Update app.py

app.py

@@ -136,27 +136,27 @@ if st.button('Сгенерировать потери'):
 
 
     stoi = STOI(48000)
-    stoi_orig = np.array(stoi(data_clean, data_clean))
-    stoi_lossy = np.array(stoi(data_clean, data_lossy))
-    stoi_enhanced = np.array(stoi(data_clean, data_enhanced))
+    stoi_orig = round(float(stoi(data_clean, data_clean)),3)
+    stoi_lossy = round(float(stoi(data_clean, data_lossy)),5)
+    stoi_enhanced = round(float(stoi(data_clean, data_enhanced)),5)
     stoi_mass=[stoi_orig, stoi_lossy, stoi_enhanced]
 
 
-    """pesq = PESQ(16000, 'nb')
-    data_clean = data_clean.cpu().numpy()
-    data_lossy = data_lossy.detach().cpu().numpy()
-    data_enhanced = data_enhanced.cpu().numpy()
+    #pesq = PESQ(16000, 'nb')
+    #data_clean = data_clean.cpu().numpy()
+    #data_lossy = data_lossy.detach().cpu().numpy()
+    #data_enhanced = data_enhanced.cpu().numpy()
 
-    if samplerate != 16000:
-        data_lossy = librosa.resample(data_lossy, orig_sr=48000, target_sr=16000)
-        data_clean = librosa.resample(data_clean, orig_sr=48000, target_sr=16000)
-        data_enhanced = librosa.resample(data_enhanced, orig_sr=48000, target_sr=16000)
+    #if samplerate != 16000:
+    #    data_lossy = librosa.resample(data_lossy, orig_sr=48000, target_sr=16000)
+    #    data_clean = librosa.resample(data_clean, orig_sr=48000, target_sr=16000)
+    #    data_enhanced = librosa.resample(data_enhanced, orig_sr=48000, target_sr=16000)
 
-        pesq_orig = np.array(pesq(torch.tensor(data_clean), torch.tensor(data_clean)))
-        pesq_lossy = np.array(pesq(torch.tensor(data_lossy), torch.tensor(data_clean)))
-        pesq_enhanced = np.array(pesq(torch.tensor(data_enhanced), torch.tensor(data_clean)))
+    #    pesq_orig = np.array(pesq(torch.tensor(data_clean), torch.tensor(data_clean)))
+    #    pesq_lossy = np.array(pesq(torch.tensor(data_lossy), torch.tensor(data_clean)))
+    #    pesq_enhanced = np.array(pesq(torch.tensor(data_enhanced), torch.tensor(data_clean)))
 
-    psq_mas=[pesq_orig, pesq_lossy, pesq_enhanced]"""
+    #psq_mas=[pesq_orig, pesq_lossy, pesq_enhanced]