dcgan.caffe: A pure caffe-python implementation of DC-GAN
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As far as I know, there is no light-weight implementation of DCGAN based on caffe.
Inspired by DeePSiM implementation, a few lines of python code can train the dcgan model quickly without any hack in caffe core lib (Dosovitskiy has already done this. However, I think the code could be merged back to master branch).
You will need to compile the deepsim-caffe-branch. And make sure your PYTHONPATH point to it.
The deepsim-caffe only support cudnn-4.0. If disable the cudnn engine and replace some convolution layers with the master branch, a latest cudnn and cuda will work fine.
For face generator, please prepare celebA dataset as the link said. Then make a train list file and put it in the data.prototxt.
Just typing
python train.py
To view the model result by
python generate.py generator.prototxt snapshots_test/4000/generator.caffemodel
The visualizations of the models at iteration 3000 and 4000 are as following:
