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README.md
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## Introduction
<a href="https://github.com/facebookresearch/detectron2">Official Repo</a>
<a href="https://github.com/SegmentationBLWX/sssegmentation/blob/main/ssseg/modules/models/segmentors/semanticfpn/semanticfpn.py">Code Snippet</a>
<details>
<summary align="left"><a href="https://arxiv.org/pdf/1901.02446.pdf">Semantic FPN (CVPR'2019)</a></summary>
```latex
@article{Kirillov_2019,
title={Panoptic Feature Pyramid Networks},
ISBN={9781728132938},
url={http://dx.doi.org/10.1109/CVPR.2019.00656},
DOI={10.1109/cvpr.2019.00656},
journal={2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
publisher={IEEE},
author={Kirillov, Alexander and Girshick, Ross and He, Kaiming and Dollar, Piotr},
year={2019},
month={Jun}
}
```
</details>
## Results
#### PASCAL VOC
| Backbone | Pretrain | Crop Size | Schedule | Train/Eval Set | mIoU | Download |
| :-: | :-: | :-: | :-: | :-: | :-: | :-: |
| R-50-D32 | ImageNet-1k-224x224 | 512x512 | LR/POLICY/BS/EPOCH: 0.01/poly/16/60 | trainaug/val | 70.88% | [cfg](https://raw.githubusercontent.com/SegmentationBLWX/sssegmentation/main/ssseg/configs/semanticfpn/semanticfpn_resnet50os32_voc.py) | [model](https://github.com/SegmentationBLWX/modelstore/releases/download/ssseg_semanticfpn/semanticfpn_resnet50os32_voc.pth) | [log](https://github.com/SegmentationBLWX/modelstore/releases/download/ssseg_semanticfpn/semanticfpn_resnet50os32_voc.log) |
| R-101-D32 | ImageNet-1k-224x224 | 512x512 | LR/POLICY/BS/EPOCH: 0.01/poly/16/60 | trainaug/val | 72.51% | [cfg](https://raw.githubusercontent.com/SegmentationBLWX/sssegmentation/main/ssseg/configs/semanticfpn/semanticfpn_resnet101os32_voc.py) | [model](https://github.com/SegmentationBLWX/modelstore/releases/download/ssseg_semanticfpn/semanticfpn_resnet101os32_voc.pth) | [log](https://github.com/SegmentationBLWX/modelstore/releases/download/ssseg_semanticfpn/semanticfpn_resnet101os32_voc.log) |
#### ADE20k
| Backbone | Pretrain | Crop Size | Schedule | Train/Eval Set | mIoU | Download |
| :-: | :-: | :-: | :-: | :-: | :-: | :-: |
| R-50-D32 | ImageNet-1k-224x224 | 512x512 | LR/POLICY/BS/EPOCH: 0.01/poly/16/130 | train/val | 38.16% | [cfg](https://raw.githubusercontent.com/SegmentationBLWX/sssegmentation/main/ssseg/configs/semanticfpn/semanticfpn_resnet50os32_ade20k.py) | [model](https://github.com/SegmentationBLWX/modelstore/releases/download/ssseg_semanticfpn/semanticfpn_resnet50os32_ade20k.pth) | [log](https://github.com/SegmentationBLWX/modelstore/releases/download/ssseg_semanticfpn/semanticfpn_resnet50os32_ade20k.log) |
| R-101-D32 | ImageNet-1k-224x224 | 512x512 | LR/POLICY/BS/EPOCH: 0.01/poly/16/130 | train/val | 39.85% | [cfg](https://raw.githubusercontent.com/SegmentationBLWX/sssegmentation/main/ssseg/configs/semanticfpn/semanticfpn_resnet101os32_ade20k.py) | [model](https://github.com/SegmentationBLWX/modelstore/releases/download/ssseg_semanticfpn/semanticfpn_resnet101os32_ade20k.pth) | [log](https://github.com/SegmentationBLWX/modelstore/releases/download/ssseg_semanticfpn/semanticfpn_resnet101os32_ade20k.log) |
#### CityScapes
| Backbone | Pretrain | Crop Size | Schedule | Train/Eval Set | mIoU | Download |
| :-: | :-: | :-: | :-: | :-: | :-: | :-: |
| R-50-D32 | ImageNet-1k-224x224 | 512x1024 | LR/POLICY/BS/EPOCH: 0.01/poly/8/220 | train/val | 76.09% | [cfg](https://raw.githubusercontent.com/SegmentationBLWX/sssegmentation/main/ssseg/configs/semanticfpn/semanticfpn_resnet50os32_cityscapes.py) | [model](https://github.com/SegmentationBLWX/modelstore/releases/download/ssseg_semanticfpn/semanticfpn_resnet50os32_cityscapes.pth) | [log](https://github.com/SegmentationBLWX/modelstore/releases/download/ssseg_semanticfpn/semanticfpn_resnet50os32_cityscapes.log) |
| R-101-D32 | ImageNet-1k-224x224 | 512x1024 | LR/POLICY/BS/EPOCH: 0.01/poly/8/220 | train/val | 76.39% | [cfg](https://raw.githubusercontent.com/SegmentationBLWX/sssegmentation/main/ssseg/configs/semanticfpn/semanticfpn_resnet101os32_cityscapes.py) | [model](https://github.com/SegmentationBLWX/modelstore/releases/download/ssseg_semanticfpn/semanticfpn_resnet101os32_cityscapes.pth) | [log](https://github.com/SegmentationBLWX/modelstore/releases/download/ssseg_semanticfpn/semanticfpn_resnet101os32_cityscapes.log) |
## More
You can also download the model weights from following sources:
- BaiduNetdisk: https://pan.baidu.com/s/1gD-NJJWOtaHCtB0qHE79rA with access code **s757**