Spaces:
Running
on
Zero
Running
on
Zero
Update inference_gradio.py
Browse files- inference_gradio.py +6 -2
inference_gradio.py
CHANGED
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@@ -46,7 +46,7 @@ class UVR5:
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# Keep paths as strings; actual model is loaded lazily.
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self.model_dir = str(model_dir)
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self.code_dir = str(code_dir)
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self.model =
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self.device = "cpu"
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def load_model(self, device: str = "cpu"):
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@@ -56,7 +56,10 @@ class UVR5:
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if self.code_dir not in sys.path:
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sys.path.append(self.code_dir)
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from multiprocess_cuda_infer import ModelData, Inference
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model_path = os.path.join(self.model_dir, "Kim_Vocal_1.onnx")
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@@ -82,6 +85,7 @@ class UVR5:
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def denoise(self, audio_info):
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print("denoise UVR5: ", audio_info)
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# # On Spaces, force CPU; locally prefer CUDA if available.
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input_audio = load_wav(audio_info, sr=44100, channel=2)
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output_audio = self.model.demix_base({0: input_audio.squeeze()}, is_match_mix=False, device="cpu")
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return output_audio.squeeze().T.cpu().numpy(), 44100
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# Keep paths as strings; actual model is loaded lazily.
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self.model_dir = str(model_dir)
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self.code_dir = str(code_dir)
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self.model = None
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self.device = "cpu"
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def load_model(self, device: str = "cpu"):
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if self.code_dir not in sys.path:
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sys.path.append(self.code_dir)
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if self.model is not None:
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return self.model
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from multiprocess_cuda_infer import ModelData, Inference
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model_path = os.path.join(self.model_dir, "Kim_Vocal_1.onnx")
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def denoise(self, audio_info):
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print("denoise UVR5: ", audio_info)
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# # On Spaces, force CPU; locally prefer CUDA if available.
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self.model = self.load_model()
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input_audio = load_wav(audio_info, sr=44100, channel=2)
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output_audio = self.model.demix_base({0: input_audio.squeeze()}, is_match_mix=False, device="cpu")
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return output_audio.squeeze().T.cpu().numpy(), 44100
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