다운로드 Face Recognition - v1.5.1

카테고리 라이브러리/데모의 추천 애플리케이션 중 하나 인 Face Recognition - v1.5.1을 (를) 다운로드하여 공유하세요.
또한 VSCAM, Guide For AnTuTu Benchmark, V380 Pro, Scandit Barcode Scanner Demo, SwipeYours, FTDA Extranet로 다운로드 할 수있는 다른 애플리케이션도 있습니다. Face Recognition - v1.5.1에 만족한다면.

Qualeams에서 출시 한 Face Recognition - v1.5.1은 현재 사용 가능한 최고의 무료 및 최고의 휴대 전화 애플리케이션 중 하나입니다. 앱 스토어의 라이브러리/데모 카테고리에 있습니다.

Face Recognition - v1.5.1의 최소 운영 체제는 Android 5.0+ 이상입니다. 아직 업데이트하지 않은 경우 휴대 전화를 업데이트해야합니다.

APKDroid에서는 Face Recognition - v1.5.1 APK 무료 다운로드를 받게됩니다. 최신 버전은 1.5.1, 게시일은 2017-05-27이며 파일 크기는 54.4 MB입니다.Google Play 스토어 통계에 따르면 약 1000 회 다운로드가 있습니다. Android에 개별적으로 다운로드하거나 설치된 앱은 원하는 경우 업데이트 할 수 있습니다. 앱도 업데이트하세요. 최신 기능에 대한 액세스 권한을 부여하고 보안을 강화합니다. 그리고 앱의 안정성. 지금 즐기세요 !!!

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