Esempio n. 1
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                # Filtre sur les séquences trop courtes et sur la présence de plusieurs personnes
                if Candidat[6]>=1 and Candidat[2]<2 and Candidat[3]<2:
                    Sequences.append(Candidat)
                

from sklearn.model_selection import train_test_split

ratio=0.7
Train, Test = train_test_split(Sequences, train_size=ratio, random_state = 42)  

importlib.reload(Fenetrage)
NumSeqTrain,Audio_Y,Video_Y,FenetresTrain=Fenetrage.Decoupe(Train,0.5,1)
NumSeqTest,Audio_TY,Video_TY,FenetresTest=Fenetrage.Decoupe(Test,0.5,1)

importlib.reload(Audio)
Audio_Features=Audio.Features_Audio(FenetresTrain,1,0.5,center=False)
importlib.reload(Video)
Video_Features=Video.Features_Video(FenetresTrain,1,cadree=True)

Audio_Test_Features=Audio.Features_Audio(FenetresTest,1,0.5,center=False)
Video_Test_Features=Video.Features_Video(FenetresTest,1,cadree=True)

# Concaténation et normalisation des features audio et Video


Features=np.hstack((Audio_Features,Video_Features))
TestFeatures=np.hstack((Audio_Test_Features,Video_Test_Features))

Features=Classifier.NormaliseTrain(Features)
TestFeatures=Classifier.NormaliseAutres(TestFeatures)
Esempio n. 2
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Oldfmax=Audio.fmax
Oldn_mfcc=Audio.n_mfcc
Oldn_MEL=Audio.n_MEL
Oldf_anal=f_anal
OldRecouvrement=Recouvrement

while True:    
        if TailleFenetre!=Last_TailleFenetre:
            importlib.reload(Fenetrage)
            NumSeqT1,Audio_Y1,Video_Y1,F1=Fenetrage.Decoupe(T1,0.5,TailleFenetre)
            NumSeqT2,Audio_Y2,Video_Y2,F2=Fenetrage.Decoupe(T2,0.5,TailleFenetre)
            NumSeqT3,Audio_Y3,Video_Y3,F3=Fenetrage.Decoupe(T3,0.5,TailleFenetre)
            Last_TailleFenetre=TailleFenetre

        Audio_F1=Audio.Features_Audio(F1,TailleFenetre,
                                            1/Recouvrement,center=False,
                                            fen_anal=f_anal)
        Audio_F2=Audio.Features_Audio(F2,TailleFenetre,
                                             1/Recouvrement,
                                             center=False,fen_anal=f_anal)
        Audio_F3=Audio.Features_Audio(F3,TailleFenetre,
                                             1/Recouvrement,
                                             center=False,fen_anal=f_anal)


        # Concaténation et normalisation des features audio et Video
        #Features=np.hstack((Audio_Features,Video_Features))
        #TestFeatures=np.hstack((Audio_Test_Features,Video_Test_Features))
            
        Fea12=np.copy(np.vstack((Audio_F1,Audio_F2)))
        Fea23=np.copy(np.vstack((Audio_F2,Audio_F3)))