import subprocess
import shlex
import os
import gradio as gr

# Clone the repository
subprocess.run(shlex.split("pip install -q 'git+https://github.com/facebookresearch/segment-anything-2.git'"))

import torch
from sam2.build_sam import build_sam2
from sam2.sam2_image_predictor import SAM2ImagePredictor

DEVICE = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
CHECKPOINT = f"checkpoints/sam2_hiera_large.pt"
CONFIG = "sam2_hiera_l.yaml"

sam2_model = build_sam2(CONFIG, CHECKPOINT, device=DEVICE)

def run(image):
    return None


demo = gr.Interface(
    fn=run,
    title="LGM Tiny",
    description="An extremely simplified version of [LGM](https://huggingface.co/ashawkey/LGM). Intended as resource for the [ML for 3D Course](https://huggingface.co/learn/ml-for-3d-course/unit0/introduction).",
    inputs="image",
    outputs=gr.Model3D(),
    examples=[
        "https://huggingface.co/datasets/dylanebert/iso3d/resolve/main/jpg@512/a_cat_statue.jpg"
    ],
    cache_examples=True,
    allow_duplication=True,
)
demo.queue().launch()