This is one of Deep learning nanodegree major projects. In this project, I have trained generative adversarial networks, especially DCGAN to generate new images of faces.My goal was to get a generator network to generate new images of faces that look as realistic as possible!

I used CelebFaces Attributes Dataset (CelebA) to train your adversarial networks.

• I have tried varuios moedel architicture :

  1- For model depth : [3 , 4] layers

  2- For convolution layer deimention : [32 , 64]

• I have tried also number of batch size : [32 , 64 , 128 ,256]

• I also have tried diffrient number of epochs : [ 20 , 30 , 50]

• As in the practise notebooks i used adam optimizer ,as it was recommended.

Actually , the models has smal deffriences and can't appear from the few sample of photos i show , but we can deffirenciate between them by the loss perfornmence.As we can see in the above graphs , the best model with loss performence is the model with the following architicutre :

layer_in_depth = 4
conv_dim = 64
batch_size = 64
num_epochs = 10

To hava a closer look to the results of each model and its traing loss plot, i encourge you to have a look at the Training loss and generator sample of training in the following report