DCGANnetwork-in-pictures

Another type of GAN, using Deep Convolutional Generative Adversarial Nerworks.

Introduction

• The structure is based on Deep Convolutional Generative Adversarial Nerworks, worked on TensorFlow.

• The whole training takes much time and calculation amount, maybe you'd better use GPU version or you will have to wait for a long time training.

• Another choice is that you can download the trained model by me. I will upload the model trained from Celeb's 10000 face pictures.

• In DCGAN_64x64.py, used as the structure: while in DCGAN_32x32.py, I reduce one layer so the output is 32x32x3 pic.

• Here is the hyperparameter:

Then there I recorded the training process in 4 kind of training dataset:

The results using fully connected network is:

while using this DCGAN is :

Here is the results in different training dataset:

• On drawing figure face:

• On car pictures:

• On human face pictures:

• On coins:

there is much difference, right?

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How to use

• Put all datasets in to a folder and change the input_data content to your dataset folder, After it trained, you can turn off To_Train button and run it again it will create pictures generated by the generator.

• I will uploaded trained model to the folder 训练完成的模型, whose name represent the dataset's type I trained. Also, I will put the hyperparameter txt in it so that you should keep yours same to that and you can use it.

I strongly recommend to use 64x64 code for I have updated it in continuing training and learning rate decay, and the model I upload will be that code.