İndir Face Recognition - v1.5.1

Lütfen Kitaplıklar ve Kısa Sunum kategorisindeki öne çıkan Uygulamalar öğelerden biri olan Face Recognition - v1.5.1 'ı indirin ve paylaşın.
Ayrıca, VSCAM, V380s, Pydroid repository plugin, V380 Pro, CommCare, Can'u - Sex Game challenges for couple olarak indirebileceğiniz başka Uygulamalar bazılarını. Face Recognition - v1.5.1 'dan memnunsanız.

Qualeams tarafından yayınlanan Face Recognition - v1.5.1, bugün mevcut olan en iyi ücretsiz ve en iyi cep telefonu uygulamalarından biridir. Uygulama mağazasının Kitaplıklar ve Kısa Sunum kategorisinde yer almaktadır.

Face Recognition - v1.5.1 için minimum işletim sistemi Android 5.0+ ve üstü. Bu nedenle, henüz yapmadıysanız telefonunuzu güncellemeniz gerekir.

APKDroid'de, en son sürümü 1.5.1, yayınlanma tarihi 2017-05-27 ve dosya boyutu 54.4 MB olan Face Recognition - v1.5.1 APK'yı ücretsiz indireceksiniz.Google Play Store'dan alınan istatistiklere göre, yaklaşık 1000 indirme var. Android'e ayrı ayrı indirilen veya yüklenen uygulamalar dilerseniz güncellenebilir. Uygulamalarınızı da güncelleyin. Size en yeni özelliklere ve güvenliğe erişim sağlar ve uygulamanın kararlılığı. Şimdi keyfini çıkarın !!!

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