| --- |
| license: agpl-3.0 |
| pipeline_tag: keypoint-detection |
| --- |
| # AggPose Lite |
| AggPose Lite provides deployment-ready model artifacts for **AggPose-L 256x192 COCO-style top-down human pose estimation**. |
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| This repository contains: |
| - a cleaned `safetensors` checkpoint converted from the original AggPose-L COCO model; |
| - a depth-pruned **D24** student checkpoint distilled from the D40 teacher; |
| - a static-batch OpenVINO INT8 artifact optimized for CPU inference; |
| - model files intended to be used together with the [`xvyv99/aggpose-lite`](https://github.com/xvyv99/aggpose-lite) codebase. |
| The project is based on the upstream [`PediaMedAI/AggPose`](https://github.com/PediaMedAI/AggPose) implementation. |
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| ## Model Files |
| | File | Variant | Format | Intended Use | |
| | -------------------------------------------------------------------------------- | ------: | --------------------- | ---------------------------------------- | |
| | `AggPose-L_256x192_COCO2017.safetensors` | D40 | PyTorch / safetensors | Full AggPose-L COCO checkpoint | |
| | `AggPose-L-D24-train32k-distilled.safetensors` | D24 | PyTorch / safetensors | Depth-pruned distilled student | |
| | `openvino/AggPose-L-D24-train32k-distilled.static-b4-map-mlp.int8.mixed.cpu.xml` | D24 | OpenVINO IR | Recommended CPU deployment model | |
| | `openvino/AggPose-L-D24-train32k-distilled.static-b4-map-mlp.int8.mixed.cpu.bin` | D24 | OpenVINO weights | Weight file required by the `.xml` model | |
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| For CPU-oriented offline batch inference, the recommended artifact is: |
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|
| ```text |
| openvino/AggPose-L-D24-train32k-distilled.static-b4-map-mlp.int8.mixed.cpu.xml |
| ``` |
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| The corresponding `.bin` file must stay in the same directory. |
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| ## License |
| This model repository is licensed under the **AGPL-3.0 License**, consistent with the upstream [`PediaMedAI/AggPose`](https://github.com/PediaMedAI/AggPose) project. |
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