其中包含190万张图片,共计600个类别,共标记了1540万个边界框。这是目前带有对象位置标注的最大数据集。这些边界框大部分是由专业的注释人员手工绘制的,以确保准确性和一致性。
Open Images is a dataset of ~9 million images that have been annotated with image-level labels and object bounding boxes. The training set of V4 contains 14.6M bounding boxes for 600 object classes on 1.74M images, making it the largest existing dataset with object location annotations. The boxes have been largely manually drawn by professional annotators to ensure accuracy and consistency. The images are very diverse and often contain complex scenes with several objects (8.4 per image on average). Moreover, the dataset is annotated with image-level labels spanning thousands of classes.
类别数量 | 600 |
图片数量 | 大约 900 万张 |
数据集官网 | https://storage.googleapis.com/openimages/web/index.html |
数据组织 |
训练集:9,011,219个图像 验证集:41,620个图像 测试集:125,436个图像 |
许可信息 |
数据标注由 google 根据 CC BY 4.0 https://creativecommons.org/licenses/by/4.0/ 进行许可。 图像则由 CC BY 2.0 进行许可。 |
引文 | Krasin I., Duerig T., Alldrin N., Ferrari V., Abu-El-Haija S., Kuznetsova A., Rom H., Uijlings J., Popov S., Kamali S., Malloci M., Pont-Tuset J., Veit A., Belongie S., Gomes V., Gupta A., Sun C., Chechik G., Cai D., Feng Z., Narayanan D., Murphy K. OpenImages: A public dataset for large-scale multi-label and multi-class image classification, 2017. Available from https://storage.googleapis.com/openimages/web/index.html. |