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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() | |