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glintr100.onnx, ResNet100 with additive angular margin loss),
for on-device face embedding on iOS.FaceEmbedding.mlmodel — neuralnetwork format, float16 weights (~124 MB)faceImage: 112×112 RGB image, 5-point aligned (InsightFace
norm_crop / ArcFace template). Preprocessing (pixel − 127.5) / 127.5 is
baked into the model.embedding: 512-dim face embedding (L2-normalize before cosine
comparison).onnx2torch) → traced → coremltools (neuralnetwork) →
fp16 weight quantization. Validated against ONNX Runtime: cosine similarity
0.999956 on random input (fp16 quantization is effectively lossless).| LFW | CFP-FP | AgeDB | CALFW | CPLFW |
|---|---|---|---|---|
| 99.65 | 95.19 | 96.10 | 94.70 | 90.93 |