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orin_yolo). It bundles the original source weights together with an ONNX export and a TensorRT FP16 engine built on a Jetson Orin Nano (8 GB).| Role | Filename | Size | SHA-256 |
|---|---|---|---|
encoder_onnx | sam2.1_hiera_large_encoder.onnx | 812.9 MB | 0062225519ac4a9b… |
decoder_onnx | sam2.1_hiera_large_decoder.onnx | 27.8 MB | 5c2fb75ebe9b3073… |
onnxruntime.InferenceSession — input image (1,3,1024,1024) f32, outputs image_embed, high_res_feats_0/1onnxruntime.InferenceSession — feed encoder outputs + point_coords (1,N,2) f32 (1024-space px) + point_labels (1,N) int32 + zeroed mask_input/has_mask_input.engine artifact is hardware-specific to Jetson Orin Nano (Ampere sm_87, TensorRT 10.3, CUDA 12.6, FP16). It will not load on other Jetson families, other TensorRT versions, or x86 GPUs. Other users should rebuild from the .onnx via python -m tools.build_engines in the linked GitHub repo.sam2.1_hiera_large.pt from https://dl.fbaipublicfiles.com/segment_anything_2/092824/ (facebookresearch/sam2). Exported via the wrappers in image/sam2/export_sam2.py (opset 17, torch.onnx.export).