App Name | Face Recognition v1.5.1 |
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Genre | Games, Libraries & Demo |
Size | 54.4 MB |
Latest Version | 1.5.1 |
Get it On | |
Update | 2017-05-27 |
Package Name | ch.zhaw.facerecognition |
Rating | ( 254 ) |
Installs | 100,000+ |
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)
– Resize
You 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 KNN
The manual can be found here https://github.com/Qualeams/Android-Face-Recognition-with-Deep-Learning/blob/master/USER%20MANUAL.md
At the moment only armeabi-v7a devices and upwards are supported.
For best experience in recognition mode rotate the device to left.
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TensorFlow:
If you want to use the Tensorflow Inception5h model, download it from here:
https://storage.googleapis.com/download.tensorflow.org/models/inception5h.zip
Then 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: 224
Image mean: 128
Output size: 1024
Input layer: input
Output layer: avgpool0
Model file: tensorflow_inception_graph.pb
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If you want to use the VGG Face Descriptor model, download it from here:
https://www.dropbox.com/s/51wi2la5e034wfv/vgg_faces.pb?dl=0
Caution: 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: 224
Image mean: 128
Output size: 4096
Input layer: Placeholder
Output layer: fc7/fc7
Model file: vgg_faces.pb
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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.gz
Caution: 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, 123
Output layer: fc7
Model file: VGG_FACE_deploy.prototxt
Weights file: VGG_FACE.caffemodel
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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
100,000+
Click on the Download button above to get the downloadable APK file for this app / game.
To do that go to Settings and search the word unknown
– For Android Nougat or lower version click on Unknown sources and enable that setting.
– For Android Oreo or later, clicking on Install unknown apps which will take you to a list of apps. Select the actual app through which you want to install the Face Recognition app.
Or you can do it other way: Let’s say, you have downloaded the Face Recognition APK file on Google chrome or firefox browser on your phone.
Go to Settings > Apps & notifications or go to Settings > search for unknown > Open the app (Chrome, Firefox or file manager app etc) > Install unknown apps and enable Allow from this source
See the below screenshots that enables to install unknown apps on Oreo for Chrome app (you need to enable on the app from where you want to install the apk):