Spaces:
Running
on
A10G
Running
on
A10G
File size: 4,828 Bytes
a6ec5b8 ca3f3ab 960308d ca3f3ab 12511b9 ca3f3ab a6ec5b8 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 |
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"],
inputs = [image_input]
)
with gr.Column():
video_input = gr.Video(label="Upload Video")
gr.Examples(
examples = ["examples/aniportrait_rap.mp4", "examples/aniportrait_song.mp4"],
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)
|