搜索资源列表
face_detect
- opencv人脸识别的应用。读入图片（需要在程序中修改）可输出识别了人脸的图片。需要opencv 1.0-opencv face detection. input image can output image with rectangular at the detected faces. need opencv 1.0
facereclib-1.2.1
- python 人脸识别库 实现了几个标准的人脸识别算法-python face recgenation
facepp-python-sdk-2.0
- 人脸识别，python 代码，在线连接face++进行人脸识别与比对-face detected and regnise with python and face++ API
face_predict_use_keras.py
- 从设备中获取图像并从文件中比较找出哪一个是自己(Use cv2 open camera show picture. compare the file and find who is self)
pyTest
- 人脸识别测试，未测试成功 VideoCapture不知从哪里安装或引用(Test of face detection)
face-SVM
- 用PCA和SVM实现人脸识别，是经典的人脸识别Python代码(Face recognition using PCA and SVM)
face-Adaboost
- 用Adaboost和PCA算法实现人脸识别，用Python写的代码，根据经典的PCA和SVM算法改编(Adaboost and PCA algorithm for face recognition, code written in Python, adapted from the classic PCA and SVM algorithm)
python_face_recog
- 基于python+opencv 的 人脸识别，对一段视频进行读取，并检测出人脸，然后进行PCA 降维，最后用SVM进行人脸识别，识别率94%左右。(Based on python + opencv face recognition, a video was read, and face detection, and then PCA dimension reduction, and finally SVM face recognition, recognition rate of about 9
源码、素材以及效果图
- 项目名称：自动添加圣诞帽 自动识别图片中的人脸信息，为其加上帽圣诞帽。(Name of the project: automatically add a Christmas hat Automatically identify the face information in the picture and add a hat to the hat.)
faceCompare
- face++人脸识别API调用；openCV-python人脸检测；(Face++ face recognition API call; openCV-python face detection;)
face_recognition.git
- 使用python 和dlib 开发的人脸是别的代码(The faces developed using Python and Dlib are other codes)
face
- 系统介绍：基于树莓派官方系统stretch 系统，系统内安装了opencv3.3.0以及 tensorflow1.1.0 。人脸识别门禁的代码在里面目录/home/pi/face。内安装了深度学习的案例。 程序启动说明：开机前连接树莓派摄像头或网络USB摄像头，网络摄像头无需下面的设置。如使用树莓派摄像头则在终端输入 sudo nano /etc/modules-load.d/modules.conf 在最后添加一行添加 bcm2835-v4l2 ctrl+O回车保存 ctrl
Chapter10
- 这是python机器学习实例这本书的第十章， 其中介绍了人脸识别(This is python machine learning this book chapter ten code, face recognition are introduced)
lbpcascade_animeface-master
- 利用opencv资源库里自带的lbpcascade_animeface.xml，对普通人脸进行识别，如果有数据库的话，也可以自己训练学习，提取人脸特征，进行学习(We use the lbpcascade_animeface.xml in opencv repository to recognize normal faces. If there are databases, we can also train ourselves to learn, extract facial features
人脸识别
- 利用face++在python下实现人脸识别(use face++ relised detect face)
FaceRecognition-master
- 卷积神经网络实现人脸识别，是用Python写的(Face recognition by convolution neural network)
real_time_face_recognition
- tensorflow 人脸识别,基于Python+tensorflow。(tensorflow,Python,tensorflow)
03SVM
- 支持向量机的python实现和用于lfw人脸识别的示例(Python implementation of support vector machines and examples of LFW face recognition)
face_recognition
- 基于python的PCA（主成分分析降维）人脸识别(PCA (principal component analysis dimensionality reduction) face recognition based on python)
深度学习mtcnn
- 用市面上的摄像头，可以实现实时人脸识别功能。(The algorithm model of facenet face recognition is obtained through deep learning, and the backbone network of feature extraction is concept-resnetv1, which is developed from concept network and RESNET, with more channels and n