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
safetensorscheckpoint 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-litecodebase. The project is based on the upstreamPediaMedAI/AggPoseimplementation.
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:
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 project.
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