# Pinned dependencies

The delivered application uses the CPU execution provider only. No downloads occur when the app runs.

| Component | Pin / source |
|---|---|
| ONNX Runtime | [v1.22.0 Windows x64 release](https://github.com/microsoft/onnxruntime/releases/tag/v1.22.0) |
| OpenCV Zoo models/reference pipeline | [commit 47534e27c9851bb1128ccc0102f1145e27f23f98](https://github.com/opencv/opencv_zoo/tree/47534e27c9851bb1128ccc0102f1145e27f23f98) |
| Portable llvm-mingw compiler, build only | [20260826 UCRT x86_64 release](https://github.com/mstorsjo/llvm-mingw/releases/tag/20260826) |

Model files are renamed for packaging but otherwise unchanged:

- `models/palm.onnx` = `palm_detection_mediapipe_2023feb.onnx`, SHA-256 `78FF51C38496B7FC8B8EBDB6CC8C1ABB02FA6C38427C6848254CDABA57FCCE7C`.
- `models/hand.onnx` = `handpose_estimation_mediapipe_2023feb.onnx`, SHA-256 `DB0898AE717B76B075D9BF563AF315B29562E11F8DF5027A1EF07B02BEF6D81C`.

The hand/palm decoding and oriented crop pipeline is adapted from OpenCV Zoo's Apache-2.0 `mp_palmdet.py` and `mp_handpose.py`. This implementation samples the oriented square directly instead of using OpenCV as a runtime dependency. It uses the strongest palm detection for one-hand initialization and landmark-based ROI tracking afterward. Original reference authors/contributors retain their copyright; see model license and the upstream repository history.

The reference GIF used during development is OpenCV Zoo's `palm_detection_mediapipe/example_outputs/mppalmdet_demo.gif` at the above commit. It is test material, not user camera footage or a claim of live webcam validation.
