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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**.
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.
## 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 |
For CPU-oriented offline batch inference, the recommended artifact is:
```text
openvino/AggPose-L-D24-train32k-distilled.static-b4-map-mlp.int8.mixed.cpu.xml
```
The corresponding `.bin` file must stay in the same directory.
## 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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