Comments (3)
Thanks a lot for the responses, @AlexanderGroshev , they helped a lot!
I have another question in mind about the dataset. In the parameters in train.py, we have --vgg, --same_person and --same_identity. I would like to train using a combination of VGGFace2, CelebAHQ and FFHQ datasets. Should I have --vgg parameter True? If so, how did you obtain the --same_person and --same_identity parameters? Are these statistics about the dataset you used or some probability you set yourself in order to perform swap with same target and source images during training? Thanks in advance
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Hi, @alcanunsal, sorry for the late response!
We trained model in 2 steps. For first step we did not use eye loss and set other weights as follows: weight_adv 1 --weight_attr 10 --weight_id 15 --weight_rec 10
. For second training part we changed identity loss weight to 70 and set eye loss as --weight_eyes 1200
. To make source person attributes stronger you should increase weights for id and eye losses.
We trained the model for 8 epochs and 2 epochs, respectively.
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@AlexanderGroshev could u please tell me the train time? I set batch size=32 and run on V100, it takes 16 hours for one epoch. 8+2=10 epochs mean that it will take 6 days to finish.
I'd really appreciate it if u can upload training logs.
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