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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()