| Developer: | Qualeams (1) | ||
| Price: | Free | ||
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Description
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.
_______________________________________________________________
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
---------------------------------------------------------------------------------------------------------
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
_______________________________________________________________
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
_______________________________________________________________
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
Screenshots
What's new
- Version: 1.5.1
- Updated:
- - Switch from building Tensorflow from source to using the Jcenter library
- Included optimized_facenet model and changed default settings to use TensorFlow by default
Price
- Today: Free
- Minimum: Free
- Maximum: Free
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Developer
- Qualeams
- Platforms: Android Apps (1)
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- Points: 0 + 266 ¡
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Additional Information
- Version: 1.5.1
- ID: ch.zhaw.facerecognition
- Category:
Android Apps›Libraries & Demo - OS:
Android 5.0 - Size:
21 Mb - Content Rating:
Everyone - Google Play Rating:
2.7(266) - Updated:
- Release Date:
Contacts
https://github.com/Qualeams/Android-Face-Recognition-with-Deep-Learning-Test-Framework «Face Recognition» is a Libraries & Demo app for Android, developed by «Qualeams». It was first released on and last updated on . This app is currently free to download. This app has not yet received any ratings or reviews on AppAgg. On Google Play, the current store rating is 2.7 based on 266 votes. AppAgg continuously tracks the price history, ratings, and user feedback for «Face Recognition». Subscribe to this app or follow its RSS feed to get notified about future discounts or updates.
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