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QtMeshEditor-blazeface-onnx
fernandotonon/QtMeshEditor-blazeface-onnx
QtMeshEditor-blazeface-onnx is a machine learning model from fernandotonon. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
Google MediaPipe's BlazeFace short-range detector, from the Face Landmarker .task bundle, converted to ONNX.
Access
Public
Updated Jul 13, 2026
Repo size
418 KB
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1
Public
Repo makeup
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.onnx418 KB · 99%
At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Jul 13, 2026
- Updated
- Jul 13, 2026
- SHA
- 50f2c66f
Model card
From the Hugging Face model README
BlazeFace short-range face detector (ONNX)
Google MediaPipe's BlazeFace short-range detector, from the Face Landmarker
.task bundle, converted to ONNX.
- Input
input[1,128,128,3]RGB, normalized to[-1,1], keep-aspect letterboxed (zero border). - Outputs
regressors[1,896,16](box + 6 keypoints per anchor),classificators[1,896,1](score logits). SSD anchors: strides[8,16,16,16], min/max scale 0.1484375/0.75 → 896 anchors; decode + weighted NMS at IoU 0.3. - Feeds the face ROI (rotation from the eye keypoints, 1.5× square-long) to the Face Mesh landmark model.
License
Apache-2.0 — this graph is a direct ONNX conversion of a Google
MediaPipe model (Apache-2.0 code
AND weights). Conversion + numerical-parity proof (vs the Python mediapipe
reference): scripts/export-facecap-onnx.py,
contract in docs/MOCAP_SPIKE.md.
How it is used
Mirror of one graph from fernandotonon/QtMeshEditor-models
(mocap/…), which QtMeshEditor
downloads on first use for its Performance Capture feature (video/webcam →
facial morph + head + full-body skeletal animation, epic #869). This standalone
repo is for discoverability; the app fetches from the aggregate repo.
- License
- apache-2.0
- Created
- Jul 13, 2026
- Updated
- Jul 13, 2026