Gated Multi-Level Wavelet Convolutional Neural Networks in Semantic Segmentation, the three authors Logan Lawrence, Runfa Li, Zihan Li are contributed equally to this work.
We totally use Cityscapes Dataset for this work. Specifically we use gt_Fine for labelset and leftImg8bit for imageset, from Cityscapes official website. To implement our code, please first prepare the dataset, then go to the directory /configs/ to change the data path of all yaml files.
For training a specific model, use train_%%%.py, our code use multi-gpu for training, a directory /run/ will be built automatically once start training, and the checkpoint will be saved there
To test a specific model, use validate_mwcnn.py, but make sure to change the configs file to the model you are testing at line 103, and modify the path to the checkpoint at line 111.
To visulize the segmentation map of the prediction, using visualize_mwcnn.ipynb, follow the instruction in the jupyter notebook file.
Submitted Project Paper on 12/21/2020.