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Run insightface on CPU and adapt the code to make it work with ZeroGPU (#1)
Browse files- Run insightface on CPU and adapt the code to make it work with ZeroGPU (20afb24ea6e0e9425221805f14242a6fb4fdfa6f)
- change it in cropper.py too (dfb1c4ae7bc5f65ec2369cad65a205dbd0ea5c55)
- Update app.py (f4ffec51a38d4a3fc5d70fc671b69d0e00e02742)
Co-authored-by: Apolinário from multimodal AI art <multimodalart@users.noreply.huggingface.co>
- app.py +12 -4
- src/utils/cropper.py +2 -2
- src/utils/landmark_runner.py +1 -1
app.py
CHANGED
@@ -35,6 +35,14 @@ gradio_pipeline = GradioPipeline(
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args=args
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)
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# assets
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title_md = "assets/gradio_title.md"
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example_portrait_dir = "assets/examples/source"
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@@ -111,7 +119,7 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
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with gr.Row():
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gr.Examples(
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examples=data_examples,
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fn=
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inputs=[
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image_input,
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video_input,
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@@ -121,7 +129,7 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
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],
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outputs=[output_image, output_image_paste_back],
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examples_per_page=5,
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cache_examples=
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)
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gr.Markdown(load_description("assets/gradio_description_retargeting.md"))
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with gr.Row():
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@@ -152,13 +160,13 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
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# binding functions for buttons
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process_button_retargeting.click(
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# fn=gradio_pipeline.execute_image,
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fn=
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inputs=[eye_retargeting_slider, lip_retargeting_slider],
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outputs=[output_image, output_image_paste_back],
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show_progress=True
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)
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process_button_animation.click(
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fn=
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inputs=[
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image_input,
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video_input,
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args=args
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)
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+
@spaces.GPU(duration=240)
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def gpu_wrapped_execute_video(*args, **kwargs):
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return gradio_pipeline.execute_video(*args, **kwargs)
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+
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@spaces.GPU(duration=240)
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def gpu_wrapped_execute_image(*args, **kwargs):
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return gradio_pipeline.execute_image(*args, **kwargs)
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+
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# assets
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title_md = "assets/gradio_title.md"
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example_portrait_dir = "assets/examples/source"
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with gr.Row():
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gr.Examples(
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examples=data_examples,
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fn=gpu_wrapped_execute_video,
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inputs=[
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image_input,
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video_input,
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],
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outputs=[output_image, output_image_paste_back],
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examples_per_page=5,
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cache_examples=False,
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)
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gr.Markdown(load_description("assets/gradio_description_retargeting.md"))
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with gr.Row():
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# binding functions for buttons
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process_button_retargeting.click(
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# fn=gradio_pipeline.execute_image,
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fn=gpu_wrapped_execute_image,
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inputs=[eye_retargeting_slider, lip_retargeting_slider],
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outputs=[output_image, output_image_paste_back],
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show_progress=True
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)
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process_button_animation.click(
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fn=gpu_wrapped_execute_video,
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inputs=[
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image_input,
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video_input,
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src/utils/cropper.py
CHANGED
@@ -36,7 +36,7 @@ class Cropper(object):
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device_id = kwargs.get('device_id', 0)
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self.landmark_runner = LandmarkRunner(
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ckpt_path=make_abs_path('../../pretrained_weights/liveportrait/landmark.onnx'),
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onnx_provider='
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device_id=device_id
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)
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self.landmark_runner.warmup()
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@@ -44,7 +44,7 @@ class Cropper(object):
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self.face_analysis_wrapper = FaceAnalysisDIY(
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name='buffalo_l',
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root=make_abs_path('../../pretrained_weights/insightface'),
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providers=["
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)
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self.face_analysis_wrapper.prepare(ctx_id=device_id, det_size=(512, 512))
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self.face_analysis_wrapper.warmup()
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device_id = kwargs.get('device_id', 0)
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self.landmark_runner = LandmarkRunner(
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ckpt_path=make_abs_path('../../pretrained_weights/liveportrait/landmark.onnx'),
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onnx_provider='cpu',
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device_id=device_id
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)
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self.landmark_runner.warmup()
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self.face_analysis_wrapper = FaceAnalysisDIY(
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name='buffalo_l',
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root=make_abs_path('../../pretrained_weights/insightface'),
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providers=["CPUExecutionProvider"]
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)
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self.face_analysis_wrapper.prepare(ctx_id=device_id, det_size=(512, 512))
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self.face_analysis_wrapper.warmup()
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src/utils/landmark_runner.py
CHANGED
@@ -27,7 +27,7 @@ class LandmarkRunner(object):
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"""landmark runner"""
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def __init__(self, **kwargs):
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ckpt_path = kwargs.get('ckpt_path')
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onnx_provider = kwargs.get('onnx_provider', 'cuda') # 默认用cuda
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device_id = kwargs.get('device_id', 0)
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self.dsize = kwargs.get('dsize', 224)
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self.timer = Timer()
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"""landmark runner"""
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def __init__(self, **kwargs):
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ckpt_path = kwargs.get('ckpt_path')
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onnx_provider = 'cpu' #run on cpu for it to work with ZeroGPU // kwargs.get('onnx_provider', 'cuda') # 默认用cuda
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device_id = kwargs.get('device_id', 0)
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self.dsize = kwargs.get('dsize', 224)
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self.timer = Timer()
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