##CnnForAndroid:A Classification Project using Convolutional Neural Network(CNN) in Android platform。It also support Caffe Model
CnnForAndroid is a android platform's implementation of deep learning using Tiny-cnn structure and provide two Recognition sample:one is gender Recognition for caffe net ; two is Car logo recognition for tiny-cnn net.
#Todo List
- add opencl support.
- change to the tiny-dnn new version
- Optimise the code and improve the speed.
#Dependencies
Opencv(for Android platform Opencv-2.4.9)
Tiny-cnn(old Version)
#Supporting Caffe model
tiny-cnn provide the caffe-convertor.cpp to support the caffe model.The project also support the caffe model from compiling the caffe_convertor and protobuf.
#For Gender Recogniton
this project also provide a sample for caffe model to distingguish man from woman also called gender recognition.
1.Where from training data?
MORPH Album 2.
the test accuracy is 90.01% in my caffe's net.
2.the net of caffe ?
3.How to train yourself caffe's model?
(1)Please using caffe and train your model.
(2)then replace /assets/tinyfile//.caffemodel and /assets/tinyfile/*.protobuf file/.
(3)Finish change those filenames in tinyCnn.java file.
#How to install it?
no need install.
Just download or git clone it and then open it by eclipse with opencv for java lib , use NDK to build it.
Surely your libs docu have the opencv_java.so file or you must add this file(from Opencv-android docu).
#Compile it
needful tools： NDK + eclipse + adt.
or android studio.
#For Vehicle Recogniton for tiny-cnn net
1.What is Vehicle Recognition?
this project classify car according to car logo.Now the lasting Version just distinguish VM car from other.
2.Where from Training Data ?
The major sources of our dataset include images captured by ourselves,Medialab LPR Dataset [1].
3.this models?
You can get it in JNi/test.cpp file.
Code:
static const bool tbl[] = {
O, X, O, O, O, O, O, O, O, O, O, X, O, O, O, O,
O, X, X, X, O, O, O, X, X, O, O, O, X, X, O, O,
O, O, X, X, X, O, O, O, X, X, O, O, X, X, X, O,
O, O, O, X, X, X, O, O, O, X, X, O, X, X, O, O,
O, O, O, O, X, X, O, O, O, O, X, X, O, X, X, O,
O, X, O, O, O, X, X, O, O, O, O, X, O, O, X, O,
};
nn << convolutional_layer<tan_h>(40 , 40 , 3 , 1 , 6)
<< average_pooling_layer<tan_h>(38 , 38 , 6 , 2)
<< convolutional_layer<tan_h>(19 , 19 , 4 , 6 , 16 ,
connection_table(tbl, 6, 16))
<< average_pooling_layer<tan_h>(16 , 16 , 16 , 2)
<< convolutional_layer<tan_h>(8 , 8 , 3 , 16, 16)
<< fully_connected_layer<tan_h>(16 * 6 * 6 , 64)
<< fully_connected_layer<relu>(64 , 2);
My models have three conv-layers and two pooling layer , fully-connect layer , in the end layer , the activation functions is relu and the size of all conv-kernel is 3x3.The optimization algorithm of cnn is stochastic gradient levenberg marquardt.
Other arguments can't be public.
4.Experiment
data：
500 train image , 298 test image.
platform:
Windows+VS2013.
Result:
the recognition rate is above 94.29%
#How to use it to recognize face or other object?
If want to recognition other object , you must learning Cnn and tiny-cnn , contructing optimal model and training it using enough object images to get the wb-file(weights and bias values).Finish , replace /assets/tinyfile/carlogo file with wb-file.
#references
[1]Medialab LPR dataset, March. 2013[online]. Available: http://www.medialab.ntua.gr/research/LPRdataset.html
[2]Humayun Karim Sulehria, Ye Zhang.Vehicle Logo Recognition Using Mathematical Morphology
[3]Humayun Karim Sulehria, Ye Zhang.Vehicle Logo Recognition Based on Bag-of-Words.IEEE International Conference on Advanced Video and Signal Based Surveillance,2013.
#Running Screenshot
(1)For Vehicle Recogniton
(3)For gender Recognition
#Discussing
- issue
- email:zhang163220@gmail.com