Update app.py

app.py

@@ -1,5 +1,4 @@
 import os
-import tempfile
 import gradio as gr
 
 from audio_separator.separator import Separator
@@ -111,145 +110,140 @@ def rename_stems(input_file, output_dir, stems, output_format):
 def roformer_separator(audio, model_key, seg_size, overlap, model_dir, out_dir, out_format, norm_thresh, amp_thresh, progress=gr.Progress()):
     """Separate audio using Roformer model."""
     model = ROFORMER_MODELS[model_key]
-    with tempfile.TemporaryDirectory() as tmp_dir:
-        separator = Separator(
-            model_file_dir=model_dir,
-            output_dir=tmp_dir,
-            output_format=out_format,
-            normalization_threshold=norm_thresh,
-            amplification_threshold=amp_thresh,
-            mdxc_params={
-                "batch_size": 1,
-                "segment_size": seg_size,
-                "overlap": overlap,
-            }
-        )
-
-        progress(0.2, desc="Model loaded")
-        separator.load_model(model_filename=model)
-
-        progress(0.7, desc="Audio separated")
-        separation = separator.separate(audio)
-
-        progress(0.9, desc="Stems renamed")
-        stems = rename_stems(audio, out_dir, separation, out_format)
-
-        return stems[0], stems[1]
+    separator = Separator(
+        model_file_dir=model_dir,
+        output_dir=out_dir,
+        output_format=out_format,
+        normalization_threshold=norm_thresh,
+        amplification_threshold=amp_thresh,
+        mdxc_params={
+            "batch_size": 1,
+            "segment_size": seg_size,
+            "overlap": overlap,
+        }
+    )
+
+    progress(0.2, desc="Model loaded")
+    separator.load_model(model_filename=model)
+
+    progress(0.7, desc="Audio separated")
+    separation = separator.separate(audio)
+
+    progress(0.9, desc="Stems renamed")
+    stems = rename_stems(audio, out_dir, separation, out_format)
+
+    return stems[0], stems[1]
 
 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."""
-    with tempfile.TemporaryDirectory() as tmp_dir:
-        separator = Separator(
-            model_file_dir=model_dir,
-            output_dir=tmp_dir,
-            output_format=out_format,
-            normalization_threshold=norm_thresh,
-            amplification_threshold=amp_thresh,
-            mdxc_params={
-                "batch_size": 1,
-                "segment_size": seg_size,
-                "overlap": overlap,
-            }
-        )
-
-        progress(0.2, desc="Model loaded")
-        separator.load_model(model_filename=model)
-
-        progress(0.7, desc="Audio separated")
-        separation = separator.separate(audio)
-
-        progress(0.9, desc="Stems renamed")
-        stems = rename_stems(audio, out_dir, separation, out_format)
-
-        return stems[0], stems[1]
+    separator = Separator(
+        model_file_dir=model_dir,
+        output_dir=out_dir,
+        output_format=out_format,
+        normalization_threshold=norm_thresh,
+        amplification_threshold=amp_thresh,
+        mdxc_params={
+            "batch_size": 1,
+            "segment_size": seg_size,
+            "overlap": overlap,
+        }
+    )
+
+    progress(0.2, desc="Model loaded")
+    separator.load_model(model_filename=model)
+
+    progress(0.7, desc="Audio separated")
+    separation = separator.separate(audio)
+
+    progress(0.9, desc="Stems renamed")
+    stems = rename_stems(audio, out_dir, separation, out_format)
+
+    return stems[0], stems[1]
 
 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."""
-    with tempfile.TemporaryDirectory() as tmp_dir:
-        separator = Separator(
-            model_file_dir=model_dir,
-            output_dir=tmp_dir,
-            output_format=out_format,
-            normalization_threshold=norm_thresh,
-            amplification_threshold=amp_thresh,
-            mdx_params={
-                "batch_size": 1,
-                "hop_length": hop_length,
-                "segment_size": seg_size,
-                "overlap": overlap,
-                "enable_denoise": denoise,
-            }
-        )
-
-        progress(0.2, desc="Model loaded")
-        separator.load_model(model_filename=model)
-
-        progress(0.7, desc="Audio separated")
-        separation = separator.separate(audio)
-
-        progress(0.9, desc="Stems renamed")
-        stems = rename_stems(audio, out_dir, separation, out_format)
-
-        return stems[0], stems[1]
+    separator = Separator(
+        model_file_dir=model_dir,
+        output_dir=out_dir,
+        output_format=out_format,
+        normalization_threshold=norm_thresh,
+        amplification_threshold=amp_thresh,
+        mdx_params={
+            "batch_size": 1,
+            "hop_length": hop_length,
+            "segment_size": seg_size,
+            "overlap": overlap,
+            "enable_denoise": denoise,
+        }
+    )
+
+    progress(0.2, desc="Model loaded")
+    separator.load_model(model_filename=model)
+
+    progress(0.7, desc="Audio separated")
+    separation = separator.separate(audio)
+
+    progress(0.9, desc="Stems renamed")
+    stems = rename_stems(audio, out_dir, separation, out_format)
+
+    return stems[0], stems[1]
 
 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."""
-    with tempfile.TemporaryDirectory() as tmp_dir:
-        separator = Separator(
-            model_file_dir=model_dir,
-            output_dir=tmp_dir,
-            output_format=out_format,
-            normalization_threshold=norm_thresh,
-            amplification_threshold=amp_thresh,
-            vr_params={
-                "batch_size": 1,
-                "window_size": window_size,
-                "aggression": aggression,
-                "enable_tta": tta,
-                "enable_post_process": post_process,
-                "post_process_threshold": post_process_threshold,
-                "high_end_process": high_end_process,
-            }
-        )
-
-        progress(0.2, desc="Model loaded")
-        separator.load_model(model_filename=model)
-
-        progress(0.7, desc="Audio separated")
-        separation = separator.separate(audio)
-
-        progress(0.9, desc="Stems renamed")
-        stems = rename_stems(audio, out_dir, separation, out_format)
-
-        return stems[0], stems[1]
+    separator = Separator(
+        model_file_dir=model_dir,
+        output_dir=out_dir,
+        output_format=out_format,
+        normalization_threshold=norm_thresh,
+        amplification_threshold=amp_thresh,
+        vr_params={
+            "batch_size": 1,
+            "window_size": window_size,
+            "aggression": aggression,
+            "enable_tta": tta,
+            "enable_post_process": post_process,
+            "post_process_threshold": post_process_threshold,
+            "high_end_process": high_end_process,
+        }
+    )
+
+    progress(0.2, desc="Model loaded")
+    separator.load_model(model_filename=model)
+
+    progress(0.7, desc="Audio separated")
+    separation = separator.separate(audio)
+
+    progress(0.9, desc="Stems renamed")
+    stems = rename_stems(audio, out_dir, separation, out_format)
+
+    return stems[0], stems[1]
 
 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."""
-    with tempfile.TemporaryDirectory() as tmp_dir:
-        separator = Separator(
-            model_file_dir=model_dir,
-            output_dir=tmp_dir,
-            output_format=out_format,
-            normalization_threshold=norm_thresh,
-            amplification_threshold=amp_thresh,
-            demucs_params={
-                "segment_size": seg_size,
-                "shifts": shifts,
-                "overlap": overlap,
-                "segments_enabled": segments_enabled,
-            }
-        )
-
-        progress(0.2, desc="Model loaded")
-        separator.load_model(model_filename=model)
-
-        progress(0.7, desc="Audio separated")
-        separation = separator.separate(audio)
-
-        progress(0.9, desc="Stems renamed")
-        stems = rename_stems(audio, out_dir, separation, out_format)
-
-        return stems[0], stems[1], stems[2], stems[3]
+    separator = Separator(
+        model_file_dir=model_dir,
+        output_dir=out_dir,
+        output_format=out_format,
+        normalization_threshold=norm_thresh,
+        amplification_threshold=amp_thresh,
+        demucs_params={
+            "segment_size": seg_size,
+            "shifts": shifts,
+            "overlap": overlap,
+            "segments_enabled": segments_enabled,
+        }
+    )
+
+    progress(0.2, desc="Model loaded")
+    separator.load_model(model_filename=model)
+
+    progress(0.7, desc="Audio separated")
+    separation = separator.separate(audio)
+
+    progress(0.9, desc="Stems renamed")
+    stems = rename_stems(audio, out_dir, separation, out_format)
+
+    return stems[0], stems[1], stems[2], stems[3]
 
 with gr.Blocks(title="🎵 PolUVR - Politrees 🎵", css="footer{display:none !important}") as app:
     gr.Markdown("<h1> Audio-Separator by Politrees </h1>")