| Operation | Latency (ms) | |-----------|--------------| | Preprocessing (alignment + resize) | 2.1 ms | | ONNX Runtime inference (FP32) | 6.4 ms | | Cosine similarity (512d) | 0.003 ms | | | ~8.5 ms |
If you have downloaded a face recognition model from repositories like InsightFace, FaceX-Zoo, or open-source model hubs, you have likely seen this file. But what exactly is it? Why is it in ONNX format? And why should you care about the "w600k" and "r50" nomenclature? w600k-r50.onnx
This model is a cornerstone for developers building scalable biometric systems, as it balances computational efficiency with high accuracy. 1. The Architecture: ResNet-50 (R50) | Operation | Latency (ms) | |-----------|--------------| |