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README
MIT

HAAR与DLib的实时人脸检测

对于opencv的人脸检测方法,优点是简单,快速;存在的问题是人脸检测效果不好。正面/垂直/光线较好的人脸,该方法可以检测出来,而侧面/歪斜/光线不好的人脸,无法检测。因此,该方法不适合现场应用。而对于dlib人脸检测方法采用64个特征点检测,效果会好于opencv的方法识别率会更高。

至于哪种方法更好,写个代码就知道。

安装

本示例的代码是基于Python3。

  1. 安装Python3的虚环境:
$ virtualenv venv -p python3
  1. 安装基本依赖

激活虚环境然后执行以下的代码安装本示例所用到的全部依赖包

$ pip install -r requirements.txt

示例说明

The MIT License (MIT) Copyright (c) 2018 Ray Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

简介

用OpenCV进行人脸识别的各种示例 展开 收起
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