cocostuff164k.yaml voc12.yaml data datasets ade20k labels.txt cityscapes labels.txt cocostuff labels.txt labels_2.txt models/deeplab_resnet101/cocostuff164k .gitkeep eval.py libs/datasets __init__.py cocostuff.py scripts setup_caffemodels.sh setup_cocostuff10k....
Welcome to official homepage of the COCO-Stuff [1] dataset. COCO-Stuff augments all 164K images of the popular COCO [2] dataset with pixel-level stuff annotations. These annotations can be used for scene understanding tasks like semantic segmentation, object detection and image captioning. Overv...
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 也可用一下方法下载数据集并设置正确的文件结构。 #Getthis repo git clone https://github.com/nightrome/cocostuff.git cd cocostuff #Downloadeverything wget--director...
COCO-Stuff: Thing and Stuff Classes in Context Holger Caesar1 Jasper Uijlings2 Vittorio Ferrari1 2 University of Edinburgh1 Google AI Perception2 Abstract Semantic classes can be either things (objects with a well-defined shape, e.g. car, person) or stuff (amorphous background regions, e.g....
To understand stuff and things in context we introduce COCO-Stuff, which augments all 164K images of the COCO 2017 dataset with pixel-wise annotations for 91 stuff classes. We introduce an efficient stuff annotation protocol based on superpixels, which leverages the original thing annotations. We ...
为了了解上下文中的事物,我们引入了COCO-Stuff1,它为91个事物类添加了逐像素注释,从而增加了COCO 2017数据集的所有164K图像。我们介绍了一种基于超像素的有效东西注释协议,该协议利用了原始东西注释。我们量化了协议速度与质量之间的权衡,并探讨了注释时间与边界复杂度之间的关系。此外,我们使用COCO-Stuff进行以下分析...
内容提示: COCO-Stuff: Thing and Stuff Classes in ContextHolger Caesar 1 Jasper Uijlings 2 Vittorio Ferrari 12University of Edinburgh 1 Google AI Perception 2AbstractSemantic classes can be either things (objects with awell-def i ned shape, e.g. car, person) or stuff (amorphousbackground ...
stuff image segmentation – per-pixel segmentation masks with 91 stuff categories, such as grass, wall, sky (see MS COCO Stuff), panoptic: full scene segmentation, with 80 thing categories (such as person, bicycle, elephant) and a subset of 91 stuff categories (grass, sky, road), ...
The MS COCO (Microsoft Common Objects in Context) dataset is a large-scale object detection, segmentation, key-point detection, and captioning dataset. The dataset consists of 328K images. Splits: The first version of MS COCO dataset was released in 201
categories是一个列表(80个元素对应80类检测目标)列表中每个元素都是一个dict对应一个类别的目标信息。包括类别id、类别名称和所属超类(一些类别的统称)。类别id也是stuff91下的类别索引,所以只下载object 80时会发现有些索引没有,训练时需要将索引映射到1-80。