Open raviy0807 opened 1 year ago
Our pretrained encoder works for non-ImageNet images, such as MS-COCO giraffes, Yosemite landscapes and Artistic portraits. I think you can try the pretrained encoder first to see whether it also works for your Non-Spoof Images and Spoof Images.
If it does not work, you can add your data into ImageNet291 just as 1001_face for training
Thank you @williamyang1991
I will try pretrained encoder, but it just from my experience it does not works well as spoof faces have high degree of variation.
Now if i take 2nd method of training the encoder. Then following are the question based on only 1 read:
Download CelebA-HQ and put the 29000 training images and 1000 testing images to ImageNet291/train/1001_face/ and ImageNet291/test/1001_face/, respectively.
As written in data preparation, should i simple create 2 folder :
Idea is to understand how to add new classes and perform on new task.
Hi,
I referred to data_preparation but its not clear if i want to use this GP-UNIT for custom dataset where encoder training will also be required.
For example, I have dataset of Face Spoof attack like https://paperswithcode.com/dataset/casia-mfsd . Where my task is to convert Non-Spoof Images to Spoof Images.
So my understanding is , I would require to re-train the encoder as task and encoder data is totally different. Please, let me know if that's not the case ?
Now, assuming i would like to train the encoder only on spoof face and non spoof face image. How would i train the encoder and prepare the data?
Thanks for the great work @williamyang1991