Open Images Dataset
Open Images Dataset Open Images Dataset is a key Computer Vision resource, offering millions of precisely annotated images for a variety of tasks such as detection, segmentation, and context analysis. Its wealth of annotations and categories makes it an essential tool for training powerful visual models.
Over 9 million images in JPEG format, detailed annotations in CSV
Free for academic and commercial use under a specific license (see conditions)
Description
Open Images Dataset brings together over 9 million images with accurate annotations including bounding boxes, image segments, relationships between objects, and detailed contextual descriptions. These rich annotations make it easy to train complex models that can understand not only individual objects but also the interactions and the overall context of visual scenes.
The CSV annotation format facilitates its integration with standard Computer Vision tools and allows flexible and efficient use when training models.
The dataset includes:
- Over 9 million images in JPEG format
- Detailed annotations in CSV format
- Over 16 million labels across thousands of object classes
- Complex annotations including inter-object relationships and contextual descriptions
What is this dataset for?
Open Images Dataset is widely used for:
- Training advanced object detection and segmentation models
- Analysis and in-depth understanding of relationships between objects present in images
- The improvement of advanced visual search and image recognition systems
- The construction of robust and versatile models thanks to its diversity and richness of data
Can it be enriched or improved?
Yes, despite its great wealth, Open Images Dataset can be further enriched:
- Increase geographic and cultural coverage to reduce bias
- Extending contextual annotations to refine the understanding of the overall context of scenes
- Introduction of new categories or sub-categories specific to industrial or professional applications
- Combination with specialized data sets to improve performance in specific areas such as medicine, industry or the environment
🔗 Source: Open Images Dataset
Frequently Asked Questions
How does Open Images differ from a dataset like COCO or ImageNet?
Open Images stands out for the diversity of its annotations: it does not only offer encompassing boxes, but also relationships between objects, hierarchical annotations, and image segments. It covers more classes than ImageNet and COCO combined, making it a versatile resource for a variety of vision tasks.
Can I only extract images with segmentation or object relationship annotations?
Yes, the official dataset site allows you to filter subsets by type of annotation. You can thus download only images containing segments (segmentation masks), “visual relationships” annotations, or both.
What are the limitations to consider when using Open Images?
The complexity and quantity of annotations may require significant pre-processing. In addition, the granularity of labels may vary between classes, which requires consistency checks for sensitive or very specific projects.
