- Network:
- global fusion
- global cross modality fusion
- ubuntu
- pytorch 1.7 (other versions may also work)
- numpy, opencv3, tqdm
- apex for efficient training
- prepare your training datasets:
- we followed A2dele and adopted their training dataset.
- Download Link; Fetch Code: 0fj8
- set your paths in
train_cross.py - run
train_cross.py
- prepare your test datasets. (Most of them are collected in RGBD-SOD survey)
- download the model from baiduyun,(fetch code: peng) and put in the root dir
- run
test_cross.py.
- put your images and depth images into
vis_feature.test_data. - set the
VisualizationDemo.pyto get your intersted feature maps. - enjoy!
- Baduyun Result Link; Fetch code: peng
- 百度网盘链接:https://pan.baidu.com/s/1edLCHGd9RA6YyJa8vuYAng . 提取码:peng
- Recommend SOD_Evaluation_Metrics
