Baixar Face Recognition - v1.5.1

Baixar Face Recognition - v1.5.1
Package Name ch.zhaw.facerecognition
Category ,
Latest Version 1.5.1
Get it On Google Play
Update December 18, 2019 (4 years ago)

Faça download e compartilhe Face Recognition - v1.5.1, um dos apresentados APLICATIVOS na categoria Bibliotecas e demos.
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Lançado por Qualeams, Face Recognition - v1.5.1 é um dos melhores e melhores aplicativos gratuitos para celular disponíveis atualmente. Localizado na categoria Bibliotecas e demos da loja de aplicativos.

O sistema operacional mínimo para Face Recognition - v1.5.1 é Android 5.0+ e superior. Portanto, você deve atualizar seu telefone, se ainda não o fez.

No APKDroid, você obterá Face Recognition - v1.5.1 download gratuito do APK, sendo a versão mais recente 1.5.1, data de publicação 2017-05-27, o tamanho do arquivo é 54.4 MB.De acordo com as estatísticas da Google Play Store, há cerca de 1000 downloads. Aplicativos baixados ou instalados individualmente no Android podem ser atualizados se você desejar. Atualize seus aplicativos também. Concede a você acesso aos recursos mais recentes e melhora a segurança e estabilidade do aplicativo. Aproveite agora !!!

Face Recognition - v1.5.1

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

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