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) - Resize You 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 KNN The manual can be found here https://github.com/Qualeams/Android-Face-Recognition-with-Deep-Learning/blob/master/USER%20MANUAL.md At 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.zip Then 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: 224 Image mean: 128 Output size: 1024 Input layer: input Output layer: avgpool0 Model 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=0 Caution: 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: 224 Image mean: 128 Output size: 4096 Input layer: Placeholder Output layer: fc7/fc7 Model 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.gz Caution: 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, 123 Output layer: fc7 Model file: VGG_FACE_deploy.prototxt Weights file: VGG_FACE.caffemodel _______________________________________________________________ The license files can be found here https://github.com/Qualeams/Android-Face-Recognition-with-Deep-Learning/blob/master/LICENSE.txt and here https://github.com/Qualeams/Android-Face-Recognition-with-Deep-Learning/blob/master/NOTICE.txt</br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br></br>