Rapidata/coco-human-inpainted-objects

该数据集收集于https://www.rapidata.ai平台，包含数万个人工标注的70多种不同类型对象的注释。Rapidata使得在这个包含约2000张COCO数据集图像上的手绘线条的仓库中收集手动标签变得容易。用户会看到一张图像，并被要求使用画笔工具绘制一个类的对象 - 图像上总是有这样一个对象，因此任务不会模糊。这种用户交互的结果是用户在特定图像上绘制的线条集合。数据集的挑战在于汇总每张图像上的线条，以了解目标对象的位置。对于每张图像，我们提供了数百个由不同人绘制的2D线条，这些线条可以用来在每张图像上的目标对象上创建边界框和分割图。除了线条，数据集还包含COCO 2D边界框的地面真实值以及基线预测以供超越。

The dataset was collected on the https://www.rapidata.ai platform and contains tens of thousands of human annotations of 70+ different kinds of objects. Rapidata makes it easy to collect manual labels in several data modalities with this repository containing freehand drawings on ~2000 images from the COCO dataset. Users are shown an image and are asked to paint a class of objects with a brush tool - there is always a single such object on the image, so the task is not ambiguous. The result of this user-interaction is a collection of lines drawn by the user on that particular image. The challenge of the dataset is to aggregate the lines on each image to get an idea of where the target object is. For each image, we provide hundreds of 2D lines drawn by different humans that can be used to create bounding boxes and segmentation maps on each image of the target object. Apart from the lines, the dataset contains the COCO 2D bounding box ground truths as well as baseline predictions to beat.