Best Visual Search Software for Linux of 2025

The VGG Image Search Engine (VISE) is an open-source software solution that enables visual searching through extensive image collections by utilizing image regions as queries. This software is crafted and sustained by the Visual Geometry Group (VGG) within the Department of Engineering Science at Oxford University. It is published under a license that permits limitless use in both academic research and commercial industries. To foster a dynamic open-source community around VISE, we actively invite contributions and participation in its ongoing development. Users can engage with the project by reporting bugs, enhancing documentation, introducing new functionalities, or refining existing ones through merge requests. The Visual Geometry Group commits to the continued development, maintenance, and support of VISE until at least November 2025. Furthermore, users are encouraged to share their questions or report any challenges they encounter with the VISE software via our GitLab issues portal, thereby helping us create a more robust platform.

We make it easy for you to add superhuman computer vision into your applications, devices, and processes to give yourself an unassailable competitive edge.

Voxel51 is the driving force behind FiftyOne, an open-source toolkit designed to enhance computer vision workflows by elevating dataset quality and providing valuable insights into model performance. With FiftyOne, you can explore, search through, and segment your datasets to quickly locate samples and labels that fit your specific needs. The toolkit offers seamless integration with popular public datasets such as COCO, Open Images, and ActivityNet, while also allowing you to create custom datasets from the ground up. Recognizing that data quality is a crucial factor affecting model performance, FiftyOne empowers users to pinpoint, visualize, and remedy the failure modes of their models. Manual identification of annotation errors can be labor-intensive and inefficient, but FiftyOne streamlines this process by automatically detecting and correcting label inaccuracies, enabling the curation of datasets with superior quality. In addition, traditional performance metrics and manual debugging methods are often insufficient for scaling, which is where the FiftyOne Brain comes into play, facilitating the identification of edge cases, the mining of new training samples, and offering a host of other advanced features to enhance your workflow. Overall, FiftyOne significantly optimizes the way you manage and improve your computer vision projects.