AniPortrait-Vid2Vid / app_hf.py
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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():
with gr.Column():
image_input = gr.Image(type="filepath", label="Upload Image")
gr.Examples(
examples = ["examples/aniportrait_man.jpg", "examples/aniportrait_woman.jpg"],
inputs = [image_input]
)
with gr.Column():
video_input = gr.Video(label="Upload Video")
gr.Examples(
examples = ["examples/aniportrait_rap.mov", "examples/aniportrait_song.mov"],
inputs = [video_input]
)
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)