elvishelvis / 68-retinaface-pytorch-version Goto Github PK

hi.
Thanks for sharing such a nice code.
When I tried your code, I found in losses.py, there are two lines to add lip weighted when compute landmarks loss, but seems idx 99 and idx 37 not the lips idx.

May I ask which two points 99 and 37 represent?

RuntimeError: Input type (torch.FloatTensor) and weight type (torch.cuda.FloatTensor) should be the same

Hello, thank you for your sharing.
I'm developing the retinaface too, could you please provide the training data?
I want to know the content in path1 = "/versa/elvishelvis/RetinaFace_Pytorch/CelebA/Anno/list_bbox_celeba.txt" and path2 = "/versa/elvishelvis/RetinaFace_Pytorch/CelebA/Anno/list_landmarks_celeba.txt"

I use LS3D-W dataset , when I training, the loss is lower .. expamle: total_loss : 1.1131469011306763 classification: 0.70500928 bbox: 0.07543718814849854 landmark: 0.6654008626937866 .
Check whether the fault is rectified.

Hello, ElvishElvis.
Thank you for your great work!
I change the backbone to mobilenet_v3 and regnet, and use the LS3D-W dataset as my training dataset. But the landmark branch loss reduces slowly (using smoothL1 Loss), for example, 1.79 -> 1.77 after 20 epochs, while the other losses reduces normally.
So, have you met this problem? And could you share your training strategy if possible?

i want to know the input size ，now i have a task that very urgent