October 29, 2019

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MenghaoGuo/AutoDeeplab

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

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