Comments (1)
Hi @stencilman
Thanks a lot for you kind words and sorry for the delay. Unfortunatelly the code released for training is for real-valued models only. You can however easily adapt it for the binary case using this: https://github.com/allenai/XNOR-Net (you basically have to do some binarization related things at train time to make them "convertible").
You can binzarize them directly, but without the binarization at train time the performance will be very bad. The function you pointed out can binzarize them corectly only if you trained as described in the XNOR paper.
If you have any other questions, please let me know.
from binary-face-alignment.
Related Issues (12)
- Visualize the net structure! So complicated! HOT 6
- Training code
- The result of my training is very poor,why?
- conversion from bnn.SpatialConvolution and bnn.binary to nn or cudnn HOT 5
- Very large GPU memory consumption HOT 1
- where is the groundTruth in eval? HOT 1
- AFLWPIFA-val.tar can not download HOT 4
- Error when 'luarocks make' HOT 3
- Visualize the bounding box HOT 3
- How Can I preditct a new image? HOT 2
- How convert this model to pytorch? HOT 4
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from binary-face-alignment.