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Update app_utils.py
Browse files- app_utils.py +24 -24
app_utils.py
CHANGED
@@ -108,7 +108,7 @@ def text_score(text):
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score=-prob*10
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else:
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score=prob*10
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print("from func:text_score————,text:",text,",score:",score)
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return text,score
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def speech_score(audio):
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@@ -137,21 +137,21 @@ def speech_score(audio):
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text_results += punc.punctuate(_result)[0]
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out_prob, score, index, text_lab = classifier.classify_batch(signal1)
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print("from func:speech_score————type and value of prob:")
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print(type(out_prob.squeeze(0).numpy()))
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print(out_prob.squeeze(0).numpy())
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print("from func:speech_score————type and value of resul_label:")
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print(type(text_lab[-1]))
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print(text_lab[-1])
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#return text_results, out_prob.squeeze(0).numpy(), text_lab[-1], Audio
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prob=out_prob.squeeze(0).numpy()
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#print(prob)
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score2=10*prob[0]-10*prob[1]
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print("from func:speech_score————score2:",score2)
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# print("from func:speech_score————",text_lab[-1])
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text,score1=text_score(text_results)
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# text_emo=str(get_text_score(text_results))
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print("from func:speech_score————text:",text,",score1:",score1)
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score=score1+score2
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@@ -268,11 +268,11 @@ def video_score(video):
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return None, None
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#for debug
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print("from func:video_score————")
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print(type(frames))
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print(frames)
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print(type(probs))
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print(probs)
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# to calculate scores
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nan=float('nan')
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s1 = 0
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@@ -304,14 +304,14 @@ def video_score(video):
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scores=[s1,s2,s3,s4,s5,s6,s7]
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scores_str=str(scores)
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score1=0*scores[0]-8*scores[1]+4*scores[2]+0*scores[3]+2*scores[4]+2*scores[5]+4*scores[6]
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print("from func:video_score————score1=",score1)
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print("from func:video_score————logs:")
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with open("local_data/data.txt",'a', encoding="utf8") as f:
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with open("local_data/data.txt",'r', encoding="utf8") as f:
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#trans the audio file
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@@ -322,10 +322,10 @@ def video_score(video):
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text,score2=speech_score(audio)
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print("from func:video_score————text:",text)
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score=score2+score1
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print("from func:video_score————score:",score)
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return text,score
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#######################################################################
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score=-prob*10
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else:
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score=prob*10
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# print("from func:text_score————,text:",text,",score:",score)
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return text,score
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def speech_score(audio):
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text_results += punc.punctuate(_result)[0]
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out_prob, score, index, text_lab = classifier.classify_batch(signal1)
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# print("from func:speech_score————type and value of prob:")
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# print(type(out_prob.squeeze(0).numpy()))
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# print(out_prob.squeeze(0).numpy())
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# print("from func:speech_score————type and value of resul_label:")
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# print(type(text_lab[-1]))
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# print(text_lab[-1])
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#return text_results, out_prob.squeeze(0).numpy(), text_lab[-1], Audio
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prob=out_prob.squeeze(0).numpy()
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#print(prob)
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score2=10*prob[0]-10*prob[1]
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# print("from func:speech_score————score2:",score2)
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# print("from func:speech_score————",text_lab[-1])
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text,score1=text_score(text_results)
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# # text_emo=str(get_text_score(text_results))
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# print("from func:speech_score————text:",text,",score1:",score1)
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score=score1+score2
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return None, None
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#for debug
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#print("from func:video_score————")
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# print(type(frames))
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# print(frames)
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# print(type(probs))
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# print(probs)
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# to calculate scores
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nan=float('nan')
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s1 = 0
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scores=[s1,s2,s3,s4,s5,s6,s7]
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scores_str=str(scores)
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score1=0*scores[0]-8*scores[1]+4*scores[2]+0*scores[3]+2*scores[4]+2*scores[5]+4*scores[6]
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#print("from func:video_score————score1=",score1)
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#print("from func:video_score————logs:")
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# with open("local_data/data.txt",'a', encoding="utf8") as f:
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# f.write(scores_str+'\n')
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# with open("local_data/data.txt",'r', encoding="utf8") as f:
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# for i in f:
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# print(i)
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#trans the audio file
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text,score2=speech_score(audio)
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#print("from func:video_score————text:",text)
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score=score2+score1
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#print("from func:video_score————score:",score)
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return text,score
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#######################################################################
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