app.py

from PIL import Image
import gradio as gr
from huggingface_hub import hf_hub_download
from model import Model
from app_canny import create_demo as create_demo_canny
from app_depth import create_demo as create_demo_depth
import os

# hf_hub_download(repo_id='wondervictor/ControlAR',
#                 filename='canny_MR.safetensors',
#                 local_dir='./checkpoints/')
# hf_hub_download(repo_id='wondervictor/ControlAR',
#                 filename='depth_MR.safetensors',
#                 local_dir='./checkpoints/')
# # hf_hub_download('google/flan-t5-xl', cache_dir='./checkpoints/')

DESCRIPTION = "# [ControlAR: Controllable Image Generation with Autoregressive Models](https://arxiv.org/abs/2410.02705) \n ### The first row in outputs is the input image and condition. The second row is the images generated by ControlAR.  \n ### You can run locally by following the instruction on our [Github Repo](https://github.com/hustvl/ControlAR)."
SHOW_DUPLICATE_BUTTON = os.getenv("SHOW_DUPLICATE_BUTTON") == "1"
model = Model()
device = "cuda"
model.to(device)
with gr.Blocks(css="style.css") as demo:
    gr.Markdown(DESCRIPTION)
    gr.DuplicateButton(
        value="Duplicate Space for private use",
        elem_id="duplicate-button",
        visible=SHOW_DUPLICATE_BUTTON,
    )
    with gr.Tabs():
        with gr.TabItem("Depth"):
            create_demo_depth(model.process_depth)
        with gr.TabItem("Canny"):
            create_demo_canny(model.process_canny)

if __name__ == "__main__":
    ckpt_folder = './checkpoints'
    t5_folder = os.path.join(ckpt_folder, "flan-t5-xl/flan-t5-xl")
    hf_hub_download(repo_id="google/flan-t5-xl", filename="config.json", local_dir=t5_folder)
    hf_hub_download(repo_id="google/flan-t5-xl", filename="pytorch_model-00001-of-00002.bin", local_dir=t5_folder)
    hf_hub_download(repo_id="google/flan-t5-xl", filename="pytorch_model-00002-of-00002.bin", local_dir=t5_folder)
    hf_hub_download(repo_id="google/flan-t5-xl", filename="pytorch_model.bin.index.json", local_dir=t5_folder)
    hf_hub_download(repo_id="google/flan-t5-xl", filename="special_tokens_map.json", local_dir=t5_folder)
    hf_hub_download(repo_id="google/flan-t5-xl", filename="spiece.model", local_dir=t5_folder)
    hf_hub_download(repo_id="google/flan-t5-xl", filename="tokenizer_config.json", local_dir=t5_folder)

    hf_hub_download(repo_id="lllyasviel/Annotators", filename="dpt_hybrid-midas-501f0c75.pt", local_dir=ckpt_folder)

    hf_hub_download(repo_id="wondervictor/ControlAR", filename="canny_MR.safetensors", local_dir=ckpt_folder)
    hf_hub_download(repo_id="wondervictor/ControlAR", filename="depth_MR.safetensors", local_dir=ckpt_folder)
    demo.launch(share=False)