I’m making a system that can detect faces from artistic paintings. I use for this the face.evoLVe repo from
https://github.com/ZhaoJ9014/face.evoLVe.PyTorch
face.evoLVe uses an MTCNN for the facial detection and works brialliantly on real world images. However, I want to fine tune it using transfer learning to work on artistic painting such as the Mona Lisa.
I tried the tutorial on the PyTorch website, https://pytorch.org/tutorials/beginner/transfer_learning_tutorial.html
However, I’m not very sure on where to include the model from face.evoLVe. Since it is an MTCNN, I assume I only have to fine tune the pnet.npy.
For the dataset on what it should fine tune I was thinking about having a dataset with two categories: faces and not-faces.