# 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_stf 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 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 os
import sys
from pathlib import Path
from src.utils.video import extract_audio
#from elevenlabs_utils import ElevenLabsPipeline
from setup_environment import initialize_environment
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('/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
stf_pipeline = 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()
###### 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
# # )
# @spaces.GPU(duration=120)
# def gpu_wrapped_execute_video(*args, **kwargs):
# return gradio_pipeline.execute_video(*args, **kwargs)
# @spaces.GPU(duration=120)
# def gpu_wrapped_execute_image(*args, **kwargs):
# return gradio_pipeline.execute_image(*args, **kwargs)
# @spaces.GPU(duration=120)
# def gpu_wrapped_stf_pipeline_execute(audio_path):
# return stf_pipeline.execute(audio_path)
# @spaces.GPU(duration=120)
# def gpu_wrapped_elevenlabs_pipeline_generate_voice(text, voice):
# return elevenlabs_pipeline.generate_voice(text, voice)
# 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()
# def run_end_to_end(image_path, text, voice, input_video, flag_relative, flag_do_crop, flag_remap, flag_crop_driving_video, male): #, animal):
# # # animal 체크 여부에 따라 다른 pipeline 사용
# # if animal:
# # gradio_pipeline = GradioPipelineAnimal(
# # inference_cfg=inference_cfg,
# # crop_cfg=crop_cfg,
# # args=args
# # )
# # else:
# # gradio_pipeline = GradioPipeline(
# # inference_cfg=inference_cfg,
# # crop_cfg=crop_cfg,
# # args=args
# # )
# if input_video is None:
# if not male:
# stf_pipeline = STFPipeline()
# else:
# stf_pipeline = STFPipeline(template_video_path="/home/user/app/stf/TEMP/Cam2_2309071202_0012_Natural_Looped.mp4",
# config_path="/home/user/app/stf/TEMP/front_config_v3.json",
# checkpoint_path="/home/user/app/stf/TEMP/0157.pth",
# )
# if input_video is None:
# #audio_path = elevenlabs_pipeline.generate_voice(text, voice)
# audio_path = gpu_wrapped_elevenlabs_pipeline_generate_voice(text, voice)
# #driving_video_path = stf_pipeline.execute(audio_path)
# driving_video_path = gpu_wrapped_stf_pipeline_execute(audio_path)
# else:
# driving_video_path = input_video
# os.makedirs("animations",exist_ok=True)
# audio_path = osp.join("animations", Path(input_video).stem+".wav")
# extract_audio(driving_video_path, audio_path)
# #output_path, crop_output_path = gradio_pipeline.execute_video(
# output_path, crop_output_path = gpu_wrapped_execute_video(
# input_image_path=image_path,
# input_video_path=driving_video_path,
# # input_driving_video_pickle_path=None,
# flag_do_crop_input=flag_do_crop,
# flag_remap_input=flag_remap,
# flag_relative_input=flag_relative,
# # driving_multiplier=1.0,
# # flag_stitching=False,
# # flag_crop_driving_video_input=flag_crop_driving_video,
# # scale=2.3,
# # vx_ratio=0.0,
# # vy_ratio=-0.125,
# # scale_crop_driving_video=2.2,
# # vx_ratio_crop_driving_video=0.0,
# # vy_ratio_crop_driving_video=-0.1,
# # tab_selection=None,
# audio_path=audio_path
# )
# return output_path, crop_output_path
# ###### 테스트중 ######
# stf_pipeline = STFPipeline()
# with gr.Blocks(theme=gr.themes.Soft()) as demo:
# stf_button = gr.Button("stf test", variant="primary")
# stf_button.click(
# fn=gpu_wrapped_stf_pipeline_execute,
# inputs=[
# audio_path
# ],
# outputs=[driving_video_path]
# )
# ###### 테스트중 ######
# with gr.Blocks(theme=gr.themes.Soft()) as demo:
# with gr.Tabs():
# # 첫 번째 탭: Text to LipSync
# with gr.Tab("Text to LipSync"):
# gr.Markdown("# Text to LipSync")
# with gr.Row():
# script_txt = gr.Text()
# voice = gr.Audio(label="사용자 음성", type="filepath")
# input_video = gr.Video()
# with gr.Row():
# image_input = gr.Image(type="filepath") # 여기서 image_input을 정의합니다.
# output_video.render()
# #crop_output_video.render()
# output_video_concat.render()
# 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")
# flag_crop_driving_video_input = gr.Checkbox(value=False, label="do crop (driving video)")
# male = gr.Checkbox(value=False, label="male")
# #animal = gr.Checkbox(value=False, label="animal") # animal 체크박스 추가
# with gr.Row():
# generate_speech = gr.Button("🚀 Generate Speech", variant="primary")
# generate_speech.click(
# fn=run_end_to_end,
# inputs=[
# image_input,
# script_txt,
# voice,
# input_video,
# flag_relative_input,
# flag_do_crop_input,
# flag_remap_input,
# flag_crop_driving_video_input,
# male,
# #animal # 추가된 animal 입력
# ],
# outputs=[output_video, output_video_concat]
# )
# # # 두 번째 탭: FLUX 이미지 생성
# # with gr.Tab("FLUX 이미지 생성"):
# # flux_tab(image_input) # FLUX 이미지 생성을 위한 별도의 탭
# # # 세 번째 탭: Flux 개발용 탭
# # with gr.Tab("FLUX Dev"):
# # flux_demo = create_flux_tab() # Flux 개발용 탭 생성
# # #flux_demo.render() # 해당 UI를 별도의 탭에만 렌더링
# with gr.Blocks(theme=gr.themes.Soft()) as demo:
# gr.HTML(load_description(title_md))
# 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,
# )
# gr.Markdown(load_description("assets/gradio_description_retargeting.md"), visible=True)
# with gr.Row(visible=True):
# eye_retargeting_slider.render()
# lip_retargeting_slider.render()
# with gr.Row(visible=True):
# process_button_retargeting = gr.Button("🚗 Retargeting", variant="primary")
# process_button_reset_retargeting = gr.ClearButton(
# [
# eye_retargeting_slider,
# lip_retargeting_slider,
# retargeting_input_image,
# output_image,
# output_image_paste_back
# ],
# value="🧹 Clear"
# )
# with gr.Row(visible=True):
# with gr.Column():
# with gr.Accordion(open=True, label="Retargeting Input"):
# retargeting_input_image.render()
# 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=[retargeting_input_image],
# cache_examples=False,
# )
# with gr.Column():
# with gr.Accordion(open=True, label="Retargeting Result"):
# output_image.render()
# with gr.Column():
# with gr.Accordion(open=True, label="Paste-back Result"):
# output_image_paste_back.render()
# # binding functions for buttons
# process_button_retargeting.click(
# # fn=gradio_pipeline.execute_image,
# fn=gpu_wrapped_execute_image,
# inputs=[eye_retargeting_slider, lip_retargeting_slider, retargeting_input_image, flag_do_crop_input],
# outputs=[output_image, output_image_paste_back],
# show_progress=True
# )
# 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
# )
# # 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
)