Steps:
-
Download all of the files and folders in this repo and prepare the dataset. In my project, in this project we used CelebA dataset and Bitmoji dataset run
python create_emojis.py
and set the number of bitmoji images on thenum_emojis
variable. -
Put the training CelebA dataset inside
dataset/CelebA/trainA/
folder, and test CelebA dataset insidedataset/CelebA/test
. -
Put all the Bitmoji dataset inside
dataset/Bitmoji
folder. -
Set up the config file inside
configs/cifar.json
. Generally, You can determine the number of epochs, n_save_steps, and batch_size. I usebatch_size=32
for faster converged. -
Run program using command
python train.py --log log_photo2emoji --project_name photo2emoji
Steps:
-
Change the
saved_model
key inconfig.json
to be./log_photo2emoji/model_500.pt
or whenever number of iteration model you use. -
run program using command
python testAtoB.py --project_name photo2emoji --log log_photo2emoji