Upload app.py.py

app.py.py

@@ -0,0 +1,41 @@
+import torch
+import os
+#os.system('pip install git+https://github.com/peterwilli/audio-maister.git')
+import gradio as gr
+
+from audiomaister import VoiceFixer
+from audiomaister.models.gs_audiomaister import AudioMaister
+
+USE_CUDA = torch.cuda.is_available()
+
+def load_default_weights():
+    from huggingface_hub import hf_hub_download
+    from pathlib import Path
+
+    REPO_ID = "peterwilli/audio-maister"
+    print(f"Loading standard model weight at {REPO_ID}")
+    MODEL_FILE_NAME = "audiomaister_v1.ckpt"
+    checkpoint_path = hf_hub_download(repo_id=REPO_ID, filename=MODEL_FILE_NAME)
+    return checkpoint_path
+
+def inference(input_file, **kwargs):
+    checkpoint = load_default_weights()
+    state = torch.load(checkpoint)
+    
+    main_model = VoiceFixer(state['hparams'], 1, 'vocals')
+    main_model.load_state_dict(state['weights'])
+    
+    inference_model = AudioMaister(main_model)
+    inference_model.restore(input=input_file, output="out.wav", mode=0)
+    
+    if USE_CUDA:
+        main_model.to('cuda')
+        inference_model.to('cuda')
+
+    return "out.wav"
+
+gr.Interface(
+    fn=inference, 
+    inputs=gr.Audio(type="filepath", source="upload"),
+    outputs="audio"
+).launch(debug=True)