# 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 import torch #추가 from elevenlabs_utils import ElevenLabsPipeline from setup_environment import initialize_environment from src.utils.video import extract_audio from download import download_files_from_url import os import sys # 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) download_files_from_url() initialize_environment() 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('/tmp/') sys.path.append('/tmp/stf/') sys.path.append('/tmp/stf/stf_alternative/') sys.path.append('/tmp/stf/stf_alternative/src/stf_alternative') # 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() # # with gr.Row(): # # create_flux_tab() # image_input을 flux_tab에 전달합니다. # ###### 테스트중 ###### 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() #stf_pipeline = STFPipeline() stf_pipeline_female = STFPipeline() stf_pipeline_male = STFPipeline( template_video_path="TEMP/Cam2_2309071202_0012_Natural_Looped.mp4", config_path="front_config_v3.json", checkpoint_path="TEMP/0157.pth", female_video=False ) # @spaces.GPU() #duration=240) # def gpu_wrapped_stf_pipeline_execute(audio_path): # return stf_pipeline.execute(audio_path) @spaces.GPU() def gpu_wrapped_stf_pipeline_execute(audio_path, video_type): if video_type == "Female video": stf_pipeline = stf_pipeline_female else: stf_pipeline = stf_pipeline_male return stf_pipeline.execute(audio_path) @spaces.GPU() def gpu_wrapped_elevenlabs_pipeline_generate_voice(text, voice): return elevenlabs_pipeline.generate_voice(text, voice) @spaces.GPU() def gpu_wrapped_execute_video(*args, **kwargs): return gradio_pipeline.execute_video(*args, **kwargs) @spaces.GPU() def gpu_wrapped_execute_image_lip(*args, **kwargs): return gradio_pipeline.execute_image_lip(*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) def txt_to_driving_video(input_text, audio_file, video_type): if audio_file is None and input_text is not None: audio_file = gpu_wrapped_elevenlabs_pipeline_generate_voice(text=input_text, voice=None) # 오디오파일이 있으면 텍스트보다 오디오를 우선적으로 처리 video_outpath = gpu_wrapped_stf_pipeline_execute(audio_file, video_type) return video_outpath # assets title_md = "assets/gradio_title.md" example_portrait_dir = "assets/examples/source" example_portrait_dir_custom = "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() #video_input = gr.Video() driving_video_path=gr.Video() with gr.Blocks(theme=gr.themes.Soft()) as demo: #gr.HTML(load_description(title_md)) gr.Markdown("# Talk-GEN by ESTsoft") gr.Markdown("**Text to talking video generation tool**\n\n") #gr.Markdown("### 1. Text to audio") gr.Markdown("### 1. Text/Audio to Driving-Video") with gr.Row(): with gr.Column(scale=1): script_txt = gr.Text(label="Textbox(Enter text OR upload an audio file.)") audio_file = gr.Audio(label="Upload audio(Enter text OR upload an audio file.)", type="filepath") # audio_gen_button = gr.Button("Audio generation", variant="primary") # with gr.Column(): # txt2video_gen_button = gr.Button("txt2video generation", variant="primary") video_type = gr.Radio(choices=["Female video", "Male video"], label="Select video type", value="Female video") txt2video_gen_button = gr.Button("Txt/Audio to video generation", variant="primary") #with gr.Column(): #audio_gen_button = gr.Button("Audio generation", variant="primary") # with gr.Row(): # output_audio = gr.Audio(label="Generated audio", type="filepath") # gr.Markdown("### 2. Audio to Driving-Video") # with gr.Row(): # #audio_path_component = gr.Textbox(label="Input", value="assets/examples/driving/test_aud.mp3") # video_gen_button = gr.Button("Audio to Video generation", variant="primary") # with gr.Row(): # #a2v_output = gr.Video() # driving_video_path.render() gr.Markdown("### 2. Image to Talking-Video with Driving-Video") #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, "01.webp")], [osp.join(example_portrait_dir, "02.webp")], [osp.join(example_portrait_dir, "03.jpg")], [osp.join(example_portrait_dir, "04.jpg")], [osp.join(example_portrait_dir, "05.jpg")], [osp.join(example_portrait_dir, "06.jpg")], [osp.join(example_portrait_dir, "07.jpg")], [osp.join(example_portrait_dir, "08.jpg")], ], inputs=[image_input], cache_examples=False, ) # ========== 여기에 closed mouth 버튼 추가 ========== # lip_ratio_input = gr.Number(value=0.0, label="Lip Ratio") process_button_closelip = gr.Button("Close lip", variant="primary") #image_close_lip = gr.Image(type="filepath") 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 ) txt2video_gen_button.click( fn=txt_to_driving_video, inputs=[ script_txt, audio_file, video_type ], outputs=[video_input], show_progress=True ) process_button_closelip.click( fn=gpu_wrapped_execute_image_lip, inputs=[lip_ratio_input, image_input, flag_do_crop_input], outputs=[image_input], show_progress=True ) # audio_gen_button.click( # fn=gpu_wrapped_elevenlabs_pipeline_generate_voice, # inputs=[ # script_txt # ], # outputs=[output_audio], # show_progress=True # ) # video_gen_button.click( # fn=gpu_wrapped_stf_pipeline_execute, # inputs=[ # output_audio # #audio_path_component # ], # outputs=[ # video_input # #driving_video_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 ) demo.launch( server_port=args.server_port, share=args.share, server_name=args.server_name )