MEUNet：Multi-scale Edge-based U-shape Network for Salient Object Detection

Code for paper "Multi-scale Edge-based U-shape Network for Salient Object Detection", by Han Sun, Yetong Bian , Ningzhong Liu, and Huiyu Zhou.

Requirements

• Python3.6
• Pytorch1.5
• torchvision
• numpy
• apex
• cv2

Usage

• Clone this repo into your workstation

git clone https://github.com/bellatong/MEUNet.git

training

1. Download the pre-trained model resnet50 ( password: 9yp3 )

2. Use edge.m to generate edge maps for the training set

3. Modify train.py to change both the dataset path and the file save path to your own real path

4. run train.py

   python3 train.py
   

test

1. Download our trained model MEUNet (password: 3zoZ) and put it into folder out

2. Modify the dataset path and file save path in the test.py and metric/main_function.m to your own real paths

3. run test.py, then the saliency maps will be generated under the corresponding path, and the evaluation scores for the model on the test dataset will be stored in result.txt

   python3 test.py
   

The result saliency maps

Here are saliency maps of our model on six different datasets (DUTS, ECSSD, DUT-OMRON, HKU-IS, PASCAL-S) The result saliency maps (passwd: 6e21)