MenghaoGuo/AutoDeeplab
Pytorch Implementation the paper Auto-DeepLab Hierarchical Neural Architecture Search for Semantic Image Segmentation
| repo name | MenghaoGuo/AutoDeeplab |
| repo link | https://github.com/MenghaoGuo/AutoDeeplab |
| homepage | https://arxiv.org/abs/1901.02985 |
| language | Python |
| size (curr.) | 75 kB |
| stars (curr.) | 334 |
| created | 2019-04-11 |
| license | |
AutoDeeplab
This is an implementation of Auto-DeepLab using Pytorch.
Environment
The implementation needs the following dependencies:
-
Python = 3.7
-
Pytorch = 0.4
-
TensorboardX
Other basic dependencies like matplotlib, tqdm … are also needed.
Installation
First, clone the repository
git clone https://github.com/MenghaoGuo/AutoDeeplab.git
Then
cd AutoDeeplab
Train
The dataloader module is built on this repo
If you want to train this model on different datasets, you need to edit –dataset parameter and then:
bash train_voc.sh
Reference
[1] : Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation
[2] : pytorch-deeplab-xception
