Benchmarks Timings at 240p: - Face locations: 0.0819s - Face landmarks: 0.0029s - Encode face : 0.4879s - End-to-end: 0.5978s Timings at 480p: - Face locations: 0.3257s - Face landmarks: 0.0028s - Encode face : 0.4959s - End-to-end: 0.8203s Timings at 720p: - Face locations: 0.7046s - Face landmarks: 0.0028s - Encode face : 0.4993s - End-to-end: 1.1888s Timings at 1080p: - Face locations: 1.5179s - Face landmarks: 0.0030s - Encode face : 0.4838s - End-to-end: 1.9404s。
Python中实现人脸识别功能有多种方法，依赖于python胶水语言的特性，我们通过调用包可以快速准确的达成这一目的，本文给大家分享使用Python实现简单的人脸识别功能的操作步骤，感兴趣的朋友一起看看吧!
Levi G， Hassner T. Age and gender classification using convolutional neural networks//Proceedings of the IEEE conference on computer vision and pattern recognition workshops. 2015: 34-42. ↩︎。
