# coding: utf-8 """ The entrance of the gradio """ import tyro import gradio as gr import os.path as osp from src.utils.helper import load_description from src.gradio_pipeline import GradioPipeline from src.config.crop_config import CropConfig from src.config.argument_config import ArgumentConfig from src.config.inference_config import InferenceConfig import spaces import cv2 #추가 from elevenlabs_utils import ElevenLabsPipeline from setup_environment import initialize_environment from src.utils.video import extract_audio from flux_dev import create_flux_tab # import gdown # folder_url = f"https://drive.google.com/drive/folders/1UtKgzKjFAOmZkhNK-OYT0caJ_w2XAnib" # gdown.download_folder(url=folder_url, output="pretrained_weights", quiet=False) # import sys # sys.path.append('/home/user/.local/lib/python3.10/site-packages') # sys.path.append('/home/user/.local/lib/python3.10/site-packages/stf_alternative/src/stf_alternative') # sys.path.append('/home/user/.local/lib/python3.10/site-packages/stf_tools/src/stf_tools') # sys.path.append('/home/user/app/') # sys.path.append('/home/user/app/stf/') # sys.path.append('/home/user/app/stf/stf_alternative/') # sys.path.append('/home/user/app/stf/stf_alternative/src/stf_alternative') # sys.path.append('/home/user/app/stf/stf_tools') # sys.path.append('/home/user/app/stf/stf_tools/src/stf_tools') # # CUDA 경로를 환경 변수로 설정 # os.environ['PATH'] = '/usr/local/cuda/bin:' + os.environ.get('PATH', '') # os.environ['LD_LIBRARY_PATH'] = '/usr/local/cuda/lib64:' + os.environ.get('LD_LIBRARY_PATH', '') # # 확인용 출력 # print("PATH:", os.environ['PATH']) # print("LD_LIBRARY_PATH:", os.environ['LD_LIBRARY_PATH']) # from stf_utils import STFPipeline def partial_fields(target_class, kwargs): return target_class(**{k: v for k, v in kwargs.items() if hasattr(target_class, k)}) # set tyro theme tyro.extras.set_accent_color("bright_cyan") args = tyro.cli(ArgumentConfig) # specify configs for inference inference_cfg = partial_fields(InferenceConfig, args.__dict__) # use attribute of args to initial InferenceConfig crop_cfg = partial_fields(CropConfig, args.__dict__) # use attribute of args to initial CropConfig gradio_pipeline = GradioPipeline( inference_cfg=inference_cfg, crop_cfg=crop_cfg, args=args ) # 추가 정의 elevenlabs_pipeline = ElevenLabsPipeline() @spaces.GPU(duration=200) def gpu_wrapped_elevenlabs_pipeline_generate_voice(text, voice): return elevenlabs_pipeline.generate_voice(text, voice) @spaces.GPU(duration=240) def gpu_wrapped_execute_video(*args, **kwargs): return gradio_pipeline.execute_video(*args, **kwargs) @spaces.GPU(duration=240) def gpu_wrapped_execute_image(*args, **kwargs): return gradio_pipeline.execute_image(*args, **kwargs) def is_square_video(video_path): video = cv2.VideoCapture(video_path) width = int(video.get(cv2.CAP_PROP_FRAME_WIDTH)) height = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT)) video.release() if width != height: raise gr.Error("Error: the video does not have a square aspect ratio. We currently only support square videos") return gr.update(visible=True) # assets title_md = "assets/gradio_title.md" example_portrait_dir = "assets/examples/source" example_video_dir = "assets/examples/driving" data_examples = [ [osp.join(example_portrait_dir, "s9.jpg"), osp.join(example_video_dir, "d0.mp4"), True, True, True, True], [osp.join(example_portrait_dir, "s6.jpg"), osp.join(example_video_dir, "d0.mp4"), True, True, True, True], [osp.join(example_portrait_dir, "s10.jpg"), osp.join(example_video_dir, "d0.mp4"), True, True, True, True], [osp.join(example_portrait_dir, "s5.jpg"), osp.join(example_video_dir, "d18.mp4"), True, True, True, True], [osp.join(example_portrait_dir, "s7.jpg"), osp.join(example_video_dir, "d19.mp4"), True, True, True, True], [osp.join(example_portrait_dir, "s22.jpg"), osp.join(example_video_dir, "d0.mp4"), True, True, True, True], ] #################### interface logic #################### # Define components first eye_retargeting_slider = gr.Slider(minimum=0, maximum=0.8, step=0.01, label="target eyes-open ratio") lip_retargeting_slider = gr.Slider(minimum=0, maximum=0.8, step=0.01, label="target lip-open ratio") retargeting_input_image = gr.Image(type="filepath") output_image = gr.Image(type="numpy") output_image_paste_back = gr.Image(type="numpy") output_video = gr.Video() output_video_concat = gr.Video() with gr.Blocks(theme=gr.themes.Soft()) as demo: #gr.HTML(load_description(title_md)) with gr.Tabs(): with gr.Tab("Text to LipSync"): gr.Markdown("# Text to LipSync") with gr.Row(): with gr.Column(): script_txt = gr.Text() with gr.Column(): audio_gen_button = gr.Button("Audio generation", variant="primary") with gr.Row(): output_audio_path = gr.Audio(label="Generated audio", type="filepath") gr.Markdown(load_description("assets/gradio_description_upload.md")) with gr.Row(): with gr.Accordion(open=True, label="Source Portrait"): image_input = gr.Image(type="filepath") gr.Examples( examples=[ [osp.join(example_portrait_dir, "s9.jpg")], [osp.join(example_portrait_dir, "s6.jpg")], [osp.join(example_portrait_dir, "s10.jpg")], [osp.join(example_portrait_dir, "s5.jpg")], [osp.join(example_portrait_dir, "s7.jpg")], [osp.join(example_portrait_dir, "s12.jpg")], [osp.join(example_portrait_dir, "s22.jpg")], ], inputs=[image_input], cache_examples=False, ) with gr.Accordion(open=True, label="Driving Video"): video_input = gr.Video() gr.Examples( examples=[ [osp.join(example_video_dir, "d0.mp4")], [osp.join(example_video_dir, "d18.mp4")], [osp.join(example_video_dir, "d19.mp4")], [osp.join(example_video_dir, "d14_trim.mp4")], [osp.join(example_video_dir, "d6_trim.mp4")], ], inputs=[video_input], cache_examples=False, ) with gr.Row(): with gr.Accordion(open=False, label="Animation Instructions and Options"): gr.Markdown(load_description("assets/gradio_description_animation.md")) with gr.Row(): flag_relative_input = gr.Checkbox(value=True, label="relative motion") flag_do_crop_input = gr.Checkbox(value=True, label="do crop") flag_remap_input = gr.Checkbox(value=True, label="paste-back") gr.Markdown(load_description("assets/gradio_description_animate_clear.md")) with gr.Row(): with gr.Column(): process_button_animation = gr.Button("🚀 Animate", variant="primary") with gr.Column(): process_button_reset = gr.ClearButton([image_input, video_input, output_video, output_video_concat], value="🧹 Clear") with gr.Row(): with gr.Column(): with gr.Accordion(open=True, label="The animated video in the original image space"): output_video.render() with gr.Column(): with gr.Accordion(open=True, label="The animated video"): output_video_concat.render() with gr.Row(): # Examples gr.Markdown("## You could also choose the examples below by one click ⬇️") with gr.Row(): gr.Examples( examples=data_examples, fn=gpu_wrapped_execute_video, inputs=[ image_input, video_input, flag_relative_input, flag_do_crop_input, flag_remap_input ], outputs=[output_image, output_image_paste_back], examples_per_page=6, cache_examples=False, ) process_button_animation.click( fn=gpu_wrapped_execute_video, inputs=[ image_input, video_input, flag_relative_input, flag_do_crop_input, flag_remap_input ], outputs=[output_video, output_video_concat], show_progress=True ) audio_gen_button.click( fn=gpu_wrapped_elevenlabs_pipeline_generate_voice, inputs=[ script_txt ], outputs=[output_audio_path], show_progress=True ) # image_input.change( # fn=gradio_pipeline.prepare_retargeting, # inputs=image_input, # outputs=[eye_retargeting_slider, lip_retargeting_slider, retargeting_input_image] # ) video_input.upload( fn=is_square_video, inputs=video_input, outputs=video_input ) # 세 번째 탭: Flux 개발용 탭 with gr.Tab("FLUX Dev"): flux_demo = create_flux_tab() # Flux 개발용 탭 생성 demo.launch( server_port=args.server_port, share=args.share, server_name=args.server_name )