prepare output type/sr

enhancer/inference.py

@@ -18,6 +18,8 @@ class Inference:
 
         if isinstance(audio,(np.ndarray,torch.Tensor)):
             assert sr is not None, "Invalid sampling rate!"
+            if len(audio.shape) == 1:
+                audio = audio.reshape(1,-1)
 
         if isinstance(audio,str):
             audio = Path(audio)
@@ -65,6 +67,8 @@ class Inference:
         window = get_window(window=window,Nx=data.shape[-1])
         window = torch.from_numpy(window).to(data.device)
         data *= window
+        step_size = window_size//2 if step_size is None else step_size
+
 
         data = data.permute(1,2,0)
         data = F.fold(data,
@@ -84,7 +88,18 @@ class Inference:
             raise FileExistsError(f"file {filename} already exists")
         else:
             wavfile.write(filename,rate=sr,data=waveform.detach().cpu())
-            
+
+    @staticmethod
+    def prepare_output(waveform:torch.Tensor, model_sampling_rate:int,
+        audio:Union[str,np.ndarray,torch.Tensor], sampling_rate:Optional[int]
+    ):
+        if isinstance(audio,np.ndarray):
+            waveform = waveform.detach().cpu().numpy()
+
+        if sampling_rate!=None:
+            waveform = Audio.resample_audio(waveform, sr=model_sampling_rate, target_sr=sampling_rate)
+
+        return waveform