import cv2
import numpy as np
import onnxruntime as ort
You do not need a deep learning researcher to use this model. Here is a Python implementation using onnxruntime and opencv.
Title: Download w600k-r50.onnx – High-Performance Face Recognition Model
Meta Description: Get the w600k-r50.onnx file for ArcFace inference. A ResNet-50 backbone trained on 600k identities. Supports ONNX Runtime for CPU/GPU deployment. Perfect for real-time face verification.

While the standard w600k-r50.onnx uses FP32 (float32) precision, it is remarkably resilient to INT8 quantization. You can shrink the file to 25MB without a significant accuracy drop (less than 0.5% loss in recall), making it ideal for edge devices.