app.py

import gradio as gr
import os
import shutil
import zipfile
from types import SimpleNamespace
from inference import run_demo, load_config
import random
import string
from gradio.themes import Soft
from gradio.themes.utils.colors import gray, neutral, slate, stone, teal, zinc

custom_theme = Soft(
    primary_hue=stone,
    secondary_hue=gray,
    radius_size="md",
    text_size="sm",
    spacing_size="sm",
)


def inference_ui(img1, img2, omega, n_denoise_steps):
    tmpdir = 'results'
    random_str = ''.join(random.choices(string.ascii_letters, k=16))
    tmpdir = tmpdir + "_" + random_str

    # 删除所有包含 "results" 的目录
    for dir in os.listdir('.'):
        if dir.startswith('results') and os.path.isdir(dir):
            shutil.rmtree(dir)
    os.makedirs(os.path.join(tmpdir, "0"), exist_ok=True)

    args = SimpleNamespace(
        img_path_1=img1,
        img_path_2=img2,
        ckpt_path='ckpts/dipo.ckpt',
        config_path='configs/config.yaml',
        use_example_graph=False,
        save_dir=tmpdir,
        gt_data_root='./data/PartnetMobility',
        n_samples=3,
        omega=omega,
        n_denoise_steps=n_denoise_steps,
    )
    args.config = load_config(args.config_path)
    run_demo(args)

    gif_path = os.path.join(tmpdir, "0", "animation.gif")
    ply_path = os.path.join(tmpdir, "0", "object.ply")
    glb_path = os.path.join(tmpdir, "0", "object.glb")

    # 压缩结果为ZIP包
    zip_path = os.path.join(tmpdir, "output.zip")
    folder_to_zip = os.path.join(tmpdir, "0")
    with zipfile.ZipFile(zip_path, 'w', zipfile.ZIP_DEFLATED) as zipf:
        for root, dirs, files in os.walk(folder_to_zip):
            for file in files:
                abs_path = os.path.join(root, file)
                rel_path = os.path.relpath(abs_path, folder_to_zip)
                zipf.write(abs_path, arcname=rel_path)

    return (
        gif_path if os.path.exists(gif_path) else None,
        zip_path if os.path.exists(zip_path) else None
    )

def prepare_data():
    if not os.path.exists("data") or not os.path.exists("saved_model"):
        print("Downloading data.tar from Hugging Face Datasets...")
        os.system("wget https://huggingface.co/datasets/wuruiqi0722/DIPO_data/resolve/main/data/data.tar -O data.tar")
        os.system("tar -xf data.tar")

with gr.Blocks(theme=custom_theme) as demo:
    gr.Markdown("## DIPO: Dual-State Images Controlled Articulated Object Generation Powered by Diverse Data")
    gr.Markdown("""
    [📖 Project Page](https://rq-wu.github.io/projects/DIPO)    |    [📄 arXiv](https://arxiv.org/abs/2505.20460)    |    [💻 GitHub](https://github.com/RQ-Wu/DIPO)
    """)
    gr.Markdown("Currently, only the articulated object in following categories are supported: `Table`, `Dishwasher`, `StorageFurniture`, `Refrigerator`, `WashingMachine`, `Microwave`, `Oven`.")

    with gr.Row():
        with gr.Column(scale=1):
            img1_input = gr.Image(label="Image: Closed State", type="filepath", height=250)
            img2_input = gr.Image(label="Image: Opened State", type="filepath", height=250)
            omega = gr.Slider(0.0, 1.0, step=0.1, value=0.5, label="Omega (CFG Guidance)")
            n_denoise = gr.Slider(10, 200, step=10, value=100, label="Denoising Steps")
            run_button = gr.Button("🚀 Run Generation (~2mins)")

        with gr.Column(scale=1):
            output_gif = gr.Image(label="GIF Animation", type="filepath", height=678, width=10000)
            zip_download_btn = gr.DownloadButton(label="📦 Download URDF folder", interactive=False)

    gr.Examples(
        examples=[
            ["examples/close10.png", "examples/open10.png"],
            ["examples/close9.jpg", "examples/open9.jpg"],
            ["examples/1.png", "examples/1_open_1.png"],
            ["examples/1.png", "examples/1_open_2.png"],
            ["examples/close1.png", "examples/open1.png"],
            # ["examples/close2.png", "examples/open2.png"],
            # ["examples/close4.png", "examples/open4.png"],
            ["examples/close5.png", "examples/open5.png"],
            ["examples/close6.png", "examples/open6.png"],
            ["examples/close7.png", "examples/open7.png"],
            ["examples/close8.png", "examples/open8.png"],
            ["examples/close3.png", "examples/open3.png"],
        ],
        inputs=[img1_input, img2_input],
        label="📂 Example Inputs"
    )

    run_button.click(
        fn=inference_ui,
        inputs=[img1_input, img2_input, omega, n_denoise],
        outputs=[output_gif, zip_download_btn]
    ).success(
    lambda: gr.DownloadButton(interactive=True),
    outputs=[zip_download_btn]
)

if __name__ == "__main__":
    prepare_data()
    demo.launch()