face recognition based attendance system using python

For objects similar to faces, you may need not less than 6,000 classifiers, each of which requires a successful match (and, of course, a fault-tolerant rate) to detect a person's face. But there is a problem: for face recognition, the algorithm starts from the upper left corner to compute a block of data, and keeps asking "Is this a

. Detection of the nose, has not been detected results, because the naked eye view of the image found that Alice's nose is slender, the head slightly lower the width of the nose tip is not large enough. Detect mouth, the mouth of the vote all in the left eye, indeed little Alice's mouth because the face micro-side appears particularly small, and by contrast, the shape of the left eye is more like mouth.The conclusion Paul Viola the Great God's article

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 i

right. Figure I 2, from the top of the mailbox page to enter the mailbox settings, in the "Account and Security" selected "Face Recognition", click "immediately set up." Figure II 3, in the face recognition process will be affected by light, face

　　fingerprint recognition algorithm is the core of fingerprint recognition system. The fingerprint recognition algorithm adopted in this system is: extracting ridge line direction, ridge Line frequency, Gabor filtering, feature extraction, and fingerprint database for featur

series of chips and Planahead and HLS tools provide the possibility for large-scale system hardware and software co-design. Therefore, this project uses the ZYNQ experimental platform developed by Digilent company Zedboard to realize the design of gesture recognition and application system. Project IntroductionThe project is

"Machine Learning Algorithm Implementation" series of articles will record personal reading machine learning papers, books in the process of the algorithm encountered, each article describes a specific algorithm, algorithm programming implementation, the application of practical examples of the algorithm. Each algorithm is programmed to be implemented in multiple languages. All code shares to Github:https://github.com/wepe/machinelearning-demo Welcome to the Exchange!(1) KNN algorithm _ Handwrit

PILBefore we start, we also need to install two additional dependent packages. One is Wand. It is the Imagemagick python interface.We need to use it to convert a PDF file into an image:We also need PIL because pyocr need to use it. You can view the official documentation to determine how to install PIL into your operating system.4. Warm UpLet's start our script. First, we need to import some important libr

Human motion recognition system based on Kinect (both algorithms and codes are released) first of all, the development environment version used by this system is the computer systems Windows 10, Visual Studio 2013, Opencv3.0, and the Kinect SDK v2.0. These can be found on Baidu, download down to install it. For the K

IRQ3 Interrupt Service subroutine when the touch wake source of Port A is triggered):. TEXT. Public _irq3_IRQ3:R1 = 0x0100;//Compare to L_IRQ3_EXT1 interruptTEST R1,[p_int_ctrl];JNZ l_irq3_ext1;//Yes, then enter; No, make the following judgmentsR1 = 0x0200;TEST R1,[p_int_ctrl];//Is l_irq3_ext2 interruptedJNZ l_irq3_ext2;//Yes, enter the interrupt; No, execute the following programL_irq3_keychange_wakeup://Not two of the above interrupts must be a key wakeup interruptR1 = 0x0080;//clear IRQ3 Tou

Here are some of the two mainstream systems now some of the special features, voice input, perhaps you have not formally used these features, but since the system has this function has its meaning, this section on the Win8 and XP speech recognition function of the use of the method.One of the "Win8" starts the speech recognition functionFirst, the user needs to p

Recently tried to use neural network to do digital character recognition, probably did a bit. The whole is very simple, that is, the test image pre-processing, and then by resampling extraction features, and finally through the neural network training and recognition. Interested can click here to learn about, welcome to advise.Here I would like to introduce how to remove a pair of pictures with more than on

,:] = Img2vector (' trainingdigits/%s '% filenamestr) testfilelist = Listdir (' testdigits ') #iterate through T He test set errorcount = 0.0 mtest = Len (testfilelist) for I in Range (mtest): Filenamestr = Testfilelist[i ] Filestr = Filenamestr.split ('. ') [0] #take off. txt classnumstr = int (Filestr.split ('_') [0]) Vectorundertest = Img2vector (' testdigits/%s ' % filenamestr) Classifierresult = Classify0 (Vectorundertest, Trainingmat, Hwlabels, 3) print "The Classifie R came back with:%d,

Today read the Python language written using SMO in SVM optimization, using the RBF function for handwriting recognition, the following simple collation of the whole process and ideas, and then detailed the various parts.(1) Acquiring training data sets Trainingmat and Labelmat;(2) Optimization parameters Alphas and B

-1,rect.bottom-25,swp_hidewindow); m_pagepicture. SetWindowPos (Null,rect.left+1,rect.top+1,rect.right-1,rect.bottom-25,swp_showwindow); break;} *presult = 0;What should we do if we want to set the display of VTK? We can call VTK's Vtkrenderwindow object's Setparetid method to set it, get the Pageviewer object under the tab control, and get a handle to the static control inside it.Renwin->setparentid (M_pageviewer. GetDlgItem (IDC_STATIC_VTK)->m_hwnd); CRect Rect;m_pageviewer. GetDlgItem (IDC_ST

NotoginsengFilestr = Filenamestr.split ('.') [0] - #classification Marks theclassnumstr = Int (Filestr.split ('_') [0]) + #reduce the current test set file dimension AVectorundertest = Img2vector ('/home/fangmeng/testdigits/%s'%filenamestr) the #classify the current test file +Classifierresult = Classify0 (Vectorundertest, Trainingmat, Hwlabels, 3) - $ if(Classifierresult! =classnumstr): $ Print "category Result:%d, actual result:%d"%(Classif

Directory 1. Application Introduction 1.1 Introduction to the experimental environment 1.2 Application Background Introduction 2. Data sources and preprocessing 2.1 Data sources and formats 2.2 Data preprocessing 3. Algorithm design and implementation 3.1 Handwriting recognition system algorithm implementation process Implementation of 3.2 K nearest neighbor algorithm 3.3 Handwriting

Since Python supports runtime dynamic loading, designing a plug-in structure is relatively straightforward. If you use PYQT, you can easily create a plug-in UI structure. However, in many cases, the main program is written using C++/stl, which implements the plug-in extension through Python. This article focuses on the "pure