Fix: Corrected shape handling for separated sources, extracting each source as a separate 1D array

src/separation/convtasnet_wrapper.py

@@ -27,9 +27,13 @@ def separate(audio, model_name='mpariente/ConvTasNet_WHAM!_sepclean'):
         with torch.no_grad():
             separated_sources = model(audio_tensor)
         
-        # Convert separated sources to NumPy arrays and remove batch dimension
-        separated_sources_np = [src.squeeze(0).cpu().numpy() for src in separated_sources]
+        # Remove batch dimension
+        separated_sources = separated_sources.squeeze(0)  # Shape: (num_sources, num_samples)
         
-        return separated_sources_np
+        # Split into list of sources
+        separated_sources_np = separated_sources.cpu().numpy()  # Convert to NumPy
+        separated_sources_list = [separated_sources_np[i, :] for i in range(separated_sources_np.shape[0])]
+        
+        return separated_sources_list
     except Exception as e:
         raise RuntimeError(f"Error during separation: {e}")

test.py

@@ -14,7 +14,6 @@ def main(input_audio_path, output_dir, model_name="mpariente/ConvTasNet_WHAM!_se
         
         separated_sources = separate(audio, model_name)
         print(f"Separated {len(separated_sources)} sources")
-        print("Separated sources are", separated_sources)
         
         for i, source in enumerate(separated_sources):
             output_path = os.path.join(output_dir, f"source_{i+1}.wav")
@@ -26,7 +25,7 @@ def main(input_audio_path, output_dir, model_name="mpariente/ConvTasNet_WHAM!_se
         
 
 if __name__ == "__main__":
-    input_audio_path = "/home/joel/Downloads/female_female_speech.wav"  
+    input_audio_path = "/home/joel/Downloads/wham/female-female-mixture.wav"  
     output_dir = "/tmp/convtasnet"  
     main(input_audio_path, output_dir)