import subprocess import shutil import os import gradio as gr import torchvision.transforms as T import sys import spaces from PIL import Image subprocess.run(["git", "clone", "https://github.com/AIRI-Institute/HairFastGAN"], check=True) os.chdir("HairFastGAN") subprocess.run(["git", "clone", "https://huggingface.co/AIRI-Institute/HairFastGAN"], check=True) os.chdir("HairFastGAN") subprocess.run(["git", "lfs", "pull"], check=True) os.chdir("..") shutil.move("HairFastGAN/pretrained_models", "pretrained_models") shutil.move("HairFastGAN/input", "input") shutil.rmtree("HairFastGAN") items = os.listdir() for item in items: print(item) shutil.move(item, os.path.join('..', item)) os.chdir("..") shutil.rmtree("HairFastGAN") from hair_swap import HairFast, get_parser hair_fast = HairFast(get_parser().parse_args([])) def resize(image_path): img = Image.open("image_path") square_size = 1024 left = (img.width - square_size) / 2 top = (img.height - square_size) / 2 right = (img.width + square_size) / 2 bottom = (img.height + square_size) / 2 img_cropped = img.crop((left, top, right, bottom)) return img_cropped @spaces.GPU def swap_hair(source, target_1, target_2, progress=gr.Progress(track_tqdm=True)): target_2 = target_2 if target_2 else target_1 final_image = hair_fast.swap(source, target_1, target_2) return T.functional.to_pil_image(final_image) with gr.Blocks() as demo: gr.Markdown("## HairFastGan") with gr.Row(): source = gr.Image(label="Photo that you want to replace the hair", type="filepath") target_1 = gr.Image(label="Reference hair you want to get", type="filepath") target_2 = gr.Image(label="Reference color hair you want to get (optional)", type="filepath") btn = gr.Button("Get the haircut") output = gr.Image(label="Your result") gr.Examples(examples=[("michael_cera-min.png", "leo_square-min.png", "pink_hair_celeb-min.png")], inputs=[source, target_1, target_2], outputs=output) source.upload(fn=resize, input=source, output=source) target_1.upload(fn=resize, input=target_1, output=target_1) target_2.upload(fn=resize, input=target_2, output=target_2) btn.click(fn=swap_hair, inputs=[source, target_1, target_2], outputs=[output]) demo.launch()