digiKam 8.3, an open-source, free, and cross-platform digital photo management application, is now available as a major release that incorporates new features and resolves a vast range of bugs and issues.
The key features of digiKam 8.3 consist of a new automatic image tagging tool utilizing a Deep Learning neural network engine, proficient in categorizing various objects, scenes, and events in digital photos, such as animals, plants, vehicles, beaches, cities, mountains, etc.
The latest release also integrates a tool that assigns metadata from an image or JSON file to your digital photos, a new settings page for modifying geolocation parameters, revamps the video preview and slideshow to align with Qt6::Multimedia and Qt5::QtAVPlayer (FFmpeg 5 and later supportive), and includes generic network proxy settings.
Moreover, the digiKam 8.3 release discards older and unmaintained QtAV framework code, updates the AppImage universal binary to coordinate with the Qt 5.15.12 LTS and KDE Frameworks 5.115 frameworks, and upgrades the LibRaw library (utilized by digiKam for reading raw files from digital cameras) to snapshot 2024-02-02.
Among other noteworthy changes, the new digiKam release adds support for the Imagga image recognition API and computer vision AI, improves support for the Olympus C-310 digital camera on SUSE Linux systems, and improves image detection from Sanyo VPC-G200 cameras.
Numerous bugs were addressed in this release to improve various functionalities of the application, such as file deletion, renaming or naming faces in the image preview, sharing and loading of maps from other mapping software, AF points in focus, support for XFC images created with GIMP 2.10.36, face tagging, and more.
Many other issues or crashes were fixed in digiKam 8.3 and you can study the changelog here for more details. Meanwhile, you can download digiKam 8.3 from here as an AppImage that you can run on virtually any GNU/Linux distribution without installing anything on your computer.
Last updated 10 hours ago