Google MobileNet Implementation using Keras Framework 2.0

• This project is just the implementation of paper from scratch. I don't have the pretrained weights or GPU's to train :)
• Separable Convolution is already implemented in both Keras and TF but, there is no BN support after Depthwise layers (Still investigating).
• Custom Depthwise Layer is just implemented by changing the source code of Separable Convolution from Keras. Keras: Separable Convolution
• There is probably a typo in Table 1 at the last "Conv dw" layer stride should be 1 according to input sizes.
• Couldn't find any information about the usage of biases at layers (not used as default).

• Add Custom Depthwise Convolution
• Add BN + RELU layers
• Check layer shapes
• Test Custom Depthwise Convolution
• Benchmark training and feedforward pass with both CPU and GPU
• Compare with SqueezeNet

• Keras v2.0+
• Tensorflow 1.0+ (not supporting Theano for now)

1. Keras Framework

2. Google MobileNet Paper

MIT License

Note: If you find this project useful, please include reference link in your work.