介绍
COCO-Stuff数据集对COCO数据集中全部164K图片做了像素级的标注。
- 80 thing classes, 91 stuff classes and 1 class 'unlabeled'
下载
Filename | Description | Size |
---|---|---|
train2017.zip | COCO 2017 train images (118K images) | 18 GB |
val2017.zip | COCO 2017 val images (5K images) | 1 GB |
stuffthingmaps_trainval2017.zip | PNG格式的标注(将像素所属的类映射到灰度值)(0~181+255) | 659 MB |
stuff_trainval2017.zip | Stuff-only COCO-style annotations on COCO 2017 trainval | 543 MB |
annotations_trainval2017.zip | Thing-only COCO-style annotations on COCO 2017 trainval | 241 MB |
labels.md | 标签的说明 | <10 KB |
labels.txt | 同上 | <10 KB |
也可用一下方法下载数据集并设置正确的文件结构。
# Get this repo
git clone https://github.com/nightrome/cocostuff.git
cd cocostuff
# Download everything
wget --directory-prefix=downloads http://images.cocodataset.org/zips/train2017.zip
wget --directory-prefix=downloads http://images.cocodataset.org/zips/val2017.zip
wget --directory-prefix=downloads http://calvin.inf.ed.ac.uk/wp-content/uploads/data/cocostuffdataset/stuffthingmaps_trainval2017.zip
# Unpack everything
mkdir -p dataset/images
mkdir -p dataset/annotations
unzip downloads/train2017.zip -d dataset/images/
unzip downloads/val2017.zip -d dataset/images/
unzip downloads/stuffthingmaps_trainval2017.zip -d dataset/annotations/
语义分割模型
PyTorch模型
作者说这个好。
标注工具
用MATLAB标注,详情看这里.