# 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) initialize_environment() 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 audio_path="assets/examples/driving/test_aud.mp3" #audio_path_component = gr.Textbox(label="Input", value="assets/examples/driving/test_aud.mp3") @spaces.GPU(duration=120) def gpu_wrapped_stf_pipeline_execute(audio_path): return stf_pipeline.execute(audio_path) ###### 테스트중 ###### stf_pipeline = STFPipeline() driving_video_path=gr.Video() # set tyro theme tyro.extras.set_accent_color("bright_cyan") args = tyro.cli(ArgumentConfig) with gr.Blocks(theme=gr.themes.Soft()) as demo: with gr.Row(): audio_path_component = gr.Textbox(label="Input", value="assets/examples/driving/test_aud.mp3") stf_button = gr.Button("stf test", variant="primary") stf_button.click( fn=gpu_wrapped_stf_pipeline_execute, inputs=[ audio_path_component ], outputs=[driving_video_path] ) with gr.Row(): driving_video_path.render() # 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(image_input) # Flux 개발용 탭 생성 demo.launch( server_port=args.server_port, share=args.share, server_name=args.server_name )