--- license: apache-2.0 pipeline_tag: mask-generation tags: - sam2 - segment-anything - instance-segmentation - robotics - IB-Robot - ascend - edge-deployment base_model: - facebook/sam2.1-hiera-tiny --- # Model Card for SAM2.1 Hiera Tiny (IB-Robot) Segment Anything Model 2.1 (SAM2.1) with Hiera-Tiny backbone, packaged for the [IB-Robot](https://gitcode.com/openeuler/IB_Robot) framework. Performs prompted segmentation: given an image and point/box prompts, generates instance masks. ## Repository Structure - `inference_manifest.json` — deployment routing (schema v3) - `assets/` — adapter config, torch weights (`.pt`) - `artifacts/ascend_310b/` — encoder + decoder OM (batch=1) - `artifacts/ascend_310p/` — encoder + decoder OM (batch=4) ## Deployment Backends | Target | Backend | Runtime | Batch | Hardware | |--------|---------|---------|-------|----------| | `ascend_310b` | ascend | ACL | 1 | Ascend 310B1 | | `ascend_310p` | ascend | ACL | 4 | Ascend 310P1 | | `torch_cpu` | torch | PyTorch | — | CPU | | `torch_cuda` | torch | PyTorch | — | NVIDIA GPU | Each Ascend deployment runs a two-stage pipeline: `encoder` then `decoder`. **Encoder input:** `host.sam2.image` float32 [N,3,1024,1024] NCHW **Decoder outputs:** `host.sam2.mask_logits` [N,1,256,256], `host.sam2.iou_predictions` [N,1], `host.sam2.low_res_masks` [N,1,256,256] ## Source Model This bundle's torch weights originate from the upstream SAM2.1 checkpoint: - **HuggingFace:** [facebook/sam2.1-hiera-tiny](https://huggingface.co/facebook/sam2.1-hiera-tiny) - **Direct checkpoint:** `https://dl.fbaipublicfiles.com/segment_anything_2/092824/sam2.1_hiera_tiny.pt` The Ascend OM artifacts were converted from these torch weights. Download script: `scripts/download_perception_models.sh`. ## Citation @inproceedings{sam2, title = {SAM 2: Segment Anything in Images and Videos}, author = {Ravi, Nikhila and Gabeur, Valentin and Hu, Yuan-Ting and others}, booktitle = {arXiv preprint arXiv:2408.00714}, year = {2024} } @software{ib_robot, title = {IB-Robot: Intelligence Boom Robot}, url = {https://gitcode.com/openeuler/IB_Robot}, license = {Apache-2.0} }