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cityscapes

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Lightweight models for real-time semantic segmentationon PyTorch (include SQNet, LinkNet, SegNet, UNet, ENet, ERFNet, EDANet, ESPNet, ESPNetv2, LEDNet, ESNet, FSSNet, CGNet, DABNet, Fast-SCNN, ContextNet, FPENet, etc.)

  • Updated Jun 21, 2022
  • Python
10
JadenLy
JadenLy commented May 25, 2022

Hello,

I am doing a school project and came across your paper on BezierLaneNet. I really like the idea and I am trying to implement it. One thing I do notice is that you opted to use mmcv for deformable convolution layer. I wonder if you think it is possible to replace it with the deform_conv2d layer provided by PyTorch as [here](https://pytorch.org/vision/main/generated/torchvision.ops.def

ogail
ogail commented Mar 7, 2018

Hi,
I tried to follow README instructions for training on my own dataset but it didn't work. Here is what I did:

  • Update DATA_DIR to point to dataset dir
  • Update DATA_LIST_PATH to point to train dataset list file.
  • Update INPUT_SIZE to '1280, 720'
  • Update NUM_CLASSES to 1
  • Update LAMBDA1 and LAMBDA2 to 0.4 and 0.6 respectively.

Then ran cmd

python train.py

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