Fix default

app.py

@@ -18,7 +18,7 @@ from df.enhance import enhance, init_df, load_audio, save_audio
 from df.utils import resample
 
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-model, df, _ = init_df()
+model, df, _ = init_df(config_allow_defaults=True)
 model = model.to(device=device).eval()
 
 
@@ -41,6 +41,7 @@ def mix_at_snr(clean, noise, snr, eps=1e-10):
     if noise.shape[1] < clean.shape[1]:
         noise = noise.repeat((1, int(math.ceil(clean.shape[1] / noise.shape[1]))))
     max_start = int(noise.shape[1] - clean.shape[1])
+    ic(max_start)
     start = torch.randint(0, max_start, ()).item()
     logger.debug(f"start: {start}, {clean.shape}")
     noise = noise[:, start : start + clean.shape[1]]
@@ -64,7 +65,7 @@ def load_audio_gradio(
     if audio_or_file is None:
         return None
     if isinstance(audio_or_file, str):
-        if  audio_or_file.lower()=="none":
+        if audio_or_file.lower() == "none":
             return None
         # First try default format
         audio, meta = load_audio(audio_or_file, sr)
@@ -92,11 +93,10 @@ def mix_and_denoise(
     if noise_fn is None:
         noise_fn = "samples/dkitchen.wav"
     meta = AudioMetaData(-1, -1, -1, -1, "")
-    if speech_upl is not None and "none" not in speech_upl:
-        speech_file = "samples/p232_013_clean.wav"
-        if speech_upl is not None and "none" not in speech_upl:
-            speech_file = speech_upl
-        speech, meta = load_audio(speech_file, sr)
+    if speech_rec is None and speech_upl is None:
+        speech, meta = load_audio("samples/p232_013_clean.wav", sr)
+    elif speech_upl is not None:
+        speech, meta = load_audio(speech_upl, sr)
     else:
         tmp = load_audio_gradio(speech_rec, sr)
         assert tmp is not None