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on
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Running
on
Zero
| import subprocess | |
| import shlex | |
| import os | |
| import gradio as gr | |
| # Clone the repository | |
| subprocess.run(shlex.split("git clone https://github.com/facebookresearch/segment-anything-2.git")) | |
| # Change to the repository directory | |
| os.chdir("segment-anything-2") | |
| # Install the package | |
| subprocess.run(shlex.split("pip install -e .")) | |
| 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() | |