Pytorch Implementation of ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation

TODO

• Implement Enet network
• Train Enet on Camvid Dataset
• Train Enet on Cityscapes Dataset
• Test with Lovasz Softmax Loss

Camvid Dataset

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• This dataset consists of street images whose pixels are labeled into 11+1 classes (one "Void" class for the ego-car)
• Run

bash ./scripts/download_camvid.sh

to fetch and unzip the dataset into data directory

Colors for Each Label Class

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How To

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• Train on Camvid:

python3 camvid_train.py

• Test on test set of Camvid

python3 ./scripts/test_camvid_testset.py

You should see the following result:

References

• Original Implementation
• Reference pytorch implementation of Enet