This work has been published in arXiv: ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation.
- train contains tools for training network using various architectures. It can be further used for visulaization of network's performance. This section is mainly for pixelwise segmentation and scene-parsing.
- visualize can be used to view the performance of trained network on any video/image as an overlay. (Will be added soon)
Find a train model here: https://www.dropbox.com/sh/dywzk3gyb12hpe5/AAD5YkUa8XgMpHs2gCRgmCVCa
This software is released under a creative commons license which allows for personal and research use only. For a commercial license please contact the authors. You can view a license summary here: http://creativecommons.org/licenses/by-nc/4.0/