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import subprocess |
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import shlex |
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import os |
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import gradio as gr |
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subprocess.run(shlex.split("pip install -q 'git+https://github.com/facebookresearch/segment-anything-2.git'")) |
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import torch |
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from sam2.build_sam import build_sam2 |
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from sam2.sam2_image_predictor import SAM2ImagePredictor |
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DEVICE = torch.device('cuda' if torch.cuda.is_available() else 'cpu') |
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CHECKPOINT = f"checkpoints/sam2_hiera_large.pt" |
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CONFIG = "sam2_hiera_l.yaml" |
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sam2_model = build_sam2(CONFIG, CHECKPOINT, device=DEVICE) |
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def run(image): |
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return None |
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demo = gr.Interface( |
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fn=run, |
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title="LGM Tiny", |
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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).", |
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inputs="image", |
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outputs=gr.Model3D(), |
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examples=[ |
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"https://huggingface.co./datasets/dylanebert/iso3d/resolve/main/jpg@512/a_cat_statue.jpg" |
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], |
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cache_examples=True, |
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allow_duplication=True, |
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) |
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demo.queue().launch() |
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