app.py

import argparse
import gradio as gr
import os
import torch
import trimesh
import sys
from pathlib import Path

pathdir = Path(__file__).parent / 'cube'
sys.path.append(pathdir.as_posix())

# print(__file__)
# print(os.listdir())
# print(os.listdir('cube'))
# print(pathdir.as_posix())

from cube3d.inference.engine import EngineFast, Engine
from pathlib import Path
import uuid
import shutil
from huggingface_hub import snapshot_download


GLOBAL_STATE = {}

def gen_save_folder(max_size=200):
    os.makedirs(GLOBAL_STATE["SAVE_DIR"], exist_ok=True)

    dirs = [f for f in Path(GLOBAL_STATE["SAVE_DIR"]).iterdir() if f.is_dir()]

    if len(dirs) >= max_size:
        oldest_dir = min(dirs, key=lambda x: x.stat().st_ctime)
        shutil.rmtree(oldest_dir)
        print(f"Removed the oldest folder: {oldest_dir}")

    new_folder = os.path.join(GLOBAL_STATE["SAVE_DIR"], str(uuid.uuid4()))
    os.makedirs(new_folder, exist_ok=True)
    print(f"Created new folder: {new_folder}")

    return new_folder

def handle_text_prompt(input_prompt, variance = 0):
    print(f"prompt: {input_prompt}, variance: {variance}")
    top_p = None if variance == 0 else (100 - variance) / 100.0
    mesh_v_f = GLOBAL_STATE["engine_fast"].t2s([input_prompt], use_kv_cache=True, resolution_base=8.0, top_p=top_p)
    # save output
    vertices, faces = mesh_v_f[0][0], mesh_v_f[0][1]
    save_folder = gen_save_folder()
    output_path = os.path.join(save_folder, "output.glb")
    trimesh.Trimesh(vertices=vertices, faces=faces).export(output_path)
    return output_path

def build_interface():
    """Build UI for gradio app
    """
    title = "Cube 3D"
    with gr.Blocks(theme=gr.themes.Soft(), title=title, fill_width=True) as interface:
        gr.Markdown(
            f"""
            # {title}
            # Check out our [Github](https://github.com/Roblox/cube) to try it on your own machine!
            """
        )

        with gr.Row():
            with gr.Column(scale=2):
                with gr.Group():
                    input_text_box = gr.Textbox(
                        value=None,
                        label="Prompt",
                        lines=2,
                    )
                    variance = gr.Slider(minimum=0, maximum=99, step=1, value=0, label="Variance")
                with gr.Row():
                    submit_button = gr.Button("Submit", variant="primary")
            with gr.Column(scale=3):
                model3d = gr.Model3D(
                    label="Output", height="45em", interactive=False
                )
    
        submit_button.click(
            handle_text_prompt,
            inputs=[
                input_text_box,
                variance
            ],
            outputs=[
                model3d
            ]
        )
                
    return interface

if __name__=="__main__":

    parser = argparse.ArgumentParser()
    parser.add_argument(
        "--config_path",
        type=str,
        help="Path to the config file",
        default="cube/cube3d/configs/open_model.yaml",
    )
    parser.add_argument(
        "--gpt_ckpt_path",
        type=str,
        help="Path to the gpt ckpt path",
        default="model_weights/shape_gpt.safetensors",
    )
    parser.add_argument(
        "--shape_ckpt_path",
        type=str,
        help="Path to the shape ckpt path",
        default="model_weights/shape_tokenizer.safetensors",
    )
    parser.add_argument(
        "--save_dir",
        type=str,
        default="gradio_save_dir",
    )

    args = parser.parse_args()
    snapshot_download(
        repo_id="Roblox/cube3d-v0.1",
        local_dir="./model_weights"
    )
    config_path = args.config_path
    gpt_ckpt_path = "./model_weights/shape_gpt.safetensors"
    shape_ckpt_path = "./model_weights/shape_tokenizer.safetensors"
    engine_fast = EngineFast(
        config_path,
        gpt_ckpt_path, 
        shape_ckpt_path,
        device=torch.device("cuda"),
    )
    GLOBAL_STATE["engine_fast"] = engine_fast
    GLOBAL_STATE["SAVE_DIR"] = args.save_dir
    os.makedirs(GLOBAL_STATE["SAVE_DIR"], exist_ok=True)

    demo = build_interface()
    demo.queue(default_concurrency_limit=1)
    demo.launch()