anime-faces数据集，GAN-动漫二次元数据集

该数据集用于进行无限制的人脸识别，包含 13000 张从互联网上获取的人脸图像，每张图片都标有该人的姓名，其中有 1680 个人的有超过2张图像。这些人脸图片均通过 Viola-Jones 人脸检测算法从互联网上检测到。 共有四个子数据集，分别为 原始数据集（lfw）、funneled images、LFW-a、deep funneled images 四组。

可直接用于人脸识别技术的图像集-人脸数据集，数据集里有 40 个人，每个都有 10 张照片，分别存储在 40 个文件夹里，s1-s40，每个文件夹下面都有 10 张 .pgm 照片，每张照片的尺寸 112*92（长 * 宽）。

Tiny Face Detector in TensorFlow 小脸检测 A TensorFlow port(inference only) of Tiny Face Detector from authors' MatConvNet codes[1]. Requirements Codes are written in Python. At first install Anaconda. Then install OpenCV, TensorFlow.

The Yale Facedatabase A (also known as Yalefaces) consists of 15 people (14 male, 1 female) each with 11 grayscale images sized pixel. There are changes in the light conditions (center light, left light, right light), facial expressions (happy, normal, sad, sleepy, surprised, wink) and glasses (glasses, no-glasses). 图片为bmp格式，裁剪为100*100

秉承开源精神，

webmorphR webmorphR的目标是与集成。 安装 您可以使用以下命令从安装开发版本： # install.packages("devtools") devtools :: install_github( " facelab/webmorphR " ) 例子 library( webmorphR ) # > # > ************ # > Welcome to webmorphR. For support and examples visit: # > https://facelab.github.io/webmorphR/ # > ************ login() # log in to webmorph.org for some functions # > Logged in as user 1 # > Your projects are using

简单的人脸识别资料库，有很多得到人脸可供识别，可供初学者使用！

在人脸识别过程中，常用到许多人脸数据库，这里提供应用极为广泛的英国orl人脸库

FACES is a set of images of naturalistic faces of 171 young (n = 58), middle-aged (n = 56), and older (n = 57) women and men displaying each of six facial expressions: neutrality, sadness, disgust, fear, anger, and happiness. The FACES database was developed between 2005 and 2007 by Natalie C. Ebner, Michaela Riediger, and Ulman Lindenberger at the Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany.（数据库太大，分开上传）