W600k-r50.onnx

: Acting as the "recognition" engine to ensure a target face is correctly identified before applying a transformation.

session = ort.InferenceSession("w600k-r50.onnx", providers=['CPUExecutionProvider']) input_name = session.get_inputs()[0].name output_name = session.get_outputs()[0].name w600k-r50.onnx

import onnx model = onnx.load("w600k-r50.onnx") print(onnx.helper.printable_graph(model.graph)) : Acting as the "recognition" engine to ensure

import cv2 import numpy as np import onnxruntime as ort w600k-r50.onnx

: Indicates the backbone architecture, ResNet-50 , a 50-layer deep residual network.

Run a quick inspection (Python + onnxruntime) to confirm these — example code below.

w600k-r50.onnx Type: Face Recognition Model