Awesome

Amulet net for salient object detection

A Pytorch implementation for Amulet(ICCV 2017).

Usage

• Train
  1. Put corresponding dataset in ./input/
     • training images(RGB, jpg format): ./input/train/raw/
     • training masks(gray, png format): ./input/train/mask/
     • validation images(RGB, jpg format): ./input/test/raw/
     • validation masks(gray, png format): ./input/test/mask/
  2. Run train.py, if you want to change some parameters, see train.py for detail.
• Inference
  1. Put inference data in ./inference/
     • inference images(RGB, jpg format): ./inference
  2. Run inference.py, output saliency maps will be in ./output directory.

Requirements

Original running environment:

• Python 3.7.5
• Pytorch 1.3.1
• TorchVision 0.2.1
• pillow 7.0.0

Detailed requirements are listed in requirements.txt.

(Currently bugs already known are fixed. If you found any bugs in this paper reproduction, you can open an issue, and I will fix it when I have time, thanks!)