tensorflow face recognition

The code address is as follows:Http://www.demodashi.com/demo/13071.html Objective:OpenCV is an open source cross-platform computer Vision library that provides interfaces to languages such as Python, and implements many common algorithms for image processing and computer vision.The Harr classifier based on the Viola-jones target detection framework is built into the OPENCV and only needs to be loaded into a configuration file (Haarcascade_frontalface_ Alt.xml) can be directly called Detecto

Large-scale Face RecognitionAlgorithmAnd face Attribute Analysis Algorithms Description Based on advanced machine learning algorithms and unique feature extraction methods, Jun technology has developed algorithms suitable for large-scale face recognition and face attrib

function In the previous blog when using TensorFlow to design a linear regression model, there is an introduction to the square difference cost function, the square difference cost function is also a more commonly used function. However, one drawback is that the descent is too slow, leading to the need to iterate many times to get close to the desired result. To give an example, for example, we do a certain topic in the exam, when the test curls dow

To use this feature we have to ensure that their mobile QQ is the latest version of QQ or otherwise will not have this function oh Now login QQ After we click "Security Center" to find "tools"-"laboratory" open into Then we'll find "face verification" to open the entry, as shown in the details. Select the Create Now button and open the entry as shown in the following illustration "Scan now," as required, will show up as sho

Recently developed, someone face recognition, and identity scan function Log in to this GitHub address to download the corresponding SDK package Https://github.com/FacePlusPlus Or go to the official website to download; Based on the documentation, import into the Android studio and then configure the problem, 1: If the introduction of their own projects, must be in their own project configuration, if this

This post uses TensorFlow as an exercise to infer the age and gender of photos based on the face, and there are many similar apps online. Training Data –adience data set The adience data set is from Flickr, which is used by users on the iphone or other smartphone devices, and is primarily intended for unfiltered face estimation of age and gender. At the same time

This article address:http://blog.csdn.net/u011239443/article/details/72861591 We are going to implement the nonstandard Lenet model:train:https://github.com/xiaoyesoso/tensorflowinaction/blob/master/inactionb1/chapter6/mnist_train_6_4_1.pyInference:https://github.com/xiaoyesoso/tensorflowinaction/blob/master/inactionb1/chapter6/mnist_inference_6_4 _1.py Train Train part and "TensorFlow actual combat--dnn--mnist digital

Tags: Linux Rainbow Soft recently launched the free Linux version of the Face Recognition SDK engine, which after its release of the free version of Windows, Android, iOS, a very commercial value for small and medium-sized enterprise version, as the ideal server OS, The release of Linux has undoubtedly become the innovation and expansion of the service-side application, since then, small and

Large Data Digest Authorized reprint Author: Huanghai Since August 2016, Wunda's start-up deeplearning.ai through Coursera to provide the latest online course of in-depth learning, and by February, Miss Wu updated the fifth part of the course (click to view the report of the large Data Digest), which takes six months. This article will focus on the fourth week of teacher Wunda's video content and notes, showing some important convolution neural network of special applications, we will start wi

BriefSeetaface was developed by the research group on face recognition led by Shanshi researcher of CAs. Code is implemented based on C + + and does not rely on Third-party libraries. However, the current Open-source code, compiled on Windows VS, is a hassle for our mac/linux users. After these days of study, Seetaface finally have a comprehensive understanding. Below, listen to me to explain. Note: This ar

size. The images has been captured from the following sources:Digital CamerasPictures scanned in using a scannerImages from the World Wide WebImages from existing face recognition and detection databases.It should is noted that all the pictures in the database is original pictures from the source without performing any proc Essing such as colour correction, sharpening, noise removal, etc. This ensures, the