Update app.py

app.py

@@ -3,19 +3,33 @@ import torchaudio
 from sgmse.model import ScoreModel
 import gradio as gr
 from sgmse.util.other import pad_spec
+
+# Define the necessary arguments
+class Args:
+    device = 'cpu'  # or 'cuda' if GPU is available and enabled in the environment
+    corrector = 'langevin'  # Define your corrector method
+    N = 50  # Example value for number of steps
+    corrector_steps = 1  # Number of steps for the corrector
+    snr = 0.1  # Signal-to-noise ratio value for the corrector
+    pad_mode = 'reflect'  # Pad mode for spectrogram padding
+
+args = Args()
+
 # Load the pre-trained model
 model = ScoreModel.load_from_checkpoint("https://huggingface.co/sp-uhh/speech-enhancement-sgmse/resolve/main/train_vb_29nqe0uh_epoch%3D115.ckpt")
+
 def enhance_speech(audio_file):
     # Load and process the audio file
     y, sr = torchaudio.load(audio_file)
-T_orig = y.size(1)   
-# Normalize
+    T_orig = y.size(1)   
+
+    # Normalize
     norm_factor = y.abs().max()
     y = y / norm_factor
     
     # Prepare DNN input
     Y = torch.unsqueeze(model._forward_transform(model._stft(y.to(args.device))), 0)
-    Y = pad_spec(Y, mode=pad_mode)
+    Y = pad_spec(Y, mode=args.pad_mode)
     
     # Reverse sampling
     sampler = model.get_pc_sampler(
@@ -25,7 +39,8 @@ T_orig = y.size(1)
     
     # Backward transform in time domain
     x_hat = model.to_audio(sample.squeeze(), T_orig)
-# Renormalize
+
+    # Renormalize
     x_hat = x_hat * norm_factor
     
     # Save the enhanced audio
@@ -33,12 +48,13 @@ T_orig = y.size(1)
     torchaudio.save(output_file, x_hat.cpu().numpy(), sr)
     
     return output_file
+
 # Gradio interface setup
 inputs = gr.Audio(label="Input Audio", type="filepath")
 outputs = gr.Audio(label="Output Audio", type="filepath")
 title = "Speech Enhancement using SGMSE"
 description = "This Gradio demo uses the SGMSE model for speech enhancement. Upload your audio file to enhance it."
 article = "<p style='text-align: center'><a href='https://huggingface.co/SP-UHH/speech-enhancement-sgmse' target='_blank'>Model Card</a></p>"
-# Launch without share=True (as it's not supported on Hugging Face Spaces)
-gr.Interface(fn=enhance_speech, inputs=inputs, outputs=outputs, title=title, description=description, article=article).launch(
 
+# Launch without share=True (as it's not supported on Hugging Face Spaces)
+gr.Interface(fn=enhance_speech, inputs=inputs, outputs=outputs, title=title, description=description, article=article).launch()