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* update LoveDA dataset api * revised lint errors in dataset_prepare.md * revised lint errors in loveda.py * revised lint errors in loveda.py * revised lint errors in dataset_prepare.md * revised lint errors in dataset_prepare.md * checked with isort and yapf * checked with isort and yapf * checked with isort and yapf * Revert "checked with isort and yapf" This reverts commit 686a51d9 * Revert "checked with isort and yapf" This reverts commit b877e121bb2935ceefc503c09675019489829feb. * Revert "revised lint errors in dataset_prepare.md" This reverts commit 2289e27c * Revert "checked with isort and yapf" This reverts commit 159db2f8 * Revert "checked with isort and yapf" This reverts commit 159db2f8 * add configs & fix bugs * update new branch * upload models&logs and add format-only * change pretraied model path of HRNet * fix the errors in dataset_prepare.md * fix the errors in dataset_prepare.md and configs in loveda.py * change the description in docs_zh-CN/dataset_prepare.md * use init_cfg * fix test converage * adding pseudo loveda dataset * adding pseudo loveda dataset * adding pseudo loveda dataset * adding pseudo loveda dataset * adding pseudo loveda dataset * adding pseudo loveda dataset * Update docs/dataset_prepare.md Co-authored-by: Junjun2016 <hejunjun@sjtu.edu.cn> * Update docs_zh-CN/dataset_prepare.md Co-authored-by: Junjun2016 <hejunjun@sjtu.edu.cn> * Update docs_zh-CN/dataset_prepare.md Co-authored-by: Junjun2016 <hejunjun@sjtu.edu.cn> * Delete unused lines of unittest and Add docs * add convert .py file * add downloading links from zenodo * move place of LoveDA and Cityscapes in doc * move place of LoveDA and Cityscapes in doc Co-authored-by: MengzhangLI <mcmong@pku.edu.cn> Co-authored-by: Junjun2016 <hejunjun@sjtu.edu.cn>
Pyramid Scene Parsing Network
Introduction
PSPNet (CVPR'2017)
@inproceedings{zhao2017pspnet,
title={Pyramid Scene Parsing Network},
author={Zhao, Hengshuang and Shi, Jianping and Qi, Xiaojuan and Wang, Xiaogang and Jia, Jiaya},
booktitle={CVPR},
year={2017}
}
Results and models
Cityscapes
| Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU | mIoU(ms+flip) | config | download |
|---|---|---|---|---|---|---|---|---|---|
| PSPNet | R-50-D8 | 512x1024 | 40000 | 6.1 | 4.07 | 77.85 | 79.18 | config | model | log |
| PSPNet | R-101-D8 | 512x1024 | 40000 | 9.6 | 2.68 | 78.34 | 79.74 | config | model | log |
| PSPNet | R-50-D8 | 769x769 | 40000 | 6.9 | 1.76 | 78.26 | 79.88 | config | model | log |
| PSPNet | R-101-D8 | 769x769 | 40000 | 10.9 | 1.15 | 79.08 | 80.28 | config | model | log |
| PSPNet | R-18-D8 | 512x1024 | 80000 | 1.7 | 15.71 | 74.87 | 76.04 | config | model | log |
| PSPNet | R-50-D8 | 512x1024 | 80000 | - | - | 78.55 | 79.79 | config | model | log |
| PSPNet | R-101-D8 | 512x1024 | 80000 | - | - | 79.76 | 81.01 | config | model | log |
| PSPNet (FP16) | R-101-D8 | 512x1024 | 80000 | 5.34 | 8.77 | 79.46 | - | config | model | log |
| PSPNet | R-18-D8 | 769x769 | 80000 | 1.9 | 6.20 | 75.90 | 77.86 | config | model | log |
| PSPNet | R-50-D8 | 769x769 | 80000 | - | - | 79.59 | 80.69 | config | model | log |
| PSPNet | R-101-D8 | 769x769 | 80000 | - | - | 79.77 | 81.06 | config | model | log |
| PSPNet | R-18b-D8 | 512x1024 | 80000 | 1.5 | 16.28 | 74.23 | 75.79 | config | model | log |
| PSPNet | R-50b-D8 | 512x1024 | 80000 | 6.0 | 4.30 | 78.22 | 79.46 | config | model | log |
| PSPNet | R-101b-D8 | 512x1024 | 80000 | 9.5 | 2.76 | 79.69 | 80.79 | config | model | log |
| PSPNet | R-18b-D8 | 769x769 | 80000 | 1.7 | 6.41 | 74.92 | 76.90 | config | model | log |
| PSPNet | R-50b-D8 | 769x769 | 80000 | 6.8 | 1.88 | 78.50 | 79.96 | config | model | log |
| PSPNet | R-101b-D8 | 769x769 | 80000 | 10.8 | 1.17 | 78.87 | 80.04 | config | model | log |
ADE20K
| Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU | mIoU(ms+flip) | config | download |
|---|---|---|---|---|---|---|---|---|---|
| PSPNet | R-50-D8 | 512x512 | 80000 | 8.5 | 23.53 | 41.13 | 41.94 | config | model | log |
| PSPNet | R-101-D8 | 512x512 | 80000 | 12 | 15.30 | 43.57 | 44.35 | config | model | log |
| PSPNet | R-50-D8 | 512x512 | 160000 | - | - | 42.48 | 43.44 | config | model | log |
| PSPNet | R-101-D8 | 512x512 | 160000 | - | - | 44.39 | 45.35 | config | model | log |
Pascal VOC 2012 + Aug
| Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU | mIoU(ms+flip) | config | download |
|---|---|---|---|---|---|---|---|---|---|
| PSPNet | R-50-D8 | 512x512 | 20000 | 6.1 | 23.59 | 76.78 | 77.61 | config | model | log |
| PSPNet | R-101-D8 | 512x512 | 20000 | 9.6 | 15.02 | 78.47 | 79.25 | config | model | log |
| PSPNet | R-50-D8 | 512x512 | 40000 | - | - | 77.29 | 78.48 | config | model | log |
| PSPNet | R-101-D8 | 512x512 | 40000 | - | - | 78.52 | 79.57 | config | model | log |
Pascal Context
| Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU | mIoU(ms+flip) | config | download |
|---|---|---|---|---|---|---|---|---|---|
| PSPNet | R-101-D8 | 480x480 | 40000 | 8.8 | 9.68 | 46.60 | 47.78 | config | model | log |
| PSPNet | R-101-D8 | 480x480 | 80000 | - | - | 46.03 | 47.15 | config | model | log |
Pascal Context 59
| Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU | mIoU(ms+flip) | config | download |
|---|---|---|---|---|---|---|---|---|---|
| PSPNet | R-101-D8 | 480x480 | 40000 | - | - | 52.02 | 53.54 | config | model | log |
| PSPNet | R-101-D8 | 480x480 | 80000 | - | - | 52.47 | 53.99 | config | model | log |
Dark Zurich and Nighttime Driving
We support evaluation results on these two datasets using models above trained on Cityscapes training set.
| Method | Backbone | Training Dataset | Test Dataset | mIoU | config | evaluation checkpoint |
|---|---|---|---|---|---|---|
| PSPNet | R-50-D8 | Cityscapes Training set | Dark Zurich | 10.91 | config | model | log |
| PSPNet | R-50-D8 | Cityscapes Training set | Nighttime Driving | 23.02 | config | model | log |
| PSPNet | R-50-D8 | Cityscapes Training set | Cityscapes Validation set | 77.85 | config | model | log |
| PSPNet | R-101-D8 | Cityscapes Training set | Dark Zurich | 10.16 | config | model | log |
| PSPNet | R-101-D8 | Cityscapes Training set | Nighttime Driving | 20.25 | config | model | log |
| PSPNet | R-101-D8 | Cityscapes Training set | Cityscapes Validation set | 78.34 | config | model | log |
| PSPNet | R-101b-D8 | Cityscapes Training set | Dark Zurich | 15.54 | config | model | log |
| PSPNet | R-101b-D8 | Cityscapes Training set | Nighttime Driving | 22.25 | config | model | log |
| PSPNet | R-101b-D8 | Cityscapes Training set | Cityscapes Validation set | 79.69 | config | model | log |
COCO-Stuff 10k
| Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU | mIoU(ms+flip) | config | download |
|---|---|---|---|---|---|---|---|---|---|
| PSPNet | R-50-D8 | 512x512 | 20000 | 9.6 | 20.5 | 35.69 | 36.62 | config | model | log |
| PSPNet | R-101-D8 | 512x512 | 20000 | 13.2 | 11.1 | 37.26 | 38.52 | config | model | log |
| PSPNet | R-50-D8 | 512x512 | 40000 | - | - | 36.33 | 37.24 | config | model | log |
| PSPNet | R-101-D8 | 512x512 | 40000 | - | - | 37.76 | 38.86 | config | model | log |
COCO-Stuff 164k
| Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU | mIoU(ms+flip) | config | download |
|---|---|---|---|---|---|---|---|---|---|
| PSPNet | R-50-D8 | 512x512 | 80000 | 9.6 | 20.5 | 38.80 | 39.19 | config | model | log |
| PSPNet | R-101-D8 | 512x512 | 80000 | 13.2 | 11.1 | 40.34 | 40.79 | config | model | log |
| PSPNet | R-50-D8 | 512x512 | 160000 | - | - | 39.64 | 39.97 | config | model | log |
| PSPNet | R-101-D8 | 512x512 | 160000 | - | - | 41.28 | 41.66 | config | model | log |
| PSPNet | R-50-D8 | 512x512 | 320000 | - | - | 40.53 | 40.75 | config | model | log |
| PSPNet | R-101-D8 | 512x512 | 320000 | - | - | 41.95 | 42.42 | config | model | log |
LoveDA
| Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU | mIoU(ms+flip) | config | download |
|---|---|---|---|---|---|---|---|---|---|
| PSPNet | R-18-D8 | 512x512 | 80000 | 1.45 | 26.87 | 48.62 | 47.57 | config | model | log |
| PSPNet | R-50-D8 | 512x512 | 80000 | 6.14 | 6.60 | 50.46 | 50.19 | config | model | log |
| PSPNet | R-101-D8 | 512x512 | 80000 | 9.61 | 4.58 | 51.86 | 51.34 | config | model | log |
Note:
FP16means Mixed Precision (FP16) is adopted in training.