Update app.py

app.py

@@ -1,4 +1,5 @@
 import os
+import logging
 import gradio as gr
 
 from audio_separator.separator import Separator
@@ -103,8 +104,7 @@ def rename_stems(input_file, output_dir, stems, output_format):
     for i, stem in enumerate(stems):
         new_name = f"{base_name}_(Stem{i+1}).{output_format}"
         new_path = os.path.join(output_dir, new_name)
-        print(f"Renaming {stem} to {new_path}")
-        os.rename(stem, new_path)
+        os.rename(os.path.join(output_dir, stem), new_path)
         renamed_stems.append(new_path)
     return renamed_stems
 
@@ -112,6 +112,7 @@ def roformer_separator(audio, model_key, seg_size, overlap, model_dir, out_dir,
     """Separate audio using Roformer model."""
     model = ROFORMER_MODELS[model_key]
     separator = Separator(
+        log_level=logging.WARNING,
         model_file_dir=model_dir,
         output_dir=out_dir,
         output_format=out_format,
@@ -130,8 +131,6 @@ def roformer_separator(audio, model_key, seg_size, overlap, model_dir, out_dir,
     progress(0.7, desc="Audio separated")
     separation = separator.separate(audio)
 
-    print(f"Separation result: {separation}")
-
     progress(0.9, desc="Stems renamed")
     stems = rename_stems(audio, out_dir, separation, out_format)
 
@@ -140,6 +139,7 @@ def roformer_separator(audio, model_key, seg_size, overlap, model_dir, out_dir,
 def mdx23c_separator(audio, model, seg_size, overlap, model_dir, out_dir, out_format, norm_thresh, amp_thresh, progress=gr.Progress()):
     """Separate audio using MDX23C model."""
     separator = Separator(
+        log_level=logging.WARNING,
         model_file_dir=model_dir,
         output_dir=out_dir,
         output_format=out_format,
@@ -166,6 +166,7 @@ def mdx23c_separator(audio, model, seg_size, overlap, model_dir, out_dir, out_fo
 def mdx_separator(audio, model, hop_length, seg_size, overlap, denoise, model_dir, out_dir, out_format, norm_thresh, amp_thresh, progress=gr.Progress()):
     """Separate audio using MDX-NET model."""
     separator = Separator(
+        log_level=logging.WARNING,
         model_file_dir=model_dir,
         output_dir=out_dir,
         output_format=out_format,
@@ -194,6 +195,7 @@ def mdx_separator(audio, model, hop_length, seg_size, overlap, denoise, model_di
 def vr_separator(audio, model, window_size, aggression, tta, post_process, post_process_threshold, high_end_process, model_dir, out_dir, out_format, norm_thresh, amp_thresh, progress=gr.Progress()):
     """Separate audio using VR ARCH model."""
     separator = Separator(
+        log_level=logging.WARNING,
         model_file_dir=model_dir,
         output_dir=out_dir,
         output_format=out_format,
@@ -224,6 +226,7 @@ def vr_separator(audio, model, window_size, aggression, tta, post_process, post_
 def demucs_separator(audio, model, seg_size, shifts, overlap, segments_enabled, model_dir, out_dir, out_format, norm_thresh, amp_thresh, progress=gr.Progress()):
     """Separate audio using Demucs model."""
     separator = Separator(
+        log_level=logging.WARNING,
         model_file_dir=model_dir,
         output_dir=out_dir,
         output_format=out_format,
@@ -276,7 +279,7 @@ with gr.Blocks(
                 roformer_model = gr.Dropdown(label="Select the Model", choices=list(ROFORMER_MODELS.keys()))
             with gr.Row():
                 roformer_seg_size = gr.Slider(minimum=32, maximum=4000, step=32, value=256, label="Segment Size", info="Larger consumes more resources, but may give better results.")
-                roformer_overlap = gr.Slider(minimum=2, maximum=4, step=1, value=4, label="Overlap", info="Amount of overlap between prediction windows.")
+                roformer_overlap = gr.Slider(minimum=2, maximum=10, step=1, value=8, label="Overlap", info="Amount of overlap between prediction windows.")
         with gr.Row():
             roformer_audio = gr.Audio(label="Input Audio", type="filepath")
         with gr.Row():
@@ -440,4 +443,4 @@ with gr.Blocks(
         outputs=[demucs_stem1, demucs_stem2, demucs_stem3, demucs_stem4],
     )
 
-app.launch()
+app.launch(share=True)