDAC test code
+#
+# Copyright 2011 Jacob Potter
+#
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation, version 3.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with this program. If not, see .
+
+import socket
+import time
+import struct
+
+def pack_point(x, y, r, g, b, i = -1, u1 = 0, u2 = 0, flags = 0):
+ """Pack some color values into a struct dac_point.
+
+ Values must be specified for x, y, r, g, and b. If a value is not
+ passed in for the other fields, i will default to max(r, g, b); the
+ rest default to zero.
+ """
+ #print(r,g,b)
+ if i < 0:
+ i = max(r, g, b)
+
+ return struct.pack(" len(self.buf):
+
+ buffy = self.conn.recv(4096)
+ #print(buffy)
+
+ self.buf += buffy
+
+ obuf = self.buf
+ self.buf = obuf[l:]
+ return obuf[:l]
+
+ def readresp(self, cmd):
+ """Read a response from the DAC."""
+ data = self.read(22)
+ response = data[0]
+ cmdR = chr(data[1])
+ status = Status(data[2:])
+
+ status.dump()
+
+ if cmdR != cmd:
+ raise ProtocolError("expected resp for %r, got %r"
+ % (cmd, cmdR))
+ if response != ord('a'):
+ raise ProtocolError("expected ACK, got %r"
+ % (response, ))
+
+ self.last_status = status
+ return status
+
+ def __init__(self, host, port = 7765):
+ """Connect to the DAC over TCP."""
+ conn = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
+ conn.connect((host, port))
+ conn.settimeout(1)
+ self.conn = conn
+ self.buf = b''
+
+ # Read the "hello" message
+ first_status = self.readresp("?")
+ first_status.dump()
+
+ '''
+ self.conn.sendall('v')
+ self.firmware_string = self.read(32).replace("\x00", " ").strip()
+ print "Firmware: %s" % (self.firmware_string, )
+ '''
+
+ def begin(self, lwm, rate):
+ cmd = struct.pack("
+
+
+
+ CFBundleDevelopmentRegion
+ English
+ CFBundleDocumentTypes
+
+
+ CFBundleTypeOSTypes
+
+ ****
+ fold
+ disk
+
+ CFBundleTypeRole
+ Viewer
+
+
+ CFBundleExecutable
+ sitter
+ CFBundleIconFile
+ PythonApplet.icns
+ CFBundleIdentifier
+ sitter
+ CFBundleInfoDictionaryVersion
+ 6.0
+ CFBundleName
+ sitter
+ CFBundlePackageType
+ APPL
+ CFBundleSignature
+ ????
+
+
diff --git a/ethertools/sitter.app/Contents/MacOS/Python b/ethertools/sitter.app/Contents/MacOS/Python
new file mode 100755
index 0000000..1cfc9df
Binary files /dev/null and b/ethertools/sitter.app/Contents/MacOS/Python differ
diff --git a/ethertools/sitter.app/Contents/MacOS/sitter b/ethertools/sitter.app/Contents/MacOS/sitter
new file mode 100755
index 0000000..56c2a1d
--- /dev/null
+++ b/ethertools/sitter.app/Contents/MacOS/sitter
@@ -0,0 +1,23 @@
+#!/System/Library/Frameworks/Python.framework/Versions/2.5/Resources/Python.app/Contents/MacOS/Python
+
+import sys, os
+execdir = os.path.dirname(sys.argv[0])
+executable = os.path.join(execdir, "Python")
+resdir = os.path.join(os.path.dirname(execdir), "Resources")
+libdir = os.path.join(os.path.dirname(execdir), "Frameworks")
+mainprogram = os.path.join(resdir, "__argvemulator_sitter.py")
+
+sys.argv.insert(1, mainprogram)
+if 0 or 0:
+ os.environ["PYTHONPATH"] = resdir
+ if 0:
+ os.environ["PYTHONHOME"] = resdir
+else:
+ pypath = os.getenv("PYTHONPATH", "")
+ if pypath:
+ pypath = ":" + pypath
+ os.environ["PYTHONPATH"] = resdir + pypath
+os.environ["PYTHONEXECUTABLE"] = executable
+os.environ["DYLD_LIBRARY_PATH"] = libdir
+os.environ["DYLD_FRAMEWORK_PATH"] = libdir
+os.execve(executable, sys.argv, os.environ)
diff --git a/ethertools/sitter.app/Contents/PkgInfo b/ethertools/sitter.app/Contents/PkgInfo
new file mode 100755
index 0000000..bd04210
--- /dev/null
+++ b/ethertools/sitter.app/Contents/PkgInfo
@@ -0,0 +1 @@
+APPL????
\ No newline at end of file
diff --git a/ethertools/sitter.app/Contents/Resources/PythonApplet.icns b/ethertools/sitter.app/Contents/Resources/PythonApplet.icns
new file mode 100755
index 0000000..c8aad9f
Binary files /dev/null and b/ethertools/sitter.app/Contents/Resources/PythonApplet.icns differ
diff --git a/ethertools/sitter.app/Contents/Resources/__argvemulator_sitter.py b/ethertools/sitter.app/Contents/Resources/__argvemulator_sitter.py
new file mode 100755
index 0000000..4f0c146
--- /dev/null
+++ b/ethertools/sitter.app/Contents/Resources/__argvemulator_sitter.py
@@ -0,0 +1,4 @@
+import argvemulator, os
+
+argvemulator.ArgvCollector().mainloop()
+execfile(os.path.join(os.path.split(__file__)[0], "sitter.py"))
diff --git a/ethertools/sitter.app/Contents/Resources/sitter.py b/ethertools/sitter.app/Contents/Resources/sitter.py
new file mode 100755
index 0000000..a1aad5e
--- /dev/null
+++ b/ethertools/sitter.app/Contents/Resources/sitter.py
@@ -0,0 +1,414 @@
+#!/usr/bin/python
+# j4cDAC "sitter"
+#
+# Copyright 2012 Jacob Potter
+#
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation, version 3.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with this program. If not, see .
+
+import socket
+import time
+import struct
+
+def pack_point(x, y, r, g, b, i = -1, u1 = 0, u2 = 0, flags = 0):
+ """Pack some color values into a struct dac_point.
+
+ Values must be specified for x, y, r, g, and b. If a value is not
+ passed in for the other fields, i will default to max(r, g, b); the
+ rest default to zero.
+ """
+
+ if i < 0:
+ i = max(r, g, b)
+
+ return struct.pack(" len(self.buf):
+ self.buf += self.conn.recv(4096)
+
+ obuf = self.buf
+ self.buf = obuf[l:]
+ return obuf[:l]
+
+ def readresp(self, cmd):
+ """Read a response from the DAC."""
+ data = self.read(22)
+ response = data[0]
+ cmdR = data[1]
+ status = Status(data[2:])
+
+# status.dump()
+
+ if cmdR != cmd:
+ raise ProtocolError("expected resp for %r, got %r"
+ % (cmd, cmdR))
+
+ if response != "a":
+ raise ProtocolError("expected ACK, got %r"
+ % (response, ))
+
+ self.last_status = status
+ return status
+
+ def __init__(self, macstr, bp):
+ self.macstr = macstr
+ self.firmware_string = "-"
+ self.got_broadcast(bp)
+
+ try:
+ t1 = time.time()
+ self.connect(self.last_broadcast.ip[0])
+ t = time.time() - t1
+ self.conn_status = "ok (%d ms)" % (t * 500)
+
+ if self.last_broadcast.sw_rev < 2:
+ self.firmware_string = "(old)"
+ else:
+ self.conn.sendall('v')
+ self.firmware_string = self.read(32).replace("\x00", " ").strip()
+ except e:
+ self.conn_status = str(e)
+
+ def connect(self, host, port = 7765):
+ """Connect to the DAC over TCP."""
+ conn = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
+ conn.settimeout(0.2)
+ conn.connect((host, port))
+ self.conn = conn
+ self.buf = ""
+
+ # Read the "hello" message
+ first_status = self.readresp("?")
+ first_status.dump()
+
+
+
+ def begin(self, lwm, rate):
+ cmd = struct.pack(">", self.update_selection)
+
+ def update_selection(self, lb=None):
+ if self.dac_display:
+ try:
+ dac_obj = self.dac_list[self.index(ACTIVE)]
+ except:
+ return
+ self.dac_display.display_dac(dac_obj)
+
+ def got_packet(self, bp):
+ macstr = bp.macstr()
+ if macstr not in self.dac_macstr_map:
+ new_dac = DAC(macstr, bp)
+ self.insert(END, macstr[6:])
+ self.dac_list.append(new_dac)
+ self.dac_macstr_map[macstr] = new_dac
+ dac_obj = new_dac
+ else:
+ dac_obj = self.dac_macstr_map[macstr]
+ dac_obj.got_broadcast(bp)
+
+ if len(self.dac_list) == 1:
+ self.selection_set(0)
+ self.update_selection()
+
+ def check_on_dac():
+ if time.time() - dac_obj.last_broadcast_time < 2:
+ return
+
+ idx = self.dac_list.index(dac_obj)
+ self.dac_list.remove(dac_obj)
+ del self.dac_macstr_map[macstr]
+ self.delete(idx)
+ self.dac_display.display_none()
+
+
+ self.after(2000, check_on_dac)
+
+
+
+# Set up the basic window
+root = Tk()
+root.title("Ether Dream")
+root.resizable(FALSE, FALSE)
+frame = Frame(root)
+frame.grid()
+
+disp = DacDisplay(root)
+disp.grid(row=0, column=1, padx=5, pady=5)
+tracker = DacTracker(root, height=22)
+tracker.grid(row=0, column=0, padx=5, pady=5)
+tracker.dac_display = disp
+
+# Set up queue checker
+packet_queue = Queue.Queue()
+def queue_check():
+ try:
+ while True:
+ data, addr = packet_queue.get_nowait()
+ tracker.got_packet(BroadcastPacket(data, addr))
+ except Queue.Empty:
+ root.after(100, queue_check)
+
+root.after(100, queue_check)
+
+# Set up listening socket and thread
+s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
+s.bind(("0.0.0.0", 7654))
+def socket_thread():
+ while True:
+ packet_queue.put(s.recvfrom(1024))
+thread.start_new(socket_thread, ())
+
+root.mainloop()
diff --git a/ethertools/sitter.py b/ethertools/sitter.py
new file mode 100755
index 0000000..677971b
--- /dev/null
+++ b/ethertools/sitter.py
@@ -0,0 +1,414 @@
+#!/usr/bin/python
+# j4cDAC "sitter"
+#
+# Copyright 2012 Jacob Potter
+#
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation, version 3.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with this program. If not, see .
+
+import socket
+import time
+import struct
+
+def pack_point(x, y, r, g, b, i = -1, u1 = 0, u2 = 0, flags = 0):
+ """Pack some color values into a struct dac_point.
+
+ Values must be specified for x, y, r, g, and b. If a value is not
+ passed in for the other fields, i will default to max(r, g, b); the
+ rest default to zero.
+ """
+
+ if i < 0:
+ i = max(r, g, b)
+
+ return struct.pack(" len(self.buf):
+ self.buf += self.conn.recv(4096)
+
+ obuf = self.buf
+ self.buf = obuf[l:]
+ return obuf[:l]
+
+ def readresp(self, cmd):
+ """Read a response from the DAC."""
+ data = self.read(22)
+ response = data[0]
+ cmdR = data[1]
+ status = Status(data[2:])
+
+# status.dump()
+
+ if cmdR != cmd:
+ raise ProtocolError("expected resp for %r, got %r"
+ % (cmd, cmdR))
+
+ if response != "a":
+ raise ProtocolError("expected ACK, got %r"
+ % (response, ))
+
+ self.last_status = status
+ return status
+
+ def __init__(self, macstr, bp):
+ self.macstr = macstr
+ self.firmware_string = "-"
+ self.got_broadcast(bp)
+
+ try:
+ t1 = time.time()
+ self.connect(self.last_broadcast.ip[0])
+ t = time.time() - t1
+ self.conn_status = "ok (%d ms)" % (t * 500)
+
+ if self.last_broadcast.sw_rev < 2:
+ self.firmware_string = "(old)"
+ else:
+ self.conn.sendall('v')
+ self.firmware_string = self.read(32).replace("\x00", " ").strip()
+ except Exception, e:
+ self.conn_status = str(e)
+
+ def connect(self, host, port = 7765):
+ """Connect to the DAC over TCP."""
+ conn = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
+ conn.settimeout(0.2)
+ conn.connect((host, port))
+ self.conn = conn
+ self.buf = ""
+
+ # Read the "hello" message
+ first_status = self.readresp("?")
+ first_status.dump()
+
+
+
+ def begin(self, lwm, rate):
+ cmd = struct.pack(">", self.update_selection)
+
+ def update_selection(self, lb=None):
+ if self.dac_display:
+ try:
+ dac_obj = self.dac_list[self.index(ACTIVE)]
+ except:
+ return
+ self.dac_display.display_dac(dac_obj)
+
+ def got_packet(self, bp):
+ macstr = bp.macstr()
+ if macstr not in self.dac_macstr_map:
+ new_dac = DAC(macstr, bp)
+ self.insert(END, macstr[6:])
+ self.dac_list.append(new_dac)
+ self.dac_macstr_map[macstr] = new_dac
+ dac_obj = new_dac
+ else:
+ dac_obj = self.dac_macstr_map[macstr]
+ dac_obj.got_broadcast(bp)
+
+ if len(self.dac_list) == 1:
+ self.selection_set(0)
+ self.update_selection()
+
+ def check_on_dac():
+ if time.time() - dac_obj.last_broadcast_time < 2:
+ return
+
+ idx = self.dac_list.index(dac_obj)
+ self.dac_list.remove(dac_obj)
+ del self.dac_macstr_map[macstr]
+ self.delete(idx)
+ self.dac_display.display_none()
+
+
+ self.after(2000, check_on_dac)
+
+
+
+# Set up the basic window
+root = Tk()
+root.title("Ether Dream")
+root.resizable(FALSE, FALSE)
+frame = Frame(root)
+frame.grid()
+
+disp = DacDisplay(root)
+disp.grid(row=0, column=1, padx=5, pady=5)
+tracker = DacTracker(root, height=22)
+tracker.grid(row=0, column=0, padx=5, pady=5)
+tracker.dac_display = disp
+
+# Set up queue checker
+packet_queue = Queue.Queue()
+def queue_check():
+ try:
+ while True:
+ data, addr = packet_queue.get_nowait()
+ tracker.got_packet(BroadcastPacket(data, addr))
+ except Queue.Empty:
+ root.after(100, queue_check)
+
+root.after(100, queue_check)
+
+# Set up listening socket and thread
+s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
+s.bind(("0.0.0.0", 7654))
+def socket_thread():
+ while True:
+ packet_queue.put(s.recvfrom(1024))
+thread.start_new(socket_thread, ())
+
+root.mainloop()
diff --git a/ethertools/talk3.py b/ethertools/talk3.py
new file mode 100755
index 0000000..183e613
--- /dev/null
+++ b/ethertools/talk3.py
@@ -0,0 +1,95 @@
+#!/usr/bin/env python
+#
+# j4cDAC test code
+#
+# Copyright 2011 Jacob Potter
+#
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation, version 3.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with this program. If not, see .
+
+import dac3 as dac
+
+class SquarePointStream(object):
+ '''
+ def produce(self):
+ pmax = 15600
+ pstep = 100
+ cmax = 65535
+ while True:
+ for x in xrange(-pmax, pmax, pstep):
+ yield (x, pmax, cmax, 0, 0, cmax)
+ for y in xrange(pmax, -pmax, -pstep):
+ yield (pmax, y, 0, cmax, 0, cmax)
+ for x in xrange(pmax, -pmax, -pstep):
+ yield (x, -pmax, 0, 0, cmax, cmax)
+ for y in xrange(-pmax, pmax, pstep):
+ yield (-pmax, y, cmax, cmax, cmax, cmax)
+ '''
+
+ def produce(self):
+
+ pmax = 15600
+ pstep = 100
+ Cmax = 65535
+
+
+ while True:
+
+ print("Cmax:",Cmax)
+
+ for x in range(-pmax, pmax, pstep):
+
+ yield (x, pmax, Cmax, 0, 0) # pure Red
+ #yield (x, pmax, 0, Cmax, 0) # pure Green
+ #yield (x, pmax, 0, 0, Cmax) # pure Blue
+ #yield (x, pmax, Cmax, Cmax, Cmax) # pure White
+
+
+ for y in range(pmax, -pmax, -pstep):
+
+ #yield (pmax, y, Cmax, 0, 0) # pure Red
+ yield (pmax, y, 0, Cmax, 0) # pure Green
+ #yield (pmax, y, 0, 0, Cmax) # pure Blue
+ #yield (pmax, y, Cmax, Cmax, Cmax) # pure White
+
+ for x in range(pmax, -pmax, -pstep):
+ #yield (x, -pmax, Cmax, 0, 0) # pure Red
+ #yield (x, -pmax, 0, Cmax, 0) # pure Green
+ yield (x, -pmax, 0, 0, Cmax) # pure Blue
+ #yield (x, -pmax, Cmax, Cmax, Cmax) # pure White
+
+
+ for y in range(-pmax, pmax, pstep):
+ #yield (-pmax, y, Cmax, 0, 0) # pure Red
+ #yield (-pmax, y,0, Cmax, 0) # pure Green
+ #yield (-pmax, y, 0, 0, Cmax) # pure Blue
+ yield (-pmax, y, Cmax, Cmax, Cmax) # pure White
+
+
+
+
+ def __init__(self):
+ self.stream = self.produce()
+
+ def read(self, n):
+ return [next(self.stream) for i in range(n)]
+
+class NullPointStream(object):
+ def read(self, n):
+ return [(0, 0, 0, 0, 0)] * n
+
+#dac.find_dac()
+
+d = dac.DAC(dac.find_first_dac())
+#d = dac.DAC("192.168.1.43")
+
+d.play_stream(SquarePointStream())
diff --git a/ethertools/watch.py b/ethertools/watch.py
new file mode 100755
index 0000000..9fff745
--- /dev/null
+++ b/ethertools/watch.py
@@ -0,0 +1,21 @@
+#!/usr/bin/env python
+#
+# j4cDAC test code
+#
+# Copyright 2011 Jacob Potter
+#
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation, version 3.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with this program. If not, see .
+
+import dac
+
+dac.find_dac()
diff --git a/libs3/lj23layers.sync-conflict-20200803-100618-TAXKCAL.py b/libs3/lj23layers.sync-conflict-20200803-100618-TAXKCAL.py
deleted file mode 100644
index fdfce35..0000000
--- a/libs3/lj23layers.sync-conflict-20200803-100618-TAXKCAL.py
+++ /dev/null
@@ -1,986 +0,0 @@
-#!/usr/bin/python3
-# -*- coding: utf-8 -*-
-# -*- mode: Python -*-
-
-'''
-
-lj23layers v0.7.6 for LJ v0.8+
-
-LJ functions (API) for python plugins/clients
-
-"layers" version :
-- "PL" has been replaced by "layer"
-- "Client"
-
-Each program using LJ should declare itself by call lj23layers Config :
-
-Config(redisIP, client number, name)
-
-
-Basic Draw :
-
-- PolyLineOneColor, rPolyLineOneColor, LineTo, Line
-- PolyLineRGB, rPolyLineRGB, LineRGBTo, LineRGB
-- rgb2int(r,g,b)
-- Drawlayer (point list number) : once you stacked all wanted elements, like 2 polylines, send them to lasers.
-- DrawDests(): Draw all requested destinations for each layer .
-
-High level draw :
-
-- Text(word, integercolor, layer , xpos, ypos, resize, rotx, roty, rotz) : Display a word
-- TextRGB(word, red, green, blue, ...)
-- Embeded font1
-
-
-Laser objects (name and convenient group of parameters for one or several point lists)
-
-- RelativeObject
-- FixedObject
-
-"Destinations" : Tell for given Layer a scene/Laser ("destination").
-Each Layer can have different destination (i.e to display same stuff on different laser)
-
-
-OSC and plugins functions :
-
-SendLJ(adress,message) : LJ remote control. See commands.py
-SendResol(address,message): Send OSC message to Resolume.
-WebStatus(message) : display message on webui
-
-Ljscene(client): Change scene number in redis keys
-Ljlayer(layer): Change layer number in redis keys = laser target.
-ClosePlugin(name): Send UI closing info of given plugin
-
-OSCstart(): Start the OSC system.
-OSCframe(): Handle incoming OSC message. Calling the right callback
-OSCstop(): Properly close the OSC system
-OSCping(): /ping Answer to LJ pings by sending /pong name
-OSCquit(): /quit Exit calling script using name in terminal
-OSCadddest(): layer , scene, laser Add a destination
-OSCdeldest(): layer , scene, lasers delete a destination
-OSCobj(): /name/obj objectname attribute value for automation
-OSCvar(): /name/var variablename value for automation
-
-
-Joystick management is removed. Get it back in todolist
-
-setup_controls(joystick)
-
-XboxController : getLeftHori, getLeftVert, getRightHori, getRightVert, getLeftTrigger, getRightTrigger
-Ps3Controller : getLeftHori, getLeftVert, getRightHori, getRightVert, getLeftTrigger, getRightTrigger, getUp, getDown, getLeft, getRight, getFire1, getFire2(self):
-MySaitekController : getLeftHori,getLeftVert, getRightHori,getRightVert, getLeftTrigger,getRightTrigger
-MyThrustController : getLeftHori, getLeftVert, getRightHori, getRightVert, getLeftTrigger, getRightTrigger
-CSLController : getLeftHori,getLeftVert,getRightHori, getRightVert,getLeftTrigger,getRightTrigger,getFire1,getFire2
-my USB Joystick : getUp,getDown,getLeft,getRight,etLeftTrigger, getRightTrigger,getFire1, getFire2
-
-
-
-Class management manuals:
-
-https://stackoverflow.com/questions/739882/iterating-over-object-instances-of-a-given-class-in-python
-https://stackoverflow.com/questions/8628123/counting-instances-of-a-class
-http://effbot.org/pyfaq/how-do-i-get-a-list-of-all-instances-of-a-given-class.htm
-
-
-LICENCE : CC
-Sam Neurohack
-
-'''
-
-import math
-import redis
-import sys
-import weakref
-import struct
-import numpy as np
-import gstt
-from multiprocessing import Process, Queue, TimeoutError
-
-is_py2 = sys.version[0] == '2'
-if is_py2:
- from OSC import OSCServer, OSCClient, OSCMessage
- #print ("Importing lj23 and OSC from libs...")
-else:
- from OSC3 import OSCServer, OSCClient, OSCMessage
- #print ("Importing lj23 and OSC3 from libs...")
-
-
-#redisIP = '127.0.0.1'
-#r = redis.StrictRedis(host=redisIP, port=6379, db=0)
-
-ClientNumber = 0
-name = "noname"
-oscrun = True
-point_list = []
-layers = [[],[],[],[],[],[],[],[],[],[]]
-
-fft3Groups = [-1,-1,-1,-1]
-
-Dests = dict()
-
-oscIPresol = "127.0.0.1"
-oscPORTresol = 7000
-
-# 3D to 2D projection parameters
-fov = 256
-viewer_distance = 2.2
-
-
-'''
-
- Laser "objects"
-
-
- set a name and convenient group of parameters for one or several point lists
-
- RelativeObject is for point lists around 0,0 with builtin move/rotation.
-
- How to init with object color, xpos,... :
- osciObj = lj.RelativeObject('osciObj', True, 255, [], white, red, green,blue,0 , False, centerX , centerY , 1 , Xrot , Yrot , Zrot)
- How to use in drawing functions : you're free to use 0, some or all of any laserobject attributes
- - draw one or several pointlists with 'A' laserobject color and 'B' laserobject xpos ypos ?
- - Change color of 'main' object and all other objects using it will change also
- how to change attribute :
- osciObj.resize = 2 or /pluginame/change 'OsciObj' 'resize' 2
-
-'''
-
-class RelativeObject:
-
- kind = 'relative'
- counter = 0
-
- def __init__(self, name, active, intensity, xy, color, red, green, blue, layer , closed, xpos , ypos , resize , rotx , roty , rotz):
- self.name = name
- self.active = active # True/False
- self.intensity = intensity
- self.xy = [] # Dots list
- self.color = color # RGB color in int
- self.red = red
- self.green = green
- self.blue = blue
- self.layer = layer
- self.closed = closed
- self.xpos = xpos
- self.ypos = ypos
- self.resize = resize
- self.rotx = rotx
- self.roty = roty
- self.rotz = rotz
-
- RelativeObject.counter += 1
- #type(self).counter += 1
-
- def __del__(self):
- RelativeObject.counter -= 1
-
-
-# Fixed Laser object : point list in 'pygame' space (top left = 0,0 / bottom right)
-class FixedObject:
-
- kind = 'fixed'
- counter = 0
-
- def __init__(self, name, intensity, active, xy, color, red, green, blue, layer , closed):
- self.name = name
- self.active = active # True/False
- self.intensity = intensity
- self.xy = []
- self.color = color
- self.red = red
- self.green = green
- self.blue = blue
- self.layer = layer
- self.closed = closed
-
- FixedObject.counter += 1
-
- def __del__(self):
- FixedObject.counter -= 1
-
-'''
-
-class IterDest(type):
- def __new__ (cls, name, bases, dct):
- dct['_instances'] = []
- return super().__new__(cls, name, bases, dct)
-
- def __call__(cls, *args, **kwargs):
- instance = super().__call__(*args, **kwargs)
- cls._instances.append(instance)
- return instance
-
- def __iter__(cls):
- return iter(cls._instances)
-
-class DestObject():
-
-# class Destinations(metaclass=IterDest):
- __metaclass__ = IterDest
- counter = 0
- def __init__(self, name, number, active, layer , scene, laser):
- self.name = name
- self.number = number
- self.active = active
- self.layer = layer
- self.scene = scene
- self.laser = laser
-
- DestObject.counter += 1
-
- def __del__(self):
- DestObject.counter -= 1
-'''
-class DestObject():
-
-# class Destinations(metaclass=IterDest):
- _instances = set()
- counter = 0
-
- def __init__(self, name, number, active, layer , scene, laser):
- self.name = name
- self.number = number
- self.active = active
- self.layer = layer
- self.scene = scene
- self.laser = laser
- self._instances.add(weakref.ref(self))
- DestObject.counter += 1
-
- @classmethod
- def getinstances(cls):
- dead = set()
- for ref in cls._instances:
- obj = ref()
- if obj is not None:
- yield obj
- else:
- dead.add(ref)
- cls._instances -= dead
-
-
- def __del__(self):
- DestObject.counter -= 1
-
-
-
-def Config(redIP,client,myname):
- global ClientNumber, name, redisIP, r
-
- redisIP = redIP
- r = redis.StrictRedis(host=redisIP, port=6379, db=0)
-
- # ClientNumber 255 are not drawing anything like artnet
- ClientNumber = client
- #print ("client configured",ClientNumber)
- name = myname
- print ("lj23layers : Plugin declare its name :",name)
- #print layer
- return r
-
-
-def LjClient(client):
- global ClientNumber
-
- ClientNumber = client
-
-
-
-def Ljlayer(somelayer):
- global layer
-
- layer = somelayer
-
-
-def fromRedis(n):
-
- encoded = r.get(n)
- #print("")
- #print('fromredis key',n,":",encoded)
- h, w = struct.unpack('>II',encoded[:8])
- #print("fromredis array size",n,":",h,w)
- a = np.frombuffer(encoded, dtype=np.int16, offset=8).reshape(h,w)
- #print("fromredis array",n,":",a)
- return a
-
-# Store Numpy array 'a' in Redis key 'n'
-# Write also in redis key 'a' numpy array, its 2 dimensions size : h time w values
-def toRedis(n,a):
-
- #print("array.shape", a.shape, len(a.shape) )
- if len(a.shape) == 1:
- h = a.shape[0]
- w = 1
- else:
- h,w = a.shape
- #print("toredis", n,"h",h,"w",w,"a",a)
- shape = struct.pack('>II',h,w)
-
- #shape = struct.pack('>II',len(a),1)
- #print("toredis",n,a)
- encoded = shape + a.tobytes()
-
- # Store encoded data in Redis
- return r.set(n,encoded)
-
-
-#
-# OSC functions
-#
-
-# OSC clients
-
-def SendLJ(oscaddress,oscargs=''):
-
- oscmsg = OSCMessage()
- oscmsg.setAddress(oscaddress)
- oscmsg.append(oscargs)
-
- osclientlj = OSCClient()
- osclientlj.connect((redisIP, 8002))
-
- print("lj23layers for",name,"sending OSC message :", oscmsg, "to", redisIP, ":8002")
- if gstt.debug >0:
- print("lj23layers for",name,"sending OSC message :", oscmsg, "to", redisIP, ":8002")
- try:
- osclientlj.sendto(oscmsg, (redisIP, 8002))
- oscmsg.clearData()
- except:
- print ('Connection to LJ refused : died ?')
- pass
- #time.sleep(0.001
-
-
-
-# Resolume OSC Arena client.
-# sendresol(oscaddress, [arg1, arg2,...])
-# example : sendresol("/noteon",note)
-
-def SendResol(oscaddress,oscargs):
-
- oscmsg = OSCMessage()
- oscmsg.setAddress(oscaddress)
- oscmsg.append(oscargs)
-
- osclientresol = OSCClient()
- osclientresol.connect((oscIPresol, oscPORTresol))
-
- print("lj23layers sending OSC message : ", oscmsg, "to Resolume", oscIPresol, ":", oscPORTresol)
- try:
- osclientresol.sendto(oscmsg, (oscIPresol, oscPORTresol))
- oscmsg.clearData()
- except:
- print ('Connection to Resolume refused : died ?')
- pass
-
-
-def SendIntensity(laser, intensity):
- r.set('/intensity/' + str(laser), str(intensity))
- r.set('/order/'+str(laser), 6)
- SendLJ("/kpps/" + str(layer)+ " " + str(int(args[1])))
-
-
-def Sendkpps(laser, kpps):
- r.set('/kpps/' + str(laser), str(kpps))
- r.set('/order/'+str(laser), 7)
-
-
-def WebStatus(message):
- SendLJ("/status", message)
-
-
-# Closing plugin messages to LJ
-def ClosePlugin():
- WebStatus(name+" Exiting")
- SendLJ("/"+name+"/start",0)
-
-
-
-
-# RAW OSC Frame available ?
-def OSCframe():
- # clear timed_out flag
- #print "oscframe"
- oscserver.timed_out = False
- # handle all pending requests then return
- while not oscserver.timed_out:
- oscserver.handle_request()
-
-# Answer to LJ pings with /pong value
-def OSCping(path, tags, args, source):
-#def OSCping():
- if gstt.debug >0:
- print(name, "lj23layers got /ping from LJ -> reply /pong", name)
- SendLJ("/pong",name)
-
-# Properly close the system. Todo
-def OSCstop():
- oscserver.close()
-
-
-# /quit
-def OSCquit(path, tags, args, source):
- global oscrun
-
- oscrun = False
- print('lj23layers got /quit for',name)
- #WebStatus(name + " quit.")
- #SendLJ("/"+name+"/start",0)
- #print("Stopping OSC...")
- #OSCstop()
- #sys.exit()
-
-
-# default handler
-def OSChandler(path, tags, args, source):
-
- oscaddress = ''.join(path.split("/"))
- print("lj23layers Default OSC Handler for",name,": msg from Client :" + str(source[0]),)
- print("OSC address", path)
- if len(args) > 0:
- print("with args", args)
-
- #oscIPout = str(source[0])
- #osclient.connect((oscIPout, oscPORTout))
-
-
-# for any laser object : /pluginame/obj objectname attribute value
-# like : /pluginname/obj 'fft' 'xpos' 100
-# attributes for all lj Objects: name, xy_list, c, layer
-# + for RelativeObjects : closed, xpos , ypos , resize , rotx , roty , rotz
-def OSCobj(path, tags, args, source):
-
- obj = eval(args[0]+"."+ args[1])
- obj = args[2]
-
-
-def OSCvar(path, tags, args, source):
-
- obj = eval(args[0])
- obj = args[1]
-
-
-def addOSCdefaults(server):
- global oscserver
-
- oscserver = server
- oscserver.addMsgHandler( "default", OSChandler )
- oscserver.addMsgHandler( "/ping", OSCping)
- oscserver.addMsgHandler( "/quit", OSCquit)
- oscserver.addMsgHandler( "/"+ name + "/adddest", OSCadddest)
- oscserver.addMsgHandler( "/"+ name + "/deldest", OSCdeldest)
- oscserver.addMsgHandler( "/"+ name + "/dest", OSCdest)
- oscserver.addMsgHandler( "/"+ name + "/obj", OSCobj)
- oscserver.addMsgHandler( "/"+ name + "/var", OSCvar)
-
-
-
-#
-# Color functions
-#
-
-# input hexcode = '0xff00ff'
-def hex2rgb(hexcode):
-
- hexcode = hexcode[2:]
- return tuple(int(hexcode[i:i+2], 16) for i in (0, 2, 4))
- #return tuple(map(ord,hexcode[1:].decode('hex')))
-
-# input rgb=(255,0,255) output '0xff00ff'
-#def rgb2hex(rgb):
-# return '0x%02x%02x%02x' % tuple(rgb)
-
-def rgb2hex(r, g, b):
- return hex((r << 16) + (g << 8) + b)
-
-
-#def rgb2int(rgb):
-# return int('0x%02x%02x%02x' % tuple(rgb),0)
-
-def rgb2int(r,g,b):
- return int('0x%02x%02x%02x' % (r,g,b),0)
-
-def int2rgb(intcode):
- #hexcode = '0x{0:06X}'.format(intcode)
- hexcode = '{0:06X}'.format(intcode)
- return tuple(int(hexcode[i:i+2], 16) for i in (0, 2, 4))
-
-
-
-#
-# Drawing basic functions
-#
-
-# Lines
-def Line(xy1, xy2, c, layer ):
- LineTo(xy1, 0, layer )
- LineTo(xy2, c , layer )
-
-def rLine(xy1, xy2, c, layer , xpos = 0, ypos =0, resize =0.7, rotx =0, roty =0 , rotz=0):
- rLineTo(xy1, 0, layer )
- rLineTo(xy2, c , layer )
-
-def LineRGB(xy1, xy2, red,green,blue, layer ):
-
- LineTo(xy1, 0, layer )
- LineTo(xy2, int('0x%02x%02x%02x' % (red,green,blue),0) , layer )
-
-
-# Lineto
-def LineTo(xy, c, layer ):
-
- layers[layer].append((xy + (c,)))
-
-def LineRGBTo(xy, red, green, blue, layer ):
-
- LineTo(xy, int('0x%02x%02x%02x' % (red,green,blue),0), layer )
-
-def rLineTo(xy, c, layer , xpos = 0, ypos =0, resize =0.7, rotx =0, roty =0 , rotz=0):
-
- layers[layer ].append((Pointransf(xy, xpos, ypos, resize, rotx, roty, rotz) + (c,)))
-
-
-# Polylines
-def PolyLineOneColor(xy_list, c, layer , closed ):
- #print "--"
- #print "c",c
- #print "xy_list",xy_list
- #print "--"
- xy0 = None
- for xy in xy_list:
- if xy0 is None:
- xy0 = xy
- #print "xy0:",xy0
- LineTo(xy0,0, layer )
- LineTo(xy0,c, layer )
- else:
- #print "xy:",xy
- LineTo(xy,c, layer )
- if closed:
- LineTo(xy0,c, layer )
-
-def PolyLineRGB(xy_list, red, green, blue, layer , closed ):
-
- PolyLineOneColor(xy_list, int('0x%02x%02x%02x' % (red,green,blue),0), layer , closed )
-
-
-# rPolylines
-# Send 2D point list around 0,0 with 3D rotation resizing and reposition around xpos ypos
-#def rPolyLineOneColor(self, xy_list, c, layer , closed, xpos = 0, ypos =0, resize =1, rotx =0, roty =0 , rotz=0):
-def rPolyLineOneColor(xy_list, c, layer , closed, xpos = 0, ypos =0, resize =0.7, rotx =0, roty =0 , rotz=0):
- xy0 = None
- for xy in xy_list:
- print(xy,xy0)
- if xy0 is None:
- xy0 = xy
- LineTo(Pointransf(xy0, xpos, ypos, resize, rotx, roty, rotz), 0, layer )
- LineTo(Pointransf(xy0, xpos, ypos, resize, rotx, roty, rotz), c, layer )
- else:
- LineTo(Pointransf(xy, xpos, ypos, resize, rotx, roty, rotz), c, layer )
- if closed:
- LineTo(Pointransf(xy0, xpos, ypos, resize, rotx, roty, rotz), c, layer )
-
-def rPolyLineRGB(xy_list, red, green, blue, layer , closed, xpos = 0, ypos =0, resize =0.7, rotx =0, roty =0 , rotz=0):
-
- rPolyLineOneColor(xy_list, int('0x%02x%02x%02x' % (red,green,blue),0), layer , closed, xpos = 0, ypos =0, resize =0.7, rotx =0, roty =0 , rotz=0)
-
-
-
-# Computing points coordinates for rPolyline function from 3D and around 0,0 to pygame coordinates
-def Pointransf(xy, xpos = 0, ypos =0, resize =1, rotx =0, roty =0 , rotz=0):
-
- x = xy[0] * resize
- y = xy[1] * resize
- z = xy[2] * resize
-
- rad = math.radians(rotx)
- cosaX = math.cos(rad)
- sinaX = math.sin(rad)
-
- y2 = y
- y = y2 * cosaX - z * sinaX
- z = y2 * sinaX + z * cosaX
-
- rad = math.radians(roty)
- cosaY = math.cos(rad)
- sinaY = math.sin(rad)
-
- z2 = z
- z = z2 * cosaY - x * sinaY
- x = z2 * sinaY + x * cosaY
-
- rad = math.radians(rotz)
- cosZ = math.cos(rad)
- sinZ = math.sin(rad)
-
- x2 = x
- x = x2 * cosZ - y * sinZ
- y = x2 * sinZ + y * cosZ
-
- #print xy, (x + xpos,y+ ypos)
- #return (x + xpos, y + ypos)
-
- #to understand why it get negative Y
- """ Transforms this 3D point to 2D using a perspective projection. """
- factor = fov / (viewer_distance + z)
- x = x * factor + xpos
- y = y * factor + ypos
- #y = - y * factor + ypos
- return (x, y)
-
-
-def Lineslayer(layer):
- print("Stupido !! your code is to old : use Drawlayer() instead of LinesPL()")
- Drawlayer(layer )
-
-
-def Draw(layer):
- #print '/pl/0/'+str(layer), str(layers[layer])
- if r.set('/pl/'+str(ClientNumber)+'/'+str(layer), str(layers[layer])) == True:
- #print '/pl/'+str(ClientNumber)+'/'+str(layer), str(layers[layer])
- layers[layer] = []
- return True
- else:
- return False
-
-def Resetlayer(self, layer):
- layers[layer] = []
-
-
-#
-# "Destinations" management for layers
-#
-
-
-# Add a destination for a given layer
-def Addest(layer, scene, laser):
-
- print (name,'adding',layer,scene,laser,'?')
- if Findest(layer, scene, laser) == -1:
- newdest = DestsObjects.counter + 1
- Dest0 = lj.DestObject(str(newdest), newdest, True, layer , scene, laser)
- print("New destination added with number", newdest)
- else:
- print("Destination already existed")
-
-
-# OSC add a destination for a given layer
-# /pluginame/dest layer, scene, laser
-def OSCadddest(path, tags, args, source):
-
- Addests(int(args[0]),int(args[1]),int(args[2]))
-
-
-# Find layer destination with its parameters in destinations dictionnary
-def Findest(layer, scene, laser):
-
- print(name, 'searching layer,scene,laser',layer,scene,laser)
- for item in DestObjects.getinstances():
- #print(item)
- if item.layer == layer and item.scene == scene and item.laser == laser:
- #Dests.append(item[0])
- print('found number',item.number)
- return item.number
- else:
- print('no destination found')
- return -1
- '''
- #Dests = list()
- allDests = Dests.items()
- for item in allDests:
- print(item)
- if item[1] == layer and item[2] == scene and item[3] == laser:
- #Dests.append(item[0])
- return Dests[item[0]]
- else:
- return -1
- '''
-
-# Find and remove a layer destination with its parameters in destinations dictionnary
-def Deldest(layer, scene, laser):
-
- Destnumber = Findest(layer, scene, laser)
- print(name,'deleting Destination layer, scene, laser', layer,scene, laser)
-
- if Destnumber != -1:
- print('found DestObject', Destnumber)
- delattr(DestObjects, str(Destnumber))
- print("Destination", Destnumber,"was removed")
- else:
- print("Destination was not found")
-
-
-# OSC Delete a destination for a given layer
-# /pluginame/deldests layer, scene, laser
-def OSCdeldest(path, tags, args, source):
-
- Deldests(args[0], args[1], args[2])
-
-
-# pluginame/dest layer, scene, laser
-def OSCdest(path, tags, args, source):
-
- # For single layer plugin : add a new destination
- Addest(0, args[0], args[1])
-
- # For single layer plugin : remove a destination
-
- # For multiple layers plugin : add or remove
-
-
-# Replace Drawlayer if Destinations paradigm is implemented in plugin code
-def DrawDests():
-
- # Objects style
-
- #print("DrawDest")
-
- for destination in DestObject.getinstances():
-
- #print(Dests[str(destination)])
- #print('/pl/'+str(Dests[str(destination)]["scene"])+'/'+str(Dests[str(destination)]["laser"]), ":", str(layers[Dests[str(destination)]["PL"]]))
- #print(len(layers[destination.layer]))
- if destination.active == True:
- if r.set('/pl/'+str(destination.scene)+'/'+str(destination.laser), str(layers[destination.layer])) == True:
- #print ('layer', destination.layer, '/pl/'+str(destination.scene)+'/'+str(destination.laser), str(layers[destination.layer]))
- pass
- else:
- print('Redis key modification failed')
-
- # Maybe one layer can be sent to multiple destination so they are all reset *after* all sending.
- for layerss in range(4):
-
- layers[layerss] = []
-
- '''
- # Dictionnary style
-
- #print(Dests)
- for destination in range(len(Dests)):
- #print(Dests[str(destination)])
- #print('/pl/'+str(Dests[str(destination)]["scene"])+'/'+str(Dests[str(destination)]["laser"]), ":", str(layers[Dests[str(destination)]["layer"]]))
- if r.set('/pl/'+str(Dests[str(destination)]["scene"])+'/'+str(Dests[str(destination)]["laser"]), str(layers[Dests[str(destination)]["layer"]])) == True:
- #print '/pl/'+str(ClientNumber)+'/'+str(layer), str(layers[layer])
- pass
- else:
- print('Redis key modification failed')
-
- # Maybe one layer can be sent to multiple destination so they are all reset *after* all sending.
- for destination in range(len(Dests)):
-
- layers[Dests[str(destination)]["layer"]] = []
- '''
-'''
-scenes = 4
-
-def DrawDestslayer(layer):
-
- for scene in range(scenes):
-
- if Dests[laser]["scene"] != -1:
- if r.set('/pl/'+str(Dests[laser]["scene"])+'/'+str(Dests[laser]["laser"]), str(layers[Dests[laser]["laser"]])) == True:
- if r.set('/pl/'+str(ClientNumber)+'/'+str(layer), str(layers[layer])) == True:
- #print '/pl/'+str(ClientNumber)+'/'+str(layer), str(layers[layer])
- layers[Dests[laser]["laser"]] = []
- return True
- else:
- return False
-
-'''
-
-#
-# High level drawing functions
-#
-
-
-# Font1
-
-
-ASCII_GRAPHICS = [
-
-#implementé
-
- [(-50,30), (-30,-30), (30,-30), (10,30), (-50,30)], # 0
- [(-20,30), (0,-30), (-20,30)], # 1
- [(-30,-10), (0,-30), (30,-10), (30,0), (-30,30), (30,30)], # 2
- [(-30,-30), (0,-30), (30,-10), (0,0), (30,10), (0,30), (-30,30)], # 3
- [(30,10), (-30,10), (0,-30), (0,30)], # 4
- [(30,-30), (-30,-30), (-30,0), (0,0), (30,10), (0,30), (-30,30)], # 5
- [(30,-30), (0,-30), (-30,-10), (-30,30), (0,30), (30,10), (30,0), (-30,0)], # 6
- [(-30,-30), (30,-30), (-30,30)], # 7
- [(-30,30), (-30,-30), (30,-30), (30,30), (-30,30), (-30,0), (30,0)], # 8
- [(30,0), (-30,0), (-30,-10), (0,-30), (30,-30), (30,10), (0,30), (-30,30)], # 9
-
-# A implementer
- [(-30,10), (30,-10), (30,10), (0,30), (-30,10), (-30,-10), (0,-30), (30,-10)], #:
- [(-30,-10), (0,-30), (0,30)], [(-30,30), (30,30)], # ;
- [(-30,-10), (0,-30), (30,-10), (30,0), (-30,30), (30,30)], # <
- [(-30,-30), (0,-30), (30,-10), (0,0), (30,10), (0,30), (-30,30)], # =
- [(30,10), (-30,10), (0,-30), (0,30)], # >
- [(30,-30), (-30,-30), (-30,0), (0,0), (30,10), (0,30), (-30,30)], # ?
- [(30,-30), (0,-30), (-30,-10), (-30,30), (0,30), (30,10), (30,0), (-30,0)], # @
-
-# Implementé 65-90
-
- [(-30,30), (-30,-30), (30,-30), (30,30), (30,0), (-30,0)], # A
- [(-30,30), (-30,-30), (30,-30), (30,30), (30,0), (-30,0)], # A
- [(-30,30), (-30,-30), (30,-30), (30,30), (-30,30), (-30,0), (30,0)], # B
- [(30,30), (-30,30), (-30,-30), (30,-30)], # C
- [(-30,30), (-30,-30), (30,-30), (30,30), (-30,30)], # D
- [(30,30), (-30,30), (-30,-0), (30,0), (-30,0), (-30,-30), (30,-30)], # E
- [(-30,30), (-30,-0), (30,0), (-30,0), (-30,-30), (30,-30)], # F
- [(0,0), (30,0), (30,30), (-30,30), (-30,-30),(30,-30)], # G
- [(-30,-30), (-30,30), (-30,0), (30,0), (30,30), (30,-30)], # H
- [(0,30), (0,-30)], # I
- [(-30,30), (0,-30), (0,-30), (-30,-30), (30,-30)], # J
- [(-30,-30), (-30,30), (-30,0), (30,-30), (-30,0), (30,30)], # K
- [(30,30), (-30,30), (-30,-30)], # L
- [(-30,30), (-30,-30), (0,0), (30,-30), (30,30)], # M
- [(-30,30), (-30,-30), (30,30), (30,-30)], # N
- [(-30,30), (-30,-30), (30,-30), (30,30), (-30,30)], # O
- [(-30,0), (30,0), (30,-30), (-30,-30), (-30,30)], # P
- [(30,30), (30,-30), (-30,-30), (-30,30), (30,30),(35,35)], # Q
- [(-30,30), (-30,-30), (30,-30), (30,0), (-30,0), (30,30)], # R
- [(30,-30), (-30,-30), (-30,0), (30,0), (30,30), (-30,30)], # S
- [(0,30), (0,-30), (-30,-30), (30,-30)], # T
- [(-30,-30), (-30,30), (30,30), (30,-30)], # U
- [(-30,-30), (0,30), (30,-30)], # V
- [(-30,-30), (-30,30), (0,0), (30,30), (30,-30)], # W
- [(-30,30), (30,-30), (-30,-30), (30,30)], # X
- [(0,30), (0,0), (30,-30), (0,0), (-30,-30)], # Y
- [(30,30), (-30,30), (30,-30), (-30,-30)], # Z
-
-# A implementer
-
- [(-30,-10), (0,-30), (0,30)], [(-30,30), (30,30)], # [
- [(-30,-10), (0,-30), (30,-10), (30,0), (-30,30), (30,30)], # \
- [(-30,-30), (0,-30), (30,-10), (0,0), (30,10), (0,30), (-30,30)], # ]
- [(30,10), (-30,10), (0,-30), (0,30)], # ^
- [(30,-30), (-30,-30), (-30,0), (0,0), (30,10), (0,30), (-30,30)], # _
- [(30,-30), (0,-30), (-30,-10), (-30,30), (0,30), (30,10), (30,0), (-30,0)], # `
-
-# Implementé 97-122
-
- [(-20,20), (-20,-20), (20,-20), (20,20), (20,0), (-20,0)], # a
- [(-20,20), (-20,-20), (20,-20), (20,20), (-20,20), (-20,0), (20,0)], # b
- [(20,20), (-20,20), (-20,-20), (20,-20)], # c
- [(-20,20), (-20,-20), (20,-20), (20,20), (-20,20)], # d
- [(20,20), (-20,20), (-20,-0), (20,0), (-20,0), (-20,-20), (20,-20)], # e
- [(-20,20), (-20,-0), (20,0), (-20,0), (-20,-20), (20,-20)], # f
- [(0,0), (20,0), (20,20), (-20,20), (-20,-20),(20,-20)], # g
- [(-20,-20), (-20,20), (-20,0), (20,0), (20,20), (20,-20)], # h
- [(0,20), (0,-20)], # i
- [(-20,20), (0,-20), (0,-20), (-20,-20), (20,-20)], # j
- [(-20,-20), (-20,20), (-20,0), (20,-20), (-20,0), (20,20)], # k
- [(20,20), (-20,20), (-20,-20)], # l
- [(-20,20), (-20,-20), (0,0), (20,-20), (20,20)], # m
- [(-20,20), (-20,-20), (20,20), (20,-20)], # n
- [(-20,20), (-20,-20), (20,-20), (20,20), (-20,20)], # o
- [(-20,0), (20,0), (20,-20), (-20,-20), (-20,20)], # p
- [(20,20), (20,-20), (-20,-20), (-20,20), (20,20),(25,25)], # q
- [(-20,20), (-20,-20), (20,-20), (20,0), (-20,0), (20,20)], # r
- [(20,-20), (-20,-20), (-20,0), (20,0), (20,20), (-20,20)], # s
- [(0,20), (0,-20), (-20,-20), (20,-20)], # t
- [(-20,-20), (-20,20), (20,20), (20,-20)], # u
- [(-20,-20), (0,20), (20,-20)], # v
- [(-20,-20), (-20,20), (0,0), (20,20), (20,-20)], # w
- [(-20,20), (20,-20)], [(-20,-20), (20,20)], # x
- [(0,20), (0,0), (20,-20), (0,0), (-20,-20)], # y
- [(20,20), (-20,20), (20,-20), (-20,-20)], # z
-
- # A implementer
- [(-2,15), (2,15)], # Point a la place de {
- [(-30,-10), (0,-30), (0,30)], [(-30,30), (30,30)], # |
- [(-30,-10), (0,-30), (30,-10), (30,0), (-30,30), (30,30)], # }
- [(-30,-30), (0,-30), (30,-10), (0,0), (30,10), (0,30), (-30,30)], #
- [(30,10), (-30,10), (0,-30), (0,30)], # DEL
-
- # Accents 128-151 a implementer
- [(30,30), (-30,30), (-30,-30), (30,-30)], # C
- [(-20,-20), (-20,20), (20,20), (20,-20)], # û
- [(20,20), (-20,20), (-20,-0), (20,0), (-20,0), (-20,-20), (20,-20)], # é
- [(-20,20), (-20,-20), (20,-20), (20,20), (20,0), (-20,0)], # â
- [(-20,20), (-20,-20), (20,-20), (20,20), (20,0), (-20,0)], # ä
- [(-20,20), (-20,-20), (20,-20), (20,20), (20,0), (-20,0)], # a
- [(20,20), (-20,20), (-20,-20), (20,-20)], # c
- [(20,20), (-20,20), (-20,-0), (20,0), (-20,0), (-20,-20), (20,-20)], # é
- [(20,20), (-20,20), (-20,-0), (20,0), (-20,0), (-20,-20), (20,-20)], # é
- [(20,20), (-20,20), (-20,-0), (20,0), (-20,0), (-20,-20), (20,-20)], # é
- [(0,20), (0,-20)], # i
- [(0,20), (0,-20)], # i
- [(0,20), (0,-20)], # i
- [(-30,30), (-30,-30), (30,-30), (30,30), (30,0), (-30,0)], # A
- [(-30,30), (-30,-30), (30,-30), (30,30), (30,0), (-30,0)], # A
- [(30,30), (-30,30), (-30,-0), (30,0), (-30,0), (-30,-30), (30,-30)], # E
- [(-20,20), (-20,-20), (20,-20), (20,20), (20,0), (-20,0)], # a
- [(-20,20), (-20,-20), (20,-20), (20,20), (20,0), (-20,0)], # a
- [(-20,20), (-20,-20), (20,-20), (20,20), (-20,20)], # o
- [(-20,20), (-20,-20), (20,-20), (20,20), (-20,20)], # o
- [(-20,20), (-20,-20), (20,-20), (20,20), (-20,20)], # o
- [(-20,-20), (-20,20), (20,20), (20,-20)], # u
- [(-20,-20), (-20,20), (20,20), (20,-20)] # u
-
-]
-
-
-def DigitsDots(number,color):
- dots =[]
- for dot in ASCII_GRAPHICS[number]:
- #print dot
- dots.append((gstt.xy_center[0]+dot[0],gstt.xy_center[1]+dot[1],color))
- #self.point_list.append((xy + (c,)))
- return dots
-
-def CharDots(char,color):
-
- dots =[]
- for dot in ASCII_GRAPHICS[ord(char)-46]:
- dots.append((dot[0],dot[1],color))
- return dots
-
-def Text(message, c, layer, xpos, ypos, resize, rotx, roty, rotz):
-
- dots =[]
-
- l = len(message)
- i= 0
- #print()
- # print (message)
-
- for ch in message:
-
- #print ""
- # texte centre en x automatiquement selon le nombre de lettres l
- x_offset = 26 * (- (0.9*l) + 3*i)
- # Digits
- if ord(ch)<58:
- char_layer_list = ASCII_GRAPHICS[ord(ch) - 48]
-
- # Uppercase
- elif 64 < ord(ch) < 91 :
- char_layer_list = ASCII_GRAPHICS[ord(ch) - 46]
-
- # Lowercase
- elif 96 < ord(ch) < 123 :
- char_layer_list = ASCII_GRAPHICS[ord(ch) - 45]
-
- char_draw = []
- #dots.append((char_layer_list[0][0] + x_offset,char_layer_list[0][1],0))
-
- for xy in char_layer_list:
- char_draw.append((xy[0] + x_offset,xy[1],c))
- i +=1
- #print ch,char_layer_list,char_draw
- rPolyLineOneColor(char_draw, c, layer , False, xpos, ypos, resize, rotx, roty, rotz)
- #dots.append(char_draw)
-
-def TextRGB(message,c, layer, xpos, ypos, resize, rotx, roty, rotz):
-
- Text(message,int('0x%02x%02x%02x' % (red,green,blue),0), layer, xpos, ypos, resize, rotx, roty, rotz)
-
-
-
-
-
-
-
\ No newline at end of file
diff --git a/libs3/tracer3.sync-conflict-20200728-024608-NJKFP4Q.py b/libs3/tracer3.sync-conflict-20200728-024608-NJKFP4Q.py
deleted file mode 100644
index 0e06084..0000000
--- a/libs3/tracer3.sync-conflict-20200728-024608-NJKFP4Q.py
+++ /dev/null
@@ -1,542 +0,0 @@
-#!/usr/bin/python3
-# -*- coding: utf-8 -*-
-# -*- mode: Python -*-
-
-'''
-
-Tracer
-for LJ v0.8.2
-
-Enhanced version (support for several lasers) of the etherdream python library from j4cDAC.
-One tracer process is launched per requested laser. I/O based on redis keys.
-
-LICENCE : CC
-Sam Neurohack, pclf
-
-Uses redis keys value for live inputs (Pointlists to draw,...) and outputs (DAC state, errors,..).
-Most of redis keys are read and set at each main loop.
-Includes live conversion in etherdream coordinates, geometric corrections,...
-Etherdream IP is found in conf file for given laser number. (LJ.conf)
-
-Redis keys to draw things :
-/order select some change to adjust. See below
-/pl/lasernumber [(x,y,color),(x1,y1,color),...] A string of list of points list.
-/resampler/lasernumber [(1.0,8), (0.25,3),(0.75,3),(1.0,10)] : a string for resampling rules.
- the first tuple (1.0,8) is for short line < 4000 in etherdream space
- (0.25,3),(0.75,3),(1.0,10) for long line > 4000
- i.e (0.25,3) means go at 25% position on the line, send 3 times this position to etherdream
-/clientkey
-
-
-Redis keys for Etherdream DAC
-
-- Control
-/kpps see order 7
-/intensity see order 6
-/red see order 8
-/green see order 8
-/blue see order 8
-
-- DAC status report
-/lstt/lasernumber value etherdream last_status.playback_state (0: idle 1: prepare 2: playing)
-/cap/lasernumber value number of empty points sent to fill etherdream buffer (up to 1799)
-/lack/lasernumber value "a": ACK "F": Full "I": invalid. 64 or 35 for no connection.
-
-
-
-Order
-
- 0 : Draw Normal point list
- 1 : Get the new EDH
- 2 : Draw BLACK point list
- 3 : Draw GRID point list
- 4 : Resampler Change (longs and shorts lsteps)
- 5 : Client Key change
- 6 : Intensity change
- 7 : kpps change
- 8 : color balance change
-
-Geometric corrections :
-
-Doctodo
-
-
-'''
-import socket
-import time
-import struct
-#from gstt import debug
-from libs3 import gstt,log
-import math
-from itertools import cycle
-#from globalVars import *
-import pdb
-import ast
-import redis
-
-from libs3 import homographyp
-import numpy as np
-import binascii
-
-black_points = [(278.0,225.0,0),(562.0,279.0,0),(401.0,375.0,0),(296.0,454.0,0),(298.0,165.0,0)]
-grid_points = [(300.0,200.0,0),(500.0,200.0,65280),(500.0,400.0,65280),(300.0,400.0,65280),(300.0,200.0,65280),(300.0,200.0,0),(200.0,100.0,0),(600.0,100.0,65280),(600.0,500.0,65280),(200.0,500.0,65280),(200.0,100.0,65280)]
-
-r = redis.StrictRedis(host=gstt.LjayServerIP, port=6379, db=0)
-# r = redis.StrictRedis(host=gstt.LjayServerIP , port=6379, db=0, password='-+F816Y+-')
-ackstate = {'61': 'ACK', '46': 'FULL', '49': "INVALID", '21': 'STOP', '64': "NO CONNECTION ?", '35': "NO CONNECTION ?" , '97': 'ACK', '70': 'FULL', '73': "INVALID", '33': 'STOP', '100': "NOCONNECTION", '48': "NOCONNECTION", 'a': 'ACK', 'F': 'FULL', 'I': "INVALID", '!': 'STOP', 'd': "NO CONNECTION ?", '0': "NO CONNECTION ?"}
-lstate = {'0': 'IDLE', '1': 'PREPARE', '2': "PLAYING", '64': "NOCONNECTION ?" }
-
-def pack_point(laser,intensity, x, y, r, g, b, i = -1, u1 = 0, u2 = 0, flags = 0):
- """Pack some color values into a struct dac_point."""
-
- #print("Tracer", laser,":", r,g,b,"intensity", intensity, "i", i)
-
- if r > intensity:
- r = intensity
- if g > intensity:
- g = intensity
- if b > intensity:
- b = intensity
-
-
- if max(r, g, b) == 0:
- i = 0
- else:
- i = intensity
-
-
- #print("Tracer", laser,":", r,g,b,"intensity", intensity, "i", i)
- #print(x, type(x), int(x))
- return struct.pack(" 1:
- self.status.dump(prefix)
-
-
-class DAC(object):
- """A connection to a DAC."""
-
-
- # "Laser point List" Point generator
- # each points is yielded : Getpoints() call n times OnePoint()
-
- def OnePoint(self):
-
- while True:
-
- #pdb.set_trace()
- for indexpoint,currentpoint in enumerate(self.pl):
- #print indexpoint, currentpoint
- xyc = [currentpoint[0],currentpoint[1],currentpoint[2]]
- self.xyrgb = self.EtherPoint(xyc)
-
- delta_x, delta_y = self.xyrgb[0] - self.xyrgb_prev[0], self.xyrgb[1] - self.xyrgb_prev[1]
-
- #test adaptation selon longueur ligne
- if math.hypot(delta_x, delta_y) < 4000:
-
- # For glitch art : decrease lsteps
- #l_steps = [ (1.0, 8)]
- l_steps = gstt.stepshortline
-
- else:
- # For glitch art : decrease lsteps
- #l_steps = [ (0.25, 3), (0.75, 3), (1.0, 10)]
- l_steps = gstt.stepslongline
-
- for e in l_steps:
- step = e[0]
-
- for i in range(0,e[1]):
-
- self.xyrgb_step = (self.xyrgb_prev[0] + step*delta_x, self.xyrgb_prev[1] + step*delta_y) + self.xyrgb[2:]
- yield self.xyrgb_step
-
- self.xyrgb_prev = self.xyrgb
-
-
- def GetPoints(self, n):
-
- d = [next(self.newstream) for i in range(n)]
- #print d
- return d
-
-
- # Etherpoint all transform in one matrix, with warp !!
- # xyc : x y color
- def EtherPoint(self,xyc):
-
- c = xyc[2]
-
- #print("")
- #print("pygame point",[(xyc[0],xyc[1],xyc[2])])
- #gstt.EDH[self.mylaser]= np.array(ast.literal_eval(r.get('/EDH/'+str(self.mylaser))))
- position = homographyp.apply(gstt.EDH[self.mylaser],np.array([(xyc[0],xyc[1])]))
-
- #print("etherdream point",position[0][0], position[0][1], ((c >> 16) & 0xFF) << 8, ((c >> 8) & 0xFF) << 8, (c & 0xFF) << 8)
-
- return (position[0][0], position[0][1], ((c >> 16) & 0xFF) << 8, ((c >> 8) & 0xFF) << 8, (c & 0xFF) << 8)
-
-
- def read(self, l):
- """Read exactly length bytes from the connection."""
- while l > len(self.buf):
- self.buf += self.conn.recv(4096)
-
- obuf = self.buf
- self.buf = obuf[l:]
- return obuf[:l]
-
- def readresp(self, cmd):
- """Read a response from the DAC."""
-
-
- data = self.read(22)
- response = data[0]
- gstt.lstt_dacanswers[self.mylaser] = response
- cmdR = chr(data[1])
- status = Status(data[2:])
-
- r.set('/lack/'+str(self.mylaser), response)
-
- if cmdR != cmd:
- raise ProtocolError("expected resp for %r, got %r"
- % (cmd, cmdR))
-
- if response != ord('a'):
- raise ProtocolError("expected ACK, got %r"
- % (response, ))
-
- self.last_status = status
- return status
-
- def __init__(self, mylaser, PL, port = 7765):
- """Connect to the DAC over TCP."""
- socket.setdefaulttimeout(2)
-
- self.mylaser = mylaser
- self.clientkey = r.get("/clientkey").decode('ascii')
-
- #log.info("Tracer "+str(self.mylaser)+" connecting to "+ gstt.lasersIPS[mylaser])
- #print("DAC", self.mylaser, "Handler process, connecting to", gstt.lasersIPS[mylaser] )
- self.conn = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
- self.connstatus = self.conn.connect_ex((gstt.lasersIPS[mylaser], port))
- if self.connstatus == 35 or self.connstatus == 64:
- log.err("Tracer "+ str(self.mylaser)+" ("+ gstt.lasersIPS[mylaser]+"): "+ackstate[str(self.connstatus)])
- else:
- print("Tracer "+ str(self.mylaser)+" ("+ gstt.lasersIPS[mylaser]+"): "+ackstate[str(self.connstatus)])
-
- # ipconn state is -1 at startup (see gstt) and modified here
- r.set('/lack/'+str(self.mylaser), self.connstatus)
- gstt.lstt_ipconn[self.mylaser] = self.connstatus
-
- self.buf = b''
- # Upper case PL is the Point List number
- self.PL = PL
-
- # Lower case pl is the actual point list coordinates
-
-
- #pdb.set_trace()
- self.pl = ast.literal_eval(r.get(self.clientkey + str(self.mylaser)).decode('ascii'))
- if r.get('/EDH/'+str(self.mylaser)) == None:
- #print("Laser",self.mylaser,"NO EDH !! Computing one...")
- homographyp.newEDH(self.mylaser)
- else:
-
- gstt.EDH[self.mylaser] = np.array(ast.literal_eval(r.get('/EDH/'+str(self.mylaser)).decode('ascii')))
- #print("Laser",self.mylaser,"found its EDH in redis")
- #print gstt.EDH[self.mylaser]
-
- self.xyrgb = self.xyrgb_prev = (0,0,0,0,0)
- self.intensity = 65280
- self.newstream = self.OnePoint()
-
- if gstt.debug >0:
- print("Tracer",self.mylaser,"init asked for ckey", self.clientkey+str(self.mylaser))
- if self.connstatus != 0:
- #print(""
- log.err("Connection ERROR " +str(self.connstatus)+" with laser "+str(mylaser)+" : "+str(gstt.lasersIPS[mylaser]))
- #print("first 10 points in PL",self.PL, self.GetPoints(10)
- else:
- print("Connection status for DAC "+str(self.mylaser)+" : "+ str(self.connstatus))
-
-
- # Reference points
- # Read the "hello" message
- first_status = self.readresp("?")
- first_status.dump()
- position = []
-
-
- def begin(self, lwm, rate):
- cmd = struct.pack("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 numeric.largeArray) { ret.push('...Large Array...'); return true; }
+ var flag = false;
+ ret.push('[');
+ for(k=0;k0) { 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;k0) {
+ ret[count] = [];
+ for(j=0;j> 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>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;j255) 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=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=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=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;iv0) { 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 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=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=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=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 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;j0;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= 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;j0) {
+ 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=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=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;j0) {
+ 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=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= 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 a) { e = k; a = c; }
+ }
+ if(abs(x[i])= 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 a) { e = k; a = c; }
+ }
+ if(abs(y[P[i]]) 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=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;im) 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;kright[i]) right[i] = j;
+ }
+ for(i=0;i right[i+1]) right[i+1] = right[i]; }
+ for(i=m-1;i>=1;i--) { if(left[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 || jN) N = Ai[k]; }
+ N++;
+ ret = numeric.rep([N],0);
+ for(k=0;k1) {
+ 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] && z0x[j] && z0x[j] && z10) {
+ 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;i20) { 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= 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(x0x1) 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;ia1) 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=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
+//
+// 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.
+//
+//
+// Seeds using physical random bits downloaded
+// from random.org.
+//
+// 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 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 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= 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= 0; j--)
+ {
+ if (q[j] < q[i])
+ {
+ // writeln(i,'-',j)
+ c = q[j];
+ q[j] = q[i];
+ q[i] = c;
+ for(k=0;k> 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> 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 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= 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(;Ethis.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(;Hh.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+0.25+0.375+0.25+0.0625;break;case 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a=(function(){var c=function(e,d){var f=(e.width*0.25+0.5)|0;return d.x<=e.x+f&&d.x>=e.x-f&&d.y<=e.y+f&&d.y>=e.y-f&&d.width<=(e.width*1.5+0.5)|0&&(d.width*1.5+0.5)|0>=e.width};return{edges_density:0.07,detect_single_scale:function(E,ad,af,q,d,f,D,B){var z=(B.size[0]*D)|0,N=(B.size[1]*D)|0,V=(0.5*D+1.5)|0,U=V;var Z,X,W,Q,O,T=(d-z)|0,R=(f-N)|0;var H=(d+1)|0,w,p,r,S;var e=1/(z*N);var t,o,l,u,s,ae,A,g=true,L,h,n,G,m;var M,K,J,I,v,C;var ac=0,ab=z,aa=N*H,Y=aa+z;var F=((z*N)*255*this.edges_density)|0;var P=[];for(O=0;O0?Math.sqrt(r):1;t=B.complexClassifiers;s=t.length;g=true;for(Z=0;Zr[s].rank){r[s].parent=t;}else{r[t].parent=s;if(r[t].rank==r[s].rank){r[s].rank++;}t=s;}var A,d=v;while(r[d].parent!=-1){A=d;d=r[d].parent;r[A].parent=t;}d=y;while(r[d].parent!=-1){A=d;d=r[d].parent;r[A].parent=t;}}}}}var w=[];var o=0;for(y=0;y=0){r[e].rank=~o++;}v=~r[e].rank;}w[y]=v;}var m=[];for(y=0;y=l){h.push({x:(m[y].x*2+q)/(2*q),y:(m[y].y*2+q)/(2*q),width:(m[y].width*2+q)/(2*q),height:(m[y].height*2+q)/(2*q),neighbors:m[y].neighbors,confidence:m[y].confidence});}}var p=[];q=h.length;for(y=0;y=u.x-f&&z.y>=u.y-f&&z.x+z.width<=u.x+u.width+f&&z.y+z.height<=u.y+u.height+f&&(u.neighbors>Math.max(3,z.neighbors)||z.neighbors<3)){x=false;break}}if(x){p.push(z);}}return p}}})();b.haar=a;})(jsfeat);(function(a){var b=(function(){var c=function(f,e){var g=(f.width*0.25+0.5)|0;return e.x<=f.x+g&&e.x>=f.x-g&&e.y<=f.y+g&&e.y>=f.y-g&&e.width<=(f.width*1.5+0.5)|0&&(e.width*1.5+0.5)|0>=f.width};var d=new jsfeat.pyramid_t(1);return{interval:4,scale:1.1486,next:5,scale_to:1,prepare_cascade:function(g){var m=g.stage_classifier.length;for(var h=0;h>1;h=g.rows>>1;if(p||n!=j.cols||h!=j.rows){d.data[l<<2]=new jsfeat.matrix_t(n,h,r);j=d.data[l<<2];}jsfeat.imgproc.pyrdown(g,j);}for(l=this.next*2;l>1;h=g.rows>>1;j=d.data[(l<<2)+1];if(p||n!=j.cols||h!=j.rows){d.data[(l<<2)+1]=new jsfeat.matrix_t(n,h,r);j=d.data[(l<<2)+1];}jsfeat.imgproc.pyrdown(g,j,1,0);j=d.data[(l<<2)+2];if(p||n!=j.cols||h!=j.rows){d.data[(l<<2)+2]=new jsfeat.matrix_t(n,h,r);j=d.data[(l<<2)+2];}jsfeat.imgproc.pyrdown(g,j,0,1);j=d.data[(l<<2)+3];if(p||n!=j.cols||h!=j.rows){d.data[(l<<2)+3]=new jsfeat.matrix_t(n,h,r);j=d.data[(l<<2)+3];}jsfeat.imgproc.pyrdown(g,j,1,1);}return d},detect:function(G,L){var h=this.interval;var N=this.scale;var m=this.next;var l=this.scale_to;var ab=0,aa=0,Z=0,W=0,S=0,R=0,U=0,B=0,J=0,I=0,V=0,ae=0,M=0,ad=0,w=0,Y=0,g=0;var E=0,X,Q,D,H,F,O=true,o=true;var z=1,v=1;var s=[0,1,0,1];var r=[0,0,1,1];var K=[];var C=G.data,ac=1,u=2,t=4;var A=[],e=[0,0,0];var P=[0,0,0];var T=[0,0,0];for(ab=0;ab>2);g=C[w+(m<<3)].rows-(L.height>>2);P[0]=C[w].cols*ac;P[1]=C[w+(m<<2)].cols*ac;P[2]=C[w+(m<<3)].cols*ac;T[0]=(C[w].cols*t)-(Y*t);T[1]=(C[w+(m<<2)].cols*u)-(Y*u);T[2]=(C[w+(m<<3)].cols*ac)-(Y*ac);B=L.stage_classifier.length;for(aa=0;aa=0){V=A[H.pz[ad]][e[H.pz[ad]]+H.px[ad]];if(V=0){W=A[H.nz[ad]][e[H.nz[ad]]+H.nx[ad]];if(W>M){if(ae<=W){o=false;break}M=W;}}}E+=(o)?X[(Z<<1)+1]:X[Z<<1];}}if(Es[t].rank){s[t].parent=u;}else{s[u].parent=t;if(s[u].rank==s[t].rank){s[t].rank++;}u=t;}var B,e=w;while(s[e].parent!=-1){B=e;e=s[e].parent;s[B].parent=u;}e=z;while(s[e].parent!=-1){B=e;e=s[e].parent;s[B].parent=u;}}}}}var x=[];var p=0;for(z=0;z=0){s[f].rank=~p++;}w=~s[f].rank;}x[z]=w;}var o=[];for(z=0;z=m){k.push({x:(o[z].x*2+r)/(2*r),y:(o[z].y*2+r)/(2*r),width:(o[z].width*2+r)/(2*r),height:(o[z].height*2+r)/(2*r),neighbors:o[z].neighbors,confidence:o[z].confidence});}}var q=[];r=k.length;for(z=0;z=v.x-g&&A.y>=v.y-g&&A.x+A.width<=v.x+v.width+g&&A.y+A.height<=v.y+v.height+g&&(v.neighbors>Math.max(3,A.neighbors)||A.neighbors<3)){y=false;break}}if(y){q.push(A);}}return q}}})();a.bbf=b;})(jsfeat);(function(a){if(typeof module==="undefined"||typeof module.exports==="undefined"){window.jsfeat=a;}else{module.exports=a;}})(jsfeat);
+
+ 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 = 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,right_val:0.3035,left_val:0.52336},{features:[[9,14,1,3,-1.],[9,15,1,1,3.]],threshold:-4.1953e-004,right_val:0.44602,left_val:0.54194},{features:[[8,14,4,3,-1.],[8,15,4,1,3.]],threshold:2.2582e-003,right_val:0.60274,left_val:0.48158},{features:[[0,15,14,4,-1.],[0,17,14,2,2.]],threshold:-6.7811e-003,right_val:0.51833,left_val:0.39803},{features:[[1,14,18,6,-1.],[1,17,18,3,2.]],threshold:0.011154,right_val:0.41888,left_val:0.54312},{features:[[0,0,10,6,-1.],[0,0,5,3,2.],[5,3,5,3,2.]],threshold:0.043162,right_val:0.6523,left_val:0.47382}],threshold:105.76}],size:[20,20],tilted:false};
+
+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> 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> 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 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 '' +
+ '
' +
+ '
' +
+ '
' +
+ '
' + msg + '
' +
+ '
' +
+ '
';
+};
+
+
+/**
+ * Mesasge for getting a webgl browser
+ * @type {string}
+ */
+// const GET_A_WEBGL_BROWSER = '' +
+// 'This page requires a browser that supports WebGL. ' +
+// 'Click here to upgrade your browser.';
+
+
+/**
+ * Mesasge for need better hardware
+ * @type {string}
+ */
+// const OTHER_PROBLEM = '' +
+// "It doesn't appear your computer can support WebGL. " +
+// 'Click here for more information.';
+
+
+/**
+ * Creates a webgl context. If creation fails it will
+ * change the contents of the container of the