Awesome
DeepLab
Introduction
DeepLab is a state-of-art deep learning system for semantic image segmentation built on top of Caffe.
It combines densely-computed deep convolutional neural network (CNN) responses with densely connected conditional random fields (CRF).
This distribution provides a publicly available implementation for the key model ingredients first reported in an arXiv paper, accepted in revised form as conference publication to the ICLR-2015 conference. It also contains implementations for methods supporting model learning using only weakly labeled examples, described in a second follow-up arXiv paper. Please consult and consider citing the following papers:
@inproceedings{chen14semantic,
title={Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs},
author={Liang-Chieh Chen and George Papandreou and Iasonas Kokkinos and Kevin Murphy and Alan L Yuille},
booktitle={ICLR},
url={http://arxiv.org/abs/1412.7062},
year={2015}
}
@article{papandreou15weak,
title={Weakly- and Semi-Supervised Learning of a DCNN for Semantic Image Segmentation},
author={George Papandreou and Liang-Chieh Chen and Kevin Murphy and Alan L Yuille},
journal={arxiv:1502.02734},
year={2015}
}
Note that if you use the densecrf implementation, please consult and cite the following paper:
@inproceedings{KrahenbuhlK11,
title={Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials},
author={Philipp Kr{\"{a}}henb{\"{u}}hl and Vladlen Koltun},
booktitle={NIPS},
year={2011}
}
Performance
DeepLab currently achieves 73.9% on the challenging PASCAL VOC 2012 image segmentation task -- see the leaderboard.
Pre-trained models
We have released several trained models and corresponding prototxt files at here. Please check it for more model details.
The best model among the released ones yields 73.6% on PASCAL VOC 2012 test set.
Python wrapper requirements
- Install wget library for python
sudo pip install wget
-
Change DATA_ROOT to point to the PASCAL images
-
To use the mat_read_layer and mat_write_layer, please download and install matio.
Running the code
python run.py
FAQ
Check FAQ if you have some problems while using the code.