Inference Code for RetinaFace with MobileNet Backend in PyTorch
cd cython
python setup.py build_ext --inplacepython inference.pyEasy Val AP: 0.8872715908531869
Medium Val AP: 0.8663337842229522
Hard Val AP: 0.771796729363941
@inproceedings{deng2019retinaface, title={RetinaFace: Single-stage Dense Face Localisation in the Wild}, author={Deng, Jiankang and Guo, Jia and Yuxiang, Zhou and Jinke Yu and Irene Kotsia and Zafeiriou, Stefanos}, booktitle={arxiv}, year={2019} }
Hello!
Could you please release the training script for your code? So that we can finetune the pytorch model that you generate from the MXNET.
Thanks!
We cannot convert the model to a JIT representation for use within C++ unless it returns a Tensor or Tuple of Tensors.
Hence, with a simple change this is fixed.
See: xsacha@da0a5bc
Cython anchors Error
Hi
Could you please to tell me which IDE are using?
Best regards,
PeterPham
Why is the centre... off-centre? This surely creates bias in the training.
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