feat: cover song identification via stream

I found a tuto with the streaming way to performe cover song identification.
I also add a way to download some sound with youtube dl.
to download musique now just type:

youtube-dl --config-location config_youtube-dl

cover_song_identification.py

@@ -18,19 +18,25 @@ import essentia.standard as estd
 from essentia.pytools.spectral import hpcpgram
 
 import IPython
+#IPython.display.Audio('./en_vogue+Funky_Divas+09-Yesterday.mp3')
+#IPython.display.Audio('./beatles+1+11-Yesterday.mp3')
+#IPython.display.Audio('./aerosmith+Live_Bootleg+06-Come_Together.mp3')
 
 yesterday_original = 'audio/Yesterday (Remastered 2009).mp3'
 yesterday_cover_01 = 'audio/Yesterday - The Beatles - Connie Talbot (Cover).mp3'
-different_song = 'audio/Jacques Brel - Ne Me Quitte Pas.mp3'
+yesterday_cover_02 = 'audio/The Beatles - Yesterday Saxophone Cover Alexandra Ilieva Thomann.mp3'
+different_song = 'audio/Bella Poarch - Build a Btch (Official Music Video).mp3'
 
 IPython.display.Audio(yesterday_original)
 IPython.display.Audio(yesterday_cover_01)
+IPython.display.Audio(yesterday_cover_02)
 IPython.display.Audio(different_song)
 
 # query cover song
 original_song = estd.MonoLoader(filename=yesterday_original, sampleRate=32000)()
 
 true_cover_01 = estd.MonoLoader(filename=yesterday_cover_01, sampleRate=32000)()
+true_cover_02 = estd.MonoLoader(filename=yesterday_cover_02, sampleRate=32000)()
 
 # wrong match
 false_cover_1 = estd.MonoLoader(filename=different_song, sampleRate=32000)()
@@ -40,6 +46,7 @@ false_cover_1 = estd.MonoLoader(filename=different_song, sampleRate=32000)()
 query_hpcp = hpcpgram(original_song, sampleRate=32000)
 
 true_cover_hpcp_1 = hpcpgram(true_cover_01, sampleRate=32000)
+true_cover_hpcp_2 = hpcpgram(true_cover_02, sampleRate=32000)
 
 false_cover_hpcp = hpcpgram(false_cover_1, sampleRate=32000)
 
@@ -77,6 +84,15 @@ plt.ylabel('Yesterday - The Beatles')
 plt.imshow(true_pair_crp_1, origin='lower')
 
 
+true_pair_crp_2 = crp(query_hpcp, true_cover_hpcp_2)
+
+fig = plt.gcf()
+fig.set_size_inches(15.5, 5.5)
+
+plt.title('Cross recurrent plot [1]')
+plt.xlabel('Yesterday accapella cover')
+plt.ylabel('Yesterday - The Beatles')
+plt.imshow(true_pair_crp_2, origin='lower')
 
 
 
@@ -138,6 +154,23 @@ plt.imshow(score_matrix, origin='lower')
 
 print('Cover song similarity distance: %s' % distance)
 
+## other similar
+
+score_matrix, distance = estd.CoverSongSimilarity(disOnset=0.5,
+                                                  disExtension=0.5,
+                                                  alignmentType='serra09',
+                                                  distanceType='asymmetric')(true_pair_crp_2)
+
+fig = plt.gcf()
+fig.set_size_inches(15.5, 5.5)
+
+plt.title('Cover song similarity distance: %s' % distance)
+plt.xlabel('Yesterday accapella cover')
+plt.ylabel('Yesterday - The Beatles')
+plt.imshow(score_matrix, origin='lower')
+
+print('Cover song similarity distance: %s' % distance)
+
 ## Computing cover song similarity distance between Yesterday - accapella cover and Come Together cover - The Aerosmith.
 
 score_matrix, distance = estd.CoverSongSimilarity(disOnset=0.5,

cover_song_stream.py

@@ -10,10 +10,9 @@ from essentia.pytools.spectral import hpcpgram
 
 yesterday_original = 'audio/Yesterday (Remastered 2009).mp3'
 yesterday_cover_01 = 'audio/Yesterday - The Beatles - Connie Talbot (Cover).mp3'
-wrong_song         = 'audio/Jacques Brel - Ne Me Quitte Pas.mp3'
+wrong_song         = 'audio/Bella Poarch - Build a Btch (Official Music Video).mp3'
 
-song_reference = yesterday_original	# the original song analysed in normal mode
-song_streaming = wrong_song		# the song get in stream mode to compare to reference
+song_reference = yesterday_original
 
 # query cover song
 original_song = estd.MonoLoader(filename=song_reference, sampleRate=32000)()
@@ -28,10 +27,11 @@ true_cover_hpcp = hpcpgram(original_song, sampleRate=32000)
 import essentia.streaming as estr
 from essentia import array, run, Pool
 
+query_filename = wrong_song
 
 # Let's instantiate all the required essentia streaming algorithms
 
-audio = estr.MonoLoader(filename=song_streaming, sampleRate=32000)
+audio = estr.MonoLoader(filename=query_filename, sampleRate=32000)
   
 frame_cutter = estr.FrameCutter(frameSize=4096, hopSize=2048)
 

rm_mp3.sh

@@ -1,2 +0,0 @@
-git filter-branch --force --index-filter 'git rm --cached --ignore-unmatch "*.mp3"' --prune-empty --tag-name-filter cat -- --all
-

todo

@@ -48,7 +48,7 @@ Ce qu'il reste a faire:
     * avoir un input type micro
     * avoir une entree avec jack (jackd)
     * Faire tourner plusieur processus pour pouvoir annalyser plusieurs track en meme temps.
-    * ET VOILA CA DEVRAIT ETRE BON =)
+    * 
 
 1) un scritp qui telecharge les son: