Instructions to use SharpAI/sam2-hiera-tiny-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sam2
How to use SharpAI/sam2-hiera-tiny-onnx with sam2:
# Use SAM2 with images import torch from sam2.sam2_image_predictor import SAM2ImagePredictor predictor = SAM2ImagePredictor.from_pretrained("SharpAI/sam2-hiera-tiny-onnx") 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("SharpAI/sam2-hiera-tiny-onnx") 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 encoder.with_runtime_opt.ort from SharpAI/sam2-hiera-tiny-onnx: direct link, hf CLI and curl.
- Browser
- Download file 134 MB
-
https://huggingface.co/SharpAI/sam2-hiera-tiny-onnx/resolve/main/encoder.with_runtime_opt.ort
- Command line
-
hf download hf://SharpAI/sam2-hiera-tiny-onnx/encoder.with_runtime_opt.ort
-
curl -L -o encoder.with_runtime_opt.ort https://huggingface.co/SharpAI/sam2-hiera-tiny-onnx/resolve/main/encoder.with_runtime_opt.ort
134 MB
- Xet hash:
- 05bcbd6ba9ebe7b90fa337d46b3b243f9231c25ff3dfbdb7c0a7e3a84e3b2dd1
- Size of remote file:
- 134 MB
- SHA256:
- 45e4b9607e78ad1a83661153340025b5ca2c49ef7ab3cce53f72ea48fd91c6de
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