Comments (1)
There are lots of reason to cause this.
- Deep learning technique is not stable.
- The implemented method in this repo is old, so the miou isn't competitive.
- In reality, semantic segmentation will need lots of pre-process and post-process (such as CRF).
from fcn-pytorch.
Related Issues (20)
- How to use test trained model? HOT 1
- hi bor~how can i inference it by my own picture? HOT 2
- pytorch 0.4.1 support? HOT 1
- Hi,the ranges of 'vgg16' have some error?
- ValueError: Target size (torch.Size([2, 32, 480, 640])) must be the same as input size (torch.Size([2, 20, 480, 640])) HOT 2
- deconvolution weight HOT 1
- Cityscapes_utils.py
- can you release the inference code? HOT 1
- can you provide a inference code?
- how much is the loss?
- why 'cnn-relu-bn' not' cnn-bn-relu'
- where is FCNs implementation from? HOT 1
- RuntimeError: The size of tensor a (44) must match the size of tensor b (45) at non-singleton dimension 2 HOT 4
- Why the train_h and val_h is different?
- loading pretrained weights
- validation loss
- where is label_colors.txt
- running speed
- Why using BCELoss? That is for binary classification while we have 20 classes HOT 1
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from fcn-pytorch.