Unduh Face Recognition - v1.5.1

Anda pernah mendengar tentang Face Recognition - v1.5.1, atau CommCare, Pydroid repository plugin, Guide For AnTuTu Benchmark, FTDA Extranet, Deeeer Simulator 3D Game - Deer Tips, V380 Pro, salah satu Aplikasi paling keren di kategori Perpustakaan & Demo.

Dan tentu saja Anda tahu bahwa, tidak semua game atau aplikasi kompatibel untuk semua ponsel. Game atau aplikasi terkadang tidak tersedia di perangkat Anda, itu tergantung pada versi sistem. Sistem operasi Android, resolusi layar, atau negara yang diizinkan aksesnya oleh Google Play. Itulah sebabnya APKPanda menyediakan file APK Android untuk Anda unduh dan tidak mematuhi batasan ini.>
Face Recognition - v1.5.1 versi terbaru adalah 1.5.1, tanggal rilis 2017-05-27, dan memiliki ukuran 54.4 MB.Dikembangkan oleh Qualeams, Face Recognition - v1.5.1 memerlukan versi Android setidaknya Android 5.0+. Oleh karena itu, Anda harus memperbarui ponsel Anda jika perlu.

Cukup banyak dimuat, tentang 1000 unduhan. Anda dapat memperbarui aplikasi yang telah diunduh atau dipasang satu per satu pada perangkat Android Anda jika Anda mau. Memperbarui aplikasi memberi Anda izin akses ke fitur-fitur terbaru dan meningkatkan keamanan dan stabilitas aplikasi.

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