MT-Segmentation
@misc{mt-segmentation,
author = {Ansheng You, Zhenhua Chai},
title = {MT-Segmentation},
howpublished = {\url{http://git.sankuai.com/users/youansheng/repos/mt-segmentation}},
year = {2020}
}
This repository provides source code for most deep learning based cv problems. We'll do our best to keep this repository up-to-date. If you do find a problem about this repository, please raise an issue or submit a pull request.
Implemented Papers
- Semantic Segmentation
- DeepLabV3: Rethinking Atrous Convolution for Semantic Image Segmentation
- PSPNet: Pyramid Scene Parsing Network
- DenseASPP: DenseASPP for Semantic Segmentation in Street Scenes
- Asymmetric Non-local Neural Networks for Semantic Segmentation
QuickStart with TorchCV
Now only support Python3.x, pytorch 1.3.
pip3 install -r requirements.txt
cd lib/exts
sh make.shPerformances with MT-Segmentation
All the performances showed below fully reimplemented the papers' results.
Semantic Segmentation
- Cityscapes (Single Scale Whole Image Test): Base LR 0.01, Crop Size 769
| Model | Backbone | Train | Test | mIOU | BS | Iters | Scripts |
|---|---|---|---|---|---|---|---|
| PSPNet | 3x3-Res101 | train | val | 78.20 | 8 | 4W | PSPNet |
| DeepLabV3 | 3x3-Res101 | train | val | 79.13 | 8 | 4W | DeepLabV3 |
- ADE20K (Single Scale Whole Image Test): Base LR 0.02, Crop Size 520
| Model | Backbone | Train | Test | mIOU | PixelACC | BS | Iters | Scripts |
|---|---|---|---|---|---|---|---|---|
| PSPNet | 3x3-Res50 | train | val | 41.52 | 80.09 | 16 | 15W | PSPNet |
| DeepLabv3 | 3x3-Res50 | train | val | 42.16 | 80.36 | 16 | 15W | DeepLabV3 |
| PSPNet | 3x3-Res101 | train | val | 43.60 | 81.30 | 16 | 15W | PSPNet |
| DeepLabv3 | 3x3-Res101 | train | val | 44.13 | 81.42 | 16 | 15W | DeepLabV3 |
Commands with MT-Segmentation
Take PSPNet as an example. ("tag" could be any string, include an empty one.)
- Training
cd scripts/cityscapes/
bash run_fs_pspnet_cityscapes_seg.sh train tag- Resume Training
cd scripts/cityscapes/
bash run_fs_pspnet_cityscapes_seg.sh train tag- Validate
cd scripts/cityscapes/
bash run_fs_pspnet_cityscapes_seg.sh val tag- Testing:
cd scripts/cityscapes/
bash run_fs_pspnet_cityscapes_seg.sh test tag