Comments (1)
Yes, currently it's redundant, but not because we fix BN. It's due to the fact that current models have no BN layer in the decoder. Note that we only fix BN for the encoder, where we do not train the BN parameters transferred from other models.
However, as introduced in README,
Add 'phase' argument in network.py for future development. 'phase=True' means training. It is mainly for controlling batch normalization (if any) in the non-pre-trained part.
What you mention here is for the same purpose. I put it in this way in case I add a BN in the decoder part.
from deeplab-v2--resnet-101--tensorflow.
Related Issues (20)
- Optimizer choice: Adam VS SGD HOT 1
- Another dataset HOT 4
- Problem with pre-trained model HOT 1
- Results for VOC2012 are not correct HOT 3
- Training Cityscapes - Changes in label_utils.py HOT 1
- pretrain model download
- How to process the outline of the object in Segmentation label images? HOT 1
- The problem about paper "Smoothed Dilated Convolutions for Improved Dense Prediction". HOT 1
- Which part of your code corresponds to the CRF in Deeplab V2? HOT 1
- How to predict dynamically from graph HOT 1
- A question about paper "Smoothed Dilated Convolutions for Improved Dense Prediction" HOT 2
- NotFoundError (see above for traceback): Tensor name HOT 3
- only can train 2images HOT 1
- Can I input 6 channel images for training? HOT 2
- how about results(mIoU) on validation set and test set HOT 2
- Hi, could you please implement it on cityscape? HOT 3
- how about the hyperparms of cityscape
- ABOUT BATCHSIZE WHEN TRAINING ON CITYSCAPES HOT 1
- It is OOM. Try reducing input_height and input_width. HOT 1
- resnet101 ------- miou 70.7% HOT 2
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from deeplab-v2--resnet-101--tensorflow.