A lite-version hopenet for head pose estimation with PyTorch
Note
Hopenet-lite uses unofficial-implement ShuffleNetV2 as backbone
network, and now the lastest PyTorch contains official ShuffleNetV2 with
various width. If you are seeking for stable performance, please use
official implementation and re-train hopenet-lite! ''' import torchvision.models as models shufflenet = models.shufflenet_v2_x1_0(pretrained=True) ... https://pytorch.org/docs/stable/torchvision/models.html#classification
Doc.
The project is based on natanielruiz's excellent work named Hopenet.
The Pre-trained model in "model" folder, but the model is not very robust to image quality, we will release more
robust model in the future.
Thanks for natanielruiz's excellent work again.
Update
Hi, guys, I finally have time to update this project... I uploaded the lastest hopenet-lite model with official ShuffleNetV2 from Pytorch torchvision, you can use it like this: ''' import stable_hopenetlite pos_net = stable_hopenetlite.shufflenet_v2_x1_0() saved_state_dict = torch.load('model/shuff_epoch_120.pkl', map_location="cpu") pos_net.load_state_dict(saved_state_dict, strict=False) pos_net.eval() ''' The Pre-trained model named "shuff_epoch_120.pkl" in "model" folder. If
you think my training is not perfect, you could re-train the model. Just
enjoy yourself !