Awesome

Richer Convolutional Features for Edge Detection

Thanks to <a href="https://github.com/yun-liu">yun-liu's</a> help. Created by XuanyiLi, if you have any problem in using it, please contact:xuanyili.edu@gmail.com. The best result of my pytorch model is 0.808 ODS F-score now.

my model result

the following are the side outputs and the prediction example

Citation

If you find our work useful in your research, please consider citing:

@article{RcfEdgePami2019, author = {Yun Liu and Ming-Ming Cheng and Xiaowei Hu and Jia-Wang Bian and Le Zhang and Xiang Bai and Jinhui Tang}, title = {Richer Convolutional Features for Edge Detection}, year = {2019}, journal= {IEEE Trans. Pattern Anal. Mach. Intell.}, volume={}, number={}, pages={}, doi = {}, }

@inproceedings{RCFEdgeCVPR2017, title={Richer Convolutional Features for Edge Detection}, author={Yun Liu and Ming-Ming Cheng, Xiaowei Hu and K Wang and X Bai}, booktitle={IEEE CVPR}, year={2017}, }

online demo(upload your own image):😋

<a href="http://mc.nankai.edu.cn/edge">online demo link</a>

Video demo:😋

this is the edge version of movie Titanic: <a href="https://www.youtube.com/channel/UC_6UOBTYzBzA6s0EZSeTh1g">youtube video link</a> Titanic example

Introduction

I implement the edge detection model according to the <a href="https://github.com/yun-liu/rcf">RCF</a> model in pytorch.

the result of my pytorch model will be released in the future

Method	ODS F-score on BSDS500 dataset	ODS F-score on NYU Depth dataset
ours	0.808	***
Reference[1]	0.811	***

Installation

Install <a href="https://pytorch.org/">pytorch</a>. The code is tested under 0.4.1 GPU version and Python 3.6 on Ubuntu 16.04. There are also some dependencies for a few Python libraries for data processing and visualizations like cv2 etc. It's highly recommended that you have access to GPUs.

Usage

image edge detection

To train a RCF model on BSDS500:

    python train_RCF.py

After training, to evaluate:

    python evaluate.py (for further work)

<i>Side Note:</i> Hello mingyang, I love you

License

Our code is released under MIT License (see LICENSE file for details).

Updates

To do

Add support for multi-gpu training for the edge detetion task.
Improve the performance to 0.806/0.811 in the original paper.
Add a gpu version of edge-eval code to accelerate the evaluation process.
Add pami version of RCF.

source：

To download the pretrained model, please click https://drive.google.com/open?id=1TupHeoBKawrniDka0Hc64m3BG4OKG8nM (This pretrained model is not the best model, just for communicating)
To download the vgg16 pretrained model which is used for the backbone. please click https://drive.google.com/file/d/1lUhPKKj-BSOH7yQL0mOIavvrUbjydPp5/view?usp=sharing.

Related Projects

[1] <a href="https://github.com/yun-liu/rcf">Richer Convolutional Features for Edge Detection</a>

[2] <a href="https://github.com/s9xie/hed">HED</a>

[3] <a href="https://github.com/zeakey/hed">HED</a> created by <a href="https://github.com/zeakey">zeakey's</a>

[4] <a href="https://github.com/godman2016/ContourNet">ContourNet</a>