Update app.py
Browse files
app.py
CHANGED
@@ -18,13 +18,6 @@ import torchaudio
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from torch_pesq import PesqLoss
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pesq = PesqLoss(0.5,
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sample_rate=44100,
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mos = pesq.mos(reference, degraded)
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loss = pesq(reference, degraded)
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@st.cache
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def load_model():
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@@ -154,16 +147,25 @@ if st.button('Сгенерировать потери'):
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stoi_mass=[stoi_orig, stoi_lossy, stoi_enhanced]
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#if samplerate != 16000:
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# data_lossy = librosa.resample(data_lossy, orig_sr=48000, target_sr=16000)
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# data_clean = librosa.resample(data_clean, orig_sr=48000, target_sr=16000)
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# data_enhanced = librosa.resample(data_enhanced, orig_sr=48000, target_sr=16000)
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#
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#pesq_orig = pesq(fs = 16000, ref = data_clean, deg = data_clean, mode='nb')
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#pesq_lossy = pesq(fs = 16000, ref = data_clean, deg = data_lossy, mode='nb')
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#pesq_enhanced = pesq(fs = 16000, ref = data_clean, deg = data_enhanced, mode='nb')
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@@ -171,7 +173,7 @@ if st.button('Сгенерировать потери'):
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df['Audio'] = ['Clean', 'Lossy', 'Enhanced']
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df['STOI'] = stoi_mass
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from torch_pesq import PesqLoss
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@st.cache
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def load_model():
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stoi_mass=[stoi_orig, stoi_lossy, stoi_enhanced]
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#if samplerate != 16000:
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# data_lossy = librosa.resample(data_lossy, orig_sr=48000, target_sr=16000)
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# data_clean = librosa.resample(data_clean, orig_sr=48000, target_sr=16000)
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# data_enhanced = librosa.resample(data_enhanced, orig_sr=48000, target_sr=16000)
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#
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pesq = PesqLoss(0.5, sample_rate=48000)
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pesq_orig = pesq.mos(data_clean, data_clean)
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pesq_lossy = pesq.mos(data_clean, data_lossy)
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pesq_enhanced= pesq.mos(data_clean, data_enhanced)
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#pesq_orig = pesq(fs = 16000, ref = data_clean, deg = data_clean, mode='nb')
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#pesq_lossy = pesq(fs = 16000, ref = data_clean, deg = data_lossy, mode='nb')
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#pesq_enhanced = pesq(fs = 16000, ref = data_clean, deg = data_enhanced, mode='nb')
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psq_mas=[pesq_orig, pesq_lossy, pesq_enhanced]
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df['Audio'] = ['Clean', 'Lossy', 'Enhanced']
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df['PESQ'] = psq_mas
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df['STOI'] = stoi_mass
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