Unduh Face Recognition - v1.5.1

Harap unduh dan bagikan Face Recognition - v1.5.1, salah satu dari Aplikasi unggulan di kategori Perpustakaan & Demo.
Plus, beberapa Aplikasi lainnya yang dapat Anda unduh sebagai FTDA Extranet, Game Booster Free Power GFX Lag Fix, Deeeer Simulator 3D Game - Deer Tips, Guide For AnTuTu Benchmark, SwipeYours, VSCAM. Jika Anda merasa puas dengan Face Recognition - v1.5.1.

Dirilis oleh Qualeams, Face Recognition - v1.5.1 adalah salah satu aplikasi telepon seluler gratis dan terbaik yang tersedia saat ini. Terletak di Perpustakaan & Demo kategori toko aplikasi.

Sistem operasi minimum untuk Face Recognition - v1.5.1 adalah Android 5.0+ dan lebih tinggi. Jadi Anda harus memperbarui ponsel Anda jika Anda belum melakukannya.

Di APKDroid, Anda akan mendapatkan Face Recognition - v1.5.1 unduhan gratis APK, dengan versi terbaru adalah 1.5.1, tanggal publikasi 2017-05-27, ukuran file 54.4 MB.Menurut statistik dari Google Play Store, ada sekitar 1000 unduhan. Aplikasi yang diunduh atau dipasang satu per satu di Android dapat diperbarui jika Anda mau. Perbarui aplikasi Anda juga. Memberi Anda akses ke fitur terbaru dan meningkatkan keamanan dan stabilitas aplikasi. Nikmati sekarang !!!

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/Qualeams/Android-Face-Recognition-with-Deep-Learning/blob/master/USER%20MANUAL.mdAt the moment only armeabi-v7a devices and upwards are supported.For best experience in recognition mode rotate the device to left._______________________________________________________________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_______________________________________________________________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

- Switch from building Tensorflow from source to using the Jcenter library- Included optimized_facenet model and changed default settings to use TensorFlow by default