{"componentChunkName":"component---src-templates-blog-post-js","path":"/blog/top-open-source-datasets-for-object-detection-in-2021/","result":{"data":{"site":{"siteMetadata":{"title":"No Frills News"}},"contentfulNfnPost":{"postTitle":"Top Open-Source Datasets For Object Detection In 2021","slug":"top-open-source-datasets-for-object-detection-in-2021","createdLocal":"2021-05-14 14:32:32.803612","publishDate":"2021-05-14 05:30:00+00:00","feedName":"Image Recognition","sourceUrl":{"sourceUrl":"https://analyticsindiamag.com/top-open-source-datasets-for-object-detection-in-2021/"},"postSummary":{"childMarkdownRemark":{"html":"<p>Here, we have listed the top open-source datasets one can use for object detection projects.\nThe dataset has several features, such as object segmentation, recognition in context, superpixel stuff segmentation, 1.5 million object instances, 80 object categories and more.\n6| Open ImagesOpen Images is a dataset of around 9 million images annotated with image-level labels, object bounding boxes, object segmentation masks, visual relationships, and localised narratives.\nThe dataset contains 16 million bounding boxes for 600 object classes on 1.9 million images, making it the largest existing dataset with object location annotations.\nThe tasks on this dataset include multi-object segmentation tracking, image tagging, road object detection, semantic segmentation, lane detection, drivable area segmentation, instance segmentation, multi-object detection tracking, domain adaptation, and imitation learning.</p>"}}}},"pageContext":{"slug":"top-open-source-datasets-for-object-detection-in-2021"}}}