EasyCNN

Easy convolution network.

Features

• All in one : without any dependency,pure c++ implemented.
• Basic layer : data layer,convolution layer,pooling layer,full connect layer,softmax layer,activation layers(sigmod,tanh,RELU)
• Loss function : Cross Entropy,MSE.
• Optimize method : SGD.

Examples

• mnist demo , with ConvNet and MLP net, examples/mnist/mnist_train_test.cpp
  

Todo List

• fix train error when batch > 1 issue.
• add load & save model function.
• add more layer,such as batch normalization layer,dropout layer,etc.
• add weight regular,gradient momentum.
• port to other platforms,such as linux,mac,android,iOS,etc.
• optimize network train/test speed,use cuBLAS/OpenBLAS etc.
• add more optimize method.
• add unit test.
• add license.

Bug Report

Use github issues please.

Pull Request

Pull request is welcome.

License

This project is released under the WTFPL LICENSE.