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on
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Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -22,7 +22,7 @@ from elevenlabs_utils import ElevenLabsPipeline
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from setup_environment import initialize_environment
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from src.utils.video import extract_audio
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#from flux_dev import create_flux_tab
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from flux_schnell import create_flux_tab
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# from diffusers import FluxPipeline
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# import gdown
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@@ -133,267 +133,267 @@ from stf_utils import STFPipeline
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# return stf_pipeline.execute(audio_path)
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#
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#
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#
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def partial_fields(target_class, kwargs):
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# set tyro theme
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tyro.extras.set_accent_color("bright_cyan")
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args = tyro.cli(ArgumentConfig)
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# specify configs for inference
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inference_cfg = partial_fields(InferenceConfig, args.__dict__) # use attribute of args to initial InferenceConfig
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crop_cfg = partial_fields(CropConfig, args.__dict__) # use attribute of args to initial CropConfig
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gradio_pipeline = GradioPipeline(
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)
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# 추가 정의
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elevenlabs_pipeline = ElevenLabsPipeline()
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stf_pipeline = STFPipeline()
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@spaces.GPU() #duration=240)
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def gpu_wrapped_stf_pipeline_execute(audio_path):
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@spaces.GPU()
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def gpu_wrapped_elevenlabs_pipeline_generate_voice(text, voice):
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@spaces.GPU()
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def gpu_wrapped_execute_video(*args, **kwargs):
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@spaces.GPU()
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def gpu_wrapped_execute_image(*args, **kwargs):
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def is_square_video(video_path):
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def txt_to_driving_video(text):
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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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example_portrait_dir_custom = "assets/examples/source"
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example_video_dir = "assets/examples/driving"
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data_examples = [
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]
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#################### interface logic ####################
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# Define components first
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eye_retargeting_slider = gr.Slider(minimum=0, maximum=0.8, step=0.01, label="target eyes-open ratio")
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lip_retargeting_slider = gr.Slider(minimum=0, maximum=0.8, step=0.01, label="target lip-open ratio")
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retargeting_input_image = gr.Image(type="filepath")
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output_image = gr.Image(type="numpy")
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output_image_paste_back = gr.Image(type="numpy")
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output_video = gr.Video()
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output_video_concat = gr.Video()
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# video_input = gr.Video()
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driving_video_path=gr.Video()
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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demo.launch(
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server_port=args.server_port,
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from setup_environment import initialize_environment
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from src.utils.video import extract_audio
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#from flux_dev import create_flux_tab
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# from flux_schnell import create_flux_tab
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# from diffusers import FluxPipeline
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# import gdown
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# return stf_pipeline.execute(audio_path)
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###### 테스트중 ######
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stf_pipeline = STFPipeline()
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driving_video_path=gr.Video()
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# set tyro theme
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tyro.extras.set_accent_color("bright_cyan")
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args = tyro.cli(ArgumentConfig)
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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with gr.Row():
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audio_path_component = gr.Textbox(label="Input", value="assets/examples/driving/test_aud.mp3")
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stf_button = gr.Button("stf test", variant="primary")
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stf_button.click(
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fn=gpu_wrapped_stf_pipeline_execute,
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inputs=[
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audio_path_component
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],
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outputs=[driving_video_path]
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)
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with gr.Row():
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driving_video_path.render()
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# with gr.Row():
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# create_flux_tab() # image_input을 flux_tab에 전달합니다.
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###### 테스트중 ######
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# def partial_fields(target_class, kwargs):
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# return target_class(**{k: v for k, v in kwargs.items() if hasattr(target_class, k)})
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# # set tyro theme
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# tyro.extras.set_accent_color("bright_cyan")
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# args = tyro.cli(ArgumentConfig)
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# # specify configs for inference
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# inference_cfg = partial_fields(InferenceConfig, args.__dict__) # use attribute of args to initial InferenceConfig
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# crop_cfg = partial_fields(CropConfig, args.__dict__) # use attribute of args to initial CropConfig
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# gradio_pipeline = GradioPipeline(
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# inference_cfg=inference_cfg,
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# crop_cfg=crop_cfg,
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# args=args
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# )
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# # 추가 정의
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# elevenlabs_pipeline = ElevenLabsPipeline()
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# stf_pipeline = STFPipeline()
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# @spaces.GPU() #duration=240)
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# def gpu_wrapped_stf_pipeline_execute(audio_path):
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# return stf_pipeline.execute(audio_path)
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# @spaces.GPU()
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# def gpu_wrapped_elevenlabs_pipeline_generate_voice(text, voice):
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# return elevenlabs_pipeline.generate_voice(text, voice)
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# @spaces.GPU()
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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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# @spaces.GPU()
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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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# def is_square_video(video_path):
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# video = cv2.VideoCapture(video_path)
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# width = int(video.get(cv2.CAP_PROP_FRAME_WIDTH))
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# height = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT))
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# video.release()
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# if width != height:
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# raise gr.Error("Error: the video does not have a square aspect ratio. We currently only support square videos")
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# return gr.update(visible=True)
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# def txt_to_driving_video(text):
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# audio_path = gpu_wrapped_elevenlabs_pipeline_generate_voice(text)
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# driving_video_path = gpu_wrapped_stf_pipeline_execute(audio_path)
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# return driving_video_path
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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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# example_portrait_dir_custom = "assets/examples/source"
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# example_video_dir = "assets/examples/driving"
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# data_examples = [
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# [osp.join(example_portrait_dir, "s9.jpg"), osp.join(example_video_dir, "d0.mp4"), True, True, True, True],
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# [osp.join(example_portrait_dir, "s6.jpg"), osp.join(example_video_dir, "d0.mp4"), True, True, True, True],
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# [osp.join(example_portrait_dir, "s10.jpg"), osp.join(example_video_dir, "d0.mp4"), True, True, True, True],
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# [osp.join(example_portrait_dir, "s5.jpg"), osp.join(example_video_dir, "d18.mp4"), True, True, True, True],
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# [osp.join(example_portrait_dir, "s7.jpg"), osp.join(example_video_dir, "d19.mp4"), True, True, True, True],
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# [osp.join(example_portrait_dir, "s22.jpg"), osp.join(example_video_dir, "d0.mp4"), True, True, True, True],
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# ]
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# #################### interface logic ####################
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# # Define components first
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# eye_retargeting_slider = gr.Slider(minimum=0, maximum=0.8, step=0.01, label="target eyes-open ratio")
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# lip_retargeting_slider = gr.Slider(minimum=0, maximum=0.8, step=0.01, label="target lip-open ratio")
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# retargeting_input_image = gr.Image(type="filepath")
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# output_image = gr.Image(type="numpy")
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# output_image_paste_back = gr.Image(type="numpy")
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# output_video = gr.Video()
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# output_video_concat = gr.Video()
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# # video_input = gr.Video()
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# driving_video_path=gr.Video()
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# with gr.Blocks(theme=gr.themes.Soft()) as demo:
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# #gr.HTML(load_description(title_md))
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# with gr.Tabs():
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# with gr.Tab("Text to LipSync"):
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# gr.Markdown("# Text to LipSync")
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# with gr.Row():
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# with gr.Column():
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# script_txt = gr.Text()
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# # with gr.Column():
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# # txt2video_gen_button = gr.Button("txt2video generation", variant="primary")
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# with gr.Column():
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# audio_gen_button = gr.Button("Audio generation", variant="primary")
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# with gr.Row():
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# output_audio = gr.Audio(label="Generated audio", type="filepath")
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# with gr.Row():
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# video_gen_button = gr.Button("Audio to Video generation", variant="primary")
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# gr.Markdown(load_description("assets/gradio_description_upload.md"))
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# with gr.Row():
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# with gr.Accordion(open=True, label="Source Portrait"):
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# image_input = gr.Image(type="filepath")
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# gr.Examples(
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# examples=[
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# [osp.join(example_portrait_dir, "01.webp")],
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# [osp.join(example_portrait_dir, "02.webp")],
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# [osp.join(example_portrait_dir, "03.jpg")],
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# [osp.join(example_portrait_dir, "04.jpg")],
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# [osp.join(example_portrait_dir, "05.jpg")],
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# [osp.join(example_portrait_dir, "06.jpg")],
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# [osp.join(example_portrait_dir, "07.jpg")],
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# [osp.join(example_portrait_dir, "08.jpg")],
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# ],
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# inputs=[image_input],
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# cache_examples=False,
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# )
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# with gr.Accordion(open=True, label="Driving Video"):
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# video_input = gr.Video()
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# gr.Examples(
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# examples=[
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# [osp.join(example_video_dir, "d0.mp4")],
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# [osp.join(example_video_dir, "d18.mp4")],
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# [osp.join(example_video_dir, "d19.mp4")],
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# [osp.join(example_video_dir, "d14_trim.mp4")],
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# [osp.join(example_video_dir, "d6_trim.mp4")],
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# ],
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# inputs=[video_input],
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# cache_examples=False,
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# )
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# with gr.Row():
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# with gr.Accordion(open=False, label="Animation Instructions and Options"):
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# gr.Markdown(load_description("assets/gradio_description_animation.md"))
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# with gr.Row():
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# flag_relative_input = gr.Checkbox(value=True, label="relative motion")
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# flag_do_crop_input = gr.Checkbox(value=True, label="do crop")
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# flag_remap_input = gr.Checkbox(value=True, label="paste-back")
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# gr.Markdown(load_description("assets/gradio_description_animate_clear.md"))
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# with gr.Row():
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# with gr.Column():
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# process_button_animation = gr.Button("🚀 Animate", variant="primary")
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# with gr.Column():
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# process_button_reset = gr.ClearButton([image_input, video_input, output_video, output_video_concat], value="🧹 Clear")
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# with gr.Row():
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# with gr.Column():
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# with gr.Accordion(open=True, label="The animated video in the original image space"):
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# output_video.render()
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# with gr.Column():
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# with gr.Accordion(open=True, label="The animated video"):
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# output_video_concat.render()
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# with gr.Row():
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# # Examples
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# gr.Markdown("## You could also choose the examples below by one click ⬇️")
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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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# flag_relative_input,
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# flag_do_crop_input,
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# flag_remap_input
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# ],
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# outputs=[output_image, output_image_paste_back],
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# examples_per_page=6,
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# cache_examples=False,
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341 |
+
# )
|
342 |
|
343 |
+
# process_button_animation.click(
|
344 |
+
# fn=gpu_wrapped_execute_video,
|
345 |
+
# inputs=[
|
346 |
+
# image_input,
|
347 |
+
# video_input,
|
348 |
+
# flag_relative_input,
|
349 |
+
# flag_do_crop_input,
|
350 |
+
# flag_remap_input
|
351 |
+
# ],
|
352 |
+
# outputs=[output_video, output_video_concat],
|
353 |
+
# show_progress=True
|
354 |
+
# )
|
355 |
+
# # txt2video_gen_button.click(
|
356 |
+
# # fn=txt_to_driving_video,
|
357 |
+
# # inputs=[
|
358 |
+
# # script_txt
|
359 |
+
# # ],
|
360 |
+
# # outputs=[video_input],
|
361 |
+
# # show_progress=True
|
362 |
+
# # )
|
363 |
+
# audio_gen_button.click(
|
364 |
+
# fn=gpu_wrapped_elevenlabs_pipeline_generate_voice,
|
365 |
+
# inputs=[
|
366 |
+
# script_txt
|
367 |
+
# ],
|
368 |
+
# outputs=[output_audio],
|
369 |
+
# show_progress=True
|
370 |
+
# )
|
371 |
+
|
372 |
+
# video_gen_button.click(
|
373 |
+
# fn=gpu_wrapped_stf_pipeline_execute,
|
374 |
+
# inputs=[
|
375 |
+
# output_audio
|
376 |
+
# ],
|
377 |
+
# outputs=[video_input],
|
378 |
+
# show_progress=True
|
379 |
+
# )
|
380 |
|
381 |
|
382 |
|
383 |
+
# # image_input.change(
|
384 |
+
# # fn=gradio_pipeline.prepare_retargeting,
|
385 |
+
# # inputs=image_input,
|
386 |
+
# # outputs=[eye_retargeting_slider, lip_retargeting_slider, retargeting_input_image]
|
387 |
+
# # )
|
388 |
+
# video_input.upload(
|
389 |
+
# fn=is_square_video,
|
390 |
+
# inputs=video_input,
|
391 |
+
# outputs=video_input
|
392 |
+
# )
|
393 |
|
394 |
+
# # 세 번째 탭: Flux 개발용 탭
|
395 |
+
# with gr.Tab("FLUX Image"):
|
396 |
+
# flux_demo = create_flux_tab(image_input) # Flux 개발용 탭 생성
|
397 |
|
398 |
demo.launch(
|
399 |
server_port=args.server_port,
|