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--- |
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license: creativeml-openrail-m |
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--- |
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Citations |
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``` |
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@inproceedings{AndyRasika, |
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title={Grounding DINO: Marrying DINO v2 with Grounded Pre-Training for Open-Set Object Detection}, |
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author={Ankush Singal}, |
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year={2023} |
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} |
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``` |
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``` |
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def load_model_hf(repo_id, filename, ckpt_config_filename, device='cpu'): |
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cache_config_file = hf_hub_download(repo_id=repo_id, filename=ckpt_config_filename) |
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args = SLConfig.fromfile(cache_config_file) |
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model = build_model(args) |
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args.device = device |
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cache_file = hf_hub_download(repo_id=repo_id, filename=filename) |
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checkpoint = torch.load(cache_file, map_location='cpu') |
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log = model.load_state_dict(clean_state_dict(checkpoint['model']), strict=False) |
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print("Model loaded from {} \n => {}".format(cache_file, log)) |
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_ = model.eval() |
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return model |
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ckpt_repo_id = "Andyrasika/GroundingDINO" |
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ckpt_filenmae = "groundingdino_swint_ogc.pth" |
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ckpt_config_filename = "GroundingDINO_SwinT_OGC.py" |
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model = load_model_hf(ckpt_repo_id, ckpt_filenmae, ckpt_config_filename) |
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``` |
