Qt的BPNN人脸识别：Q Qt开发的基于BPNN（反向传播神经网络）的人脸识别系统

# BPNN-Face-Recognition-For-Qt A Face Recognition System Based on BPNN(Back Propagation Neural Network) Developed by Qt. Parallel Version：[Github . PAC-P2P/BPNN-Face-Recognition-For-Parallel](https://github.com/PAC-P2P/BPNN-Face-Recognition-For-Parallel) Serial Version：[Github . PAC-P2P/BPNN-Face-Recognition](https://github.com/PAC-P2P/BPNN-Face-Recognition) Qt Version：[Github . PAC-P2P/BPNN-Face-Recognition-For-Qt](https://github.com/PAC-P2P/BPNN-Face-Recognition-For-Qt) ## Download [BPNN-Face-Recognition-For-Qt / releases](https://github.com/PAC-P2P/BPNN-Face-Recognition-For-Qt/releases) ## Usage ### Run 1. git clone https://github.com/PAC-P2P/BPNN-Face-Recognition-For-Qt.git 2. Use **Qt** to open `BPNN-Face-Recognition-For-Qt.pro` 3. Generate / Run ### Use #### Train 1. Menu Bar - Net - Training 2. Enter Training times (Default 100 times) 3. OK (Start training) 4. Qt console prints training information, evaluation results, such as: Iteration number: 100 Accuracy rate of: 74.359% Average error: 0.125675 5. Save to data/facenet.net 6. Successful train #### Input Images 1. Input 2. Enter User ID (Unique) 3. Enter Train times (Default 100 times) 4. Take photo 20 times (Save to data/images/imagesTrain) 5. Train 6. Successful input #### Recognition 1. Enter name (Optional) 2. Take Photo (Save to data/images/imagesRec/rec_01.pgm) 3. Train (if no facenet.net) 4. Recognition 5. Recognition result ## Neural network structure 1. `facenet.net` is a three-layer neural network with only one hidden layer * Input Layer : The size of the images * Hidden Layer : Number of training sets * Output Layer : Number of training sets 2. Neural network structure file: `data/facenet.net`. It is a `15360 * 6 * 6` neural network ## Warning 1. Images Size Make sure that the training set image has **the same image size** as the test set (including recognition). There are three sizes of images in `data/images`. * UserID_\*_1.pgm : 128 * 120 * UserID_\*_2.pgm : 64 * 60 * UserID_\*_3.pgm : 32 * 30 If your camera is not of these sizes please delete it(Including modifying data/*.list) and enter your own photo. 2. User ID `User ID` must be **Unique**, otherwise it will overwrite user data. 3. Directory tree Please keep the following directory structure so that the program can run normally. . ├── BPNN-Face-Recognition.pro ├── Release │   └── BPNN-Face-Recognition.exe ├── data │   ├── facenet.net │   ├── images │   │   ├── imagesRec │   │   │ └── rec_01.pgm │   │   └── imagesTrain │   │   ├── an2i_1_1.pgm │   │   ├── ...(images) │   │   └── cheyer_8_3.pgm │   ├── imagesSet_rec.list │   ├── imagesSet_testAll.list │   └── straightrnd_train.list └── src ├── backprop.cpp ├── backprop.h ├── camera.cpp ├── camera.h ├── camera.ui ├── dir.cpp ├── dir.h ├── facetrain.cpp ├── facetrain.h ├── imagenet.cpp ├── imagenet.h ├── imagesettings.cpp ├── imagesettings.h ├── imagesettings.ui ├── main.cpp ├── mainwindow.cpp ├── mainwindow.h ├── mainwindow.ui ├── pgmimage.cpp ├── pgmimage.h ├── src.pro ├── trainingsetting.cpp ├── trainingsetting.h └── trainingsetting.ui # Options * `SEED` : Seed of a random generator (Default `102194`) * `SAVEDELTA` : Save the network every SAVEDELTA times (Default `100`) * `LEARNRATE` : Learning rate (Default `0.3`) * `IMPULSE` : Impulse (Default `0.3`) * `INPUTTIMES` : Maximum number of photos inputed (Default `20`) * `MAXTRAINTIMES` : Maximum training times (Default `100000`) Modify these in `facetrain.cpp` or `camera.cpp` ## Screenshots  ## Data Set [Neural Networks for Face Recognition](http://www.cs.cmu.edu/afs/cs.cmu.edu/user/mitchell/ftp/faces.html) ## License [MIT](https://github.com/PAC-P2P/BPNN-Face-Recognition-For-Qt/blob/master/LICENSE)