resampling if sr is not target sr

enhancement.py

@@ -6,6 +6,7 @@ from soundfile import write
 from torchaudio import load
 from os.path import join, dirname
 from argparse import ArgumentParser
+from librosa import resample
 
 # Set CUDA architecture list
 from sgmse.util.other import set_torch_cuda_arch_list
@@ -38,10 +39,10 @@ if __name__ == '__main__':
 
     # Check if the model is trained on 48 kHz data
     if model.backbone == 'ncsnpp_48k':
-        sr = 48000
+        target_sr = 48000
         pad_mode = "reflection"
     else:
-        sr = 16000
+        target_sr = 16000
         pad_mode = "zero_pad"
 
     # Enhance files
@@ -50,7 +51,12 @@ if __name__ == '__main__':
         filename = noisy_file.replace(args.test_dir, "")[1:] # Remove the first character which is a slash
         
         # Load wav
-        y, _ = load(noisy_file) 
+        y, sr = load(noisy_file)
+
+        # Resample if necessary
+        if sr != target_sr:
+            y = resample(y, orig_sr=sr, target_sr=target_sr)
+
         T_orig = y.size(1)   
 
         # Normalize
@@ -75,4 +81,4 @@ if __name__ == '__main__':
 
         # Write enhanced wav file
         makedirs(dirname(join(args.enhanced_dir, filename)), exist_ok=True)
-        write(join(args.enhanced_dir, filename), x_hat.cpu().numpy(), sr)
+        write(join(args.enhanced_dir, filename), x_hat.cpu().numpy(), target_sr)