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68-retinaface-pytorch-version's Issues

Training Data

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"

Why my loss is lower?

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.

The landmark loss reduces slowly.

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?

question about lip weights in loss function

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.
image
May I ask which two points 99 and 37 represent?

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