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import gradio as gr | |
import subprocess | |
import yaml | |
import os | |
import cv2 | |
def get_video_frame_count(video_path): | |
if video_path is None: | |
return None | |
video = cv2.VideoCapture(video_path) | |
frame_count = int(video.get(cv2.CAP_PROP_FRAME_COUNT)) | |
video.release() | |
return frame_count | |
def initialize_yaml(config_path): | |
try: | |
with open(config_path, 'r') as file: | |
config = yaml.safe_load(file) | |
if config is None: | |
print("YAML file is empty or contains invalid content. Initializing...") | |
config = {'test_cases': {}} | |
with open(config_path, 'w') as outfile: | |
yaml.safe_dump(config, outfile) | |
else: | |
print("YAML file is valid.") | |
except FileNotFoundError: | |
print("YAML file not found. Creating a new one...") | |
config = {'test_cases': {}} | |
with open(config_path, 'w') as outfile: | |
yaml.safe_dump(config, outfile) | |
def run_vid2vid(image_path, video_path, width, height, length, seed, cfg, steps): | |
# Assuming the rest of the configuration remains constant | |
config_path = './configs/prompts/animation_facereenac.yaml' | |
# Ensure paths are strings | |
image_path_str = str(image_path) | |
video_path_str = str(video_path) | |
# Load the existing configuration | |
with open(config_path, 'r') as file: | |
config = yaml.safe_load(file) | |
# If the file is somehow still empty or invalid, initialize config | |
if config is None: | |
config = {'test_cases': {}} | |
# Update the configuration using string paths | |
config['test_cases'] = {image_path_str: [video_path_str]} | |
# Save the updated configuration | |
with open(config_path, 'w') as file: | |
yaml.safe_dump(config, file, default_flow_style=False) | |
# Construct the command with all the additional arguments | |
command = [ | |
"python", "-m", "scripts.vid2vid_gr", | |
"--config", config_path, | |
"-W", str(width), | |
"-H", str(height), | |
# "-L", str(length), | |
"--seed", str(seed), | |
"--cfg", str(cfg), | |
"--steps", str(steps) | |
] | |
# Conditionally add the "-L" argument if a meaningful value is provided | |
if length is not None: | |
command.extend(["-L", str(length)]) | |
# Only add "--fps" argument if it is provided (not None) | |
# if fps is not None: | |
# command.extend(["--fps", str(fps)]) | |
# Run the vid2vid script with the specified parameters | |
subprocess.run(command) | |
# Assuming the script saves its output to a known, fixed path | |
output_file_path = "output/result/result.mp4" | |
# Return this path for Gradio to display the video | |
return output_file_path | |
with gr.Blocks(title="AniPortrait") as blocks_app: | |
gr.Markdown("# Gradio UI for AniPortrait vid2vid") | |
gr.Markdown("Audio-Driven Synthesis of Photorealistic Portrait Animation") | |
gr.Markdown("Original Project: https://github.com/Zejun-Yang/AniPortrait") | |
with gr.Row(): | |
image_input = gr.Image(type="filepath", label="Upload Image") | |
video_input = gr.Video(label="Upload Video") | |
with gr.Row(): | |
width = gr.Slider(minimum=256, maximum=1024, step=8, value=512, label="Width (-W)") | |
height = gr.Slider(minimum=256, maximum=1024, step=8, value=512, label="Height (-H)") | |
with gr.Row(): | |
length = gr.Number(value=None, label="Length (-L)") | |
seed = gr.Number(value=42, label="Seed (--seed)") | |
video_input.change(get_video_frame_count, inputs=video_input, outputs=length) | |
with gr.Row(): | |
cfg = gr.Slider(minimum=0.1, maximum=10.0, step=0.1, value=3.5, label="Cfg (--cfg)") | |
steps = gr.Slider(minimum=1, maximum=100.0, step=1, value=25, label="Steps (--steps)") | |
# with gr.Row(): | |
# fps = gr.Number(label="FPS (--fps)") | |
output_video = gr.PlayableVideo(label="Result") | |
def process_and_display(image_path, video_path, width, height, length, seed, cfg, steps): | |
return run_vid2vid(image_path, video_path, width, height, length, seed, cfg, steps) | |
run_button = gr.Button("Run") | |
run_button.click( | |
process_and_display, | |
inputs=[image_input, video_input, width, height, length, seed, cfg, steps], | |
outputs=output_video | |
) | |
if __name__ == "__main__": | |
blocks_app.queue(max_size=3).launch(share=False, show_error=True, show_api=False) | |