Fix spectrogram issue

app.py

@@ -89,7 +89,6 @@ def enhance(filepath, model_name):
 
         out = torch.cat(enhanced_chunks)[:len(x)].cpu().numpy()  # trim padding
 
-        out_wav = out.copy()
         # back to original rate
         if orig_sr != 16000:
             out = librosa.resample(out, orig_sr=16000, target_sr=orig_sr)
@@ -98,7 +97,6 @@ def enhance(filepath, model_name):
         peak = np.max(np.abs(out))
         if peak > 0.05:
             out = out / peak * 0.85
-            out_wav = out_wav / peak * 0.85
 
         # write file
         sf.write("enhanced.wav", out, orig_sr)
@@ -113,7 +111,7 @@ def enhance(filepath, model_name):
         axs[0].set_title("Noisy Spectrogram")
 
         # enhanced
-        D_clean = librosa.stft(out_wav, n_fft=512, hop_length=256)
+        D_clean = librosa.stft(out, n_fft=512, hop_length=256)
         S_clean = librosa.amplitude_to_db(np.abs(D_clean), ref=np.max)
         librosa.display.specshow(S_clean, sr=orig_sr, hop_length=256, x_axis="time", y_axis="hz", ax=axs[1], vmax=0)
         #librosa.display.specshow(S_clean, sr=16000, hop_length=512, x_axis="time", y_axis="hz", ax=axs[1], vmax=0)