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https://github.com/mitmul/chainer-pspnet
PSPNet in Chainer
https://github.com/mitmul/chainer-pspnet
ade20k chainer cityscapes convolutional-neural-networks deep-learning imagenet pascal-voc pspnet python semantic-segmentation
Last synced: about 2 months ago
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PSPNet in Chainer
- Host: GitHub
- URL: https://github.com/mitmul/chainer-pspnet
- Owner: mitmul
- Created: 2017-08-09T06:47:49.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2018-10-09T08:25:40.000Z (almost 6 years ago)
- Last Synced: 2024-07-08T16:40:21.531Z (2 months ago)
- Topics: ade20k, chainer, cityscapes, convolutional-neural-networks, deep-learning, imagenet, pascal-voc, pspnet, python, semantic-segmentation
- Language: Python
- Size: 78.1 KB
- Stars: 74
- Watchers: 4
- Forks: 18
- Open Issues: 5
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
PSPNet
======
This is an unofficial implementation of Pyramid Scene Parsing Network (PSPNet) in [Chainer](https://github.com/chainer/chainer).
# Training
## Requirement
- Python 3.4.4+
- Chainer 3.0.0b1+
- ChainerMN master
- CuPy 2.0.0b1+
- ChainerCV 0.6.0+
- NumPy 1.12.0+
- tqdm 4.11.0+
```
pip install chainer --pre
pip install cupy --pre
pip install git+git://github.com/chainer/chainermn
pip install git+git://github.com/chainer/chainercv
pip install tqdm
````
---
# Inference using converted weights
## Requirement
- Python 3.4.4+
- Chainer 3.0.0b1+
- ChainerCV 0.6.0+
- Matplotlib 2.0.0+
- CuPy 2.0.0b1+
- tqdm 4.11.0+
## 1. Run demo.py
### Cityscapes
```
$ python demo.py -g 0 -m cityscapes -f aachen_000000_000019_leftImg8bit.png
```
### Pascal VOC2012
```
$ python demo.py -g 0 -m voc2012 -f 2008_000005.jpg
```
### ADE20K
```
$ python demo.py -g 0 -m ade20k -f ADE_val_00000001.jpg
```
### FAQ
If you get `RuntimeError: Invalid DISPLAY variable`, how about specifying the matplotlib's backend by an environment variable?
```
$ MPLBACKEND=Agg python demo.py -g 0 -m cityscapes -f aachen_000000_000019_leftImg8bit.png
```
---
# Convert weights by yourself
**Caffe is NOT needed** to convert `.caffemodel` to Chainer model. Use `caffe_pb2.py`.
## Requirement
- Python 3.4.4+
- protobuf 3.2.0+
- Chainer 3.0.0b1+
- NumPy 1.12.0+
## 1. Download the original weights
Please download the weights below from the author's repository:
- pspnet50\_ADE20K.caffemodel: [GoogleDrive](https://drive.google.com/open?id=0BzaU285cX7TCN1R3QnUwQ0hoMTA)
- pspnet101\_VOC2012.caffemodel: [GoogleDrive](https://drive.google.com/open?id=0BzaU285cX7TCNVhETE5vVUdMYk0)
- pspnet101\_cityscapes.caffemodel: [GoogleDrive](https://drive.google.com/open?id=0BzaU285cX7TCT1M3TmNfNjlUeEU)
**and then put them into `weights` directory.**
## 2. Convert weights
```
$ python convert.py
```
---
# Reference
- The original implementation by authors is: [hszhao/PSPNet](https://github.com/hszhao/PSPNet)
- The original paper is:
- Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, Jiaya Jia, "Pyramid Scene Parsing Network", Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017