Instructions to use AtlasAnalyticsLab/AtlasPatch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sam2
How to use AtlasAnalyticsLab/AtlasPatch with sam2:
# Use SAM2 with images import torch from sam2.sam2_image_predictor import SAM2ImagePredictor predictor = SAM2ImagePredictor.from_pretrained("AtlasAnalyticsLab/AtlasPatch") with torch.inference_mode(), torch.autocast("cuda", dtype=torch.bfloat16): predictor.set_image(<your_image>) masks, _, _ = predictor.predict(<input_prompts>)# Use SAM2 with videos import torch from sam2.sam2_video_predictor import SAM2VideoPredictor predictor = SAM2VideoPredictor.from_pretrained("AtlasAnalyticsLab/AtlasPatch") with torch.inference_mode(), torch.autocast("cuda", dtype=torch.bfloat16): state = predictor.init_state(<your_video>) # add new prompts and instantly get the output on the same frame frame_idx, object_ids, masks = predictor.add_new_points(state, <your_prompts>) # propagate the prompts to get masklets throughout the video for frame_idx, object_ids, masks in predictor.propagate_in_video(state): ... - Notebooks
- Google Colab
- Kaggle
Download model.pth from AtlasAnalyticsLab/AtlasPatch: direct link, hf CLI and curl.
- Browser
- Download file 156 MB
-
https://huggingface.co/AtlasAnalyticsLab/AtlasPatch/resolve/refs%2Fpr%2F1/model.pth
- Command line
-
hf download hf://AtlasAnalyticsLab/AtlasPatch@refs/pr/1/model.pth
-
curl -L -o model.pth https://huggingface.co/AtlasAnalyticsLab/AtlasPatch/resolve/refs%2Fpr%2F1/model.pth
156 MB
- Xet hash:
- de30e575f2c4d1b01f416ab6bb03b8d10b498cdf3784a18ffb879740318064dd
- Size of remote file:
- 156 MB
- SHA256:
- 51481c42c1079738f8c506f4da6183002aa34b1eb27d79423ae8f802e052be22
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