-
Notifications
You must be signed in to change notification settings - Fork 1
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
- Loading branch information
1 parent
9ffdc7a
commit b5faf7a
Showing
1 changed file
with
0 additions
and
67 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,68 +1 @@ | ||
| ## [Richer Convolutional Features for Edge Detection](http://mmcheng.net/rcfedge/) | ||
|
|
||
| This is the PyTorch implementation of our edge detection method, RCF. | ||
|
|
||
| ### Citations | ||
|
|
||
| If you are using the code/model/data provided here in a publication, please consider citing: | ||
|
|
||
| @article{liu2019richer, | ||
| title={Richer Convolutional Features for Edge Detection}, | ||
| author={Liu, Yun and Cheng, Ming-Ming and Hu, Xiaowei and Bian, Jia-Wang and Zhang, Le and Bai, Xiang and Tang, Jinhui}, | ||
| journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, | ||
| volume={41}, | ||
| number={8}, | ||
| pages={1939--1946}, | ||
| year={2019}, | ||
| publisher={IEEE} | ||
| } | ||
|
|
||
| ### Training | ||
|
|
||
| 1. Clone the RCF repository: | ||
| ``` | ||
| git clone https://github.com/yun-liu/RCF-PyTorch.git | ||
| ``` | ||
| 2. Download the ImageNet-pretrained model ([Google Drive](https://drive.google.com/file/d/1szqDNG3dUO6BM3l6YBuC9vWp16n48-cK/view?usp=sharing) or [Baidu Yun](https://pan.baidu.com/s/1vfntX-cTKnk58atNW5T1lA?pwd=g5af)), and put it into the `$ROOT_DIR` folder. | ||
| 3. Download the datasets as below, and extract these datasets to the `$ROOT_DIR/data/` folder. | ||
| ``` | ||
| wget http://mftp.mmcheng.net/liuyun/rcf/data/bsds_pascal_train_pair.lst | ||
| wget http://mftp.mmcheng.net/liuyun/rcf/data/HED-BSDS.tar.gz | ||
| wget http://mftp.mmcheng.net/liuyun/rcf/data/PASCAL.tar.gz | ||
| ``` | ||
| 4. Run the following command to start the training: | ||
| ``` | ||
| python train.py --save-dir /path/to/output/directory/ | ||
| ``` | ||
| ### Testing | ||
| 1. Download the pretrained model (BSDS500+PASCAL: [Google Drive](https://drive.google.com/file/d/1oxlHQCM4mm5zhHzmE7yho_oToU5Ucckk/view?usp=sharing) or [Baidu Yun](https://pan.baidu.com/s/1Tpf_-dIxHmKwH5IeClt0Ng?pwd=03ad)), and put it into the `$ROOT_DIR` folder. | ||
| 2. Run the following command to start the testing: | ||
| ``` | ||
| python test.py --checkpoint bsds500_pascal_model.pth --save-dir /path/to/output/directory/ | ||
| ``` | ||
| This pretrained model should achieve an ODS F-measure of 0.812. | ||
| For more information about RCF and edge quality evaluation, please refer to this page: [yun-liu/RCF](https://github.com/yun-liu/RCF) | ||
| ### Edge PR Curves | ||
| We have released the code and data for plotting the edge PR curves of many existing edge detectors [here](https://github.com/yun-liu/plot-edge-pr-curves). | ||
| ### RCF based on other frameworks | ||
| Caffe based RCF: [yun-liu/RCF](https://github.com/yun-liu/RCF) | ||
| Jittor based RCF: [yun-liu/RCF-Jittor](https://github.com/yun-liu/RCF-Jittor) | ||
| ### Acknowledgements | ||
| [1] [balajiselvaraj1601/RCF_Pytorch_Updated](https://github.com/balajiselvaraj1601/RCF_Pytorch_Updated) | ||
| [2] [meteorshowers/RCF-pytorch](https://github.com/meteorshowers/RCF-pytorch) |