🔥🔥🔥The code for SCG: Saliency and Contour Guided Salient Instance Segmentation🔥🔥🔥
- As it is suggested in RDPNet, we plan to use official cocoapi to evaluate the performance, for the convenience of future work.
1.Build. Follow the installation instructions of maskrcnn-benchmark.
2.Train. The whole network, the saliency branch, and the contour branch will be iteratively trained.
cd tools
python train_net.py --config-file configs/e2e_mask_rcnn_R_50_FPN_1x.yaml
3.Test and Eval. We adopt the same evaluation code as S4Net.
cd tools
python test_net.py
We adopt the training set of ILSO to train the Mask R-CNN part, and you can download the dataset in pickle format from Link (57ej). DUTS and PASCAL VOS Context are adopted to train the saliency and contour branch, respectively. You can find the pre-processed data in PoolNet.
We provide the pretrained models for SCG and SCG* in Google Drive and Baidu Drive(vi0x). Please put the pretrained model in ./tools/.
This repository is built upon maskrcnn-benchmark and S4Net.