Pyramid Attention Networks Pytorch Save
Implementation of Pyramid Attention Networks for Semantic Segmentation.
Project README
PAN-pytorch
A Pytorch implementation of Pyramid Attention Networks for Semantic Segmentation from 2018 paper by Hanchao Li, Pengfei Xiong, Jie An, Lingxue Wang.
Installation
- Env: Python3.6, Pytorch1.0-preview
- Clone this repository.
- Download the dataset by following the instructions below.
VOC2012 Dataset
The overall dataset is augmented by Semantic Boundaries Dataset, resulting in training data 10582 and test data 1449. https://www.sun11.me/blog/2018/how-to-use-10582-trainaug-images-on-DeeplabV3-code/
After preparing the data, please change the directory below for training.
training_data = Voc2012('/home/tom/DISK/DISK2/jian/PASCAL/VOC2012', 'train_aug', transform=train_transforms)
test_data = Voc2012('/home/tom/DISK/DISK2/jian/PASCAL/VOC2012', 'val',transform=test_transforms)
Evaluation
| Pixel acc | mIOU |
|---|---|
| 93.19% | 78.498% |
Open Source Agenda is not affiliated with "Pyramid Attention Networks Pytorch" Project. README Source: JaveyWang/Pyramid-Attention-Networks-pytorch
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