Face Recognition for Android
Free English Version: 1.1.1
Face recognition can be used as a test framework for face recognition methods.
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Software description
Face Recognition can be used as a test framework for several face recognition methods including the Neural Networks with TensorFlow and Caffe. It includes following preprocessing algorithms: Grayscale- Crop- Eye Alignment- Gamma Correction- Difference of Gaussians- Canny-Filter- Local Binary Pattern- Histogramm Equalization (can only be used if grayscale is used too) – ResizeYou can choose from the following feature extraction and classification methods: Eigenfaces with Nearest Neighbour- Image Reshaping with Support Vector Machine- TensorFlow with SVM or KNN- Caffe with SVM or KNNThe manual can be found here https://github.com/sladomic/Face-RecognitionAt the moment only armeabi-v7a devices and upwards are supported. For best experience in recognition mode rotate the device to left. For best performance use “Image Reshaping with Support Vector Machine” (0. 5 s / image). For best accuracy use the “VGG Face Descriptor” model (the performance is very bad though – 6. 5 s/ image). TensorFlow: If you want to use the Tensorflow Inception5h model, download it from here: https://storage. googleapis.com/download. tensorflow. org/models/inception5h. zipThen copy the file “tensorflow_inception_graph. pb” to “/sdcard/Pictures/facerecognition/data/TensorFlow”Use these default settings for a start: Number of classes: 1001 (not relevant as we don’t use the last layer) Input Size: 224Image mean: 128Output size: 1024Input layer: inputOutput layer: avgpool0Model file: tensorflow_inception_graph. pb. If you want to use the VGG Face Descriptor model, download it from here: https://www.dropbox.com/s/51wi2la5e034wfv/vgg_faces. pb? dl=0Caution: This model runs only on devices with at least 3 GB or RAM. Then copy the file “vgg_faces. pb” to “/sdcard/Pictures/facerecognition/data/TensorFlow”Use these default settings for a start: Number of classes: 1000 (not relevant as we don’t use the last layer) Input Size: 224Image mean: 128Output size: 4096Input layer: PlaceholderOutput layer: fc7/fc7Model file: vgg_faces. pb. Caffe: If you want to use the VGG Face Descriptor model, download it from here: http://www.robots. ox. ac. uk/. vgg/software/vgg_face/src/vgg_face_caffe. tar. gzCaution: This model runs only on devices with at least 3 GB or RAM. Then copy the files “VGG_FACE_deploy. prototxt” and “VGG_FACE. caffemodel” to “/sdcard/Pictures/facerecognition/data/caffe”Use these default settings for a start: Mean values: 104, 117, 123Output layer: fc7Model file: VGG_FACE_deploy. prototxtWeights file: VGG_FACE. caffemodel.
