added changes on checking similarity

base/api/librosa_run.py

@@ -0,0 +1,72 @@
+import librosa
+import librosa.display as display
+import matplotlib.pyplot as plt
+import os
+# from numpy import array
+from datetime import datetime
+
+from numpy.linalg import norm
+from dtw import dtw
+
+# import math
+
+import warnings
+warnings.filterwarnings("ignore")
+
+def dot(A,B): 
+    return (sum(a*b for a,b in zip(A,B)))
+
+def cosine_similarity(a,b):
+    return dot(a,b) / ( (dot(a,a) **.5) * (dot(b,b) ** .5) )
+
+def fungsi_librosa(sound_url1,sound_url2):
+  
+	print(sound_url1)
+	print(sound_url2)
+  
+	y1, sr1 = librosa.load(sound_url1)
+	y2, sr2 = librosa.load(sound_url2)
+		
+	mfcc1 = librosa.feature.mfcc(y1,sr1) 
+	mfcc2 = librosa.feature.mfcc(y2,sr2)
+
+	
+	path = 'static/created_image/'
+	if not os.path.exists(path):
+		os.makedirs(path)
+  
+	today_date = datetime.now().strftime("%Y-%m-%d")
+  
+  
+	path = path + today_date+ '/'
+	path_nya = path
+ 
+	if not os.path.exists(path):
+		os.makedirs(path)
+  
+	hour_min_sec = datetime.now().strftime("%H-%M-%S")
+  
+	plt.figure(figsize=(14, 5))
+	display.waveshow(y1, sr=sr1)
+	plt.savefig(path+'spec'+hour_min_sec+'.png')
+
+	plt.figure(figsize=(14, 5))
+	display.waveshow(y2, sr=sr2)
+	plt.savefig(path+'spec1'+hour_min_sec+'.png')
+ 
+	dist, cost, acc_cost, path = dtw(mfcc1.T, mfcc2.T, dist=lambda x, y: norm(x - y, ord=1))
+ 
+	array1 = []
+	for nums in mfcc1:
+			for val in nums:
+					array1.append(val)
+        
+	array2 = []
+	for nums in mfcc2:
+			for val in nums:
+					array2.append(val)
+ 
+	cosine_similaritynya = cosine_similarity(array1, array2) 
+ 
+	return {'dist': dist, 'cosine_similaritynya': cosine_similaritynya, 'path': path_nya, 'hour_min_sec': hour_min_sec}
+