When it comes to tweaking and managing photos, few applications can rival digiKam. This everything-but-the-kitchen-sink software is designed to handle virtually every photographic task, from transferring and processing photos to organizing and sharing them. digiKam developers churn out new versions of the application at an impressive rate, and each new release brings a slew of bug fixes, improvements, and new features. The latest version 2.0 is no exception. Despite the modest point-one increase in version number, digiKam 2.0 brings several significant new features and a vast array of tweaks and fixes.
Let’s start with the seemingly minor additions called Colour Labels and Picks. As you might have guessed, the Color Labels feature allows you to mark photos in albums using colour labels. Better yet, each colour label has its own default keyboard shortcut, which speeds up the marking process. Colour Labels can come in handy in several situations. For example, you can use colour codes to triage incoming photos, marking them by relevance. You can also use colour labels to specify the privacy level for each photo, with the read labels assigned to private shots, yellow for snaps that can be shared with family and friends, and green for public photos. If you submit your photos to agencies or stock sites, the Picks feature can help you to keep tabs on the status of each submitted photo. In other words, while the Colour Labels and Picks features don’t add any revolutionary functionality, they can prove to be indispensable tools for improving the photographic workflow.
Geolocation is not a new feature, but in digiKam 2.0 it has been thoroughly reworked to make the process of geotagging photos more efficient. You can now add geographical coordinates to the photos by dragging them from the list onto the desired spot on the map. Alternatively, you can assign the geographical coordinates of a specific search result to the photos. The Search feature lets you specify a full or partial address and then returns a list of matching results, where each result is marked in the map. You can then select photos in the list, right-click on the desired search result, and pick the “Move selected images to this position item” from the context menu to geotag them. The Geolocation interface offers another nifty feature called Reverse Geocoding. This tool can retrieve human-readable locations such as city, street, country, etc. for photos based on their geographical coordinates. The obtained location names can be stored in photos as new tags, so you can easily search for photos taken in a specific country, city, or even street. In other words, using the reverse geocoding operation on your photos, you can tag them by their locations, like Germany (country), Berlin (city), Unter den Eichen (street), and so on. So next time you want to quickly pull all photos taken in a specific country or city, you can do so by using the appropriate tag or tags as filters. Speaking of filters, digiKam’s filtering features are now consolidated in the Filters right sidebar, and you can now filter photos not only by their tags and ratings, but also by colour labels and picks.
Face recognition has been one of the most requested digiKam features, and the latest version of the photo management application provides this functionality. The face recognition functionality can be used to find photos containing faces and attach face tags to persons in photos. This lets you quickly locate all photos of a specific person using digiKam’s filtering capabilities. Tagging faces in digiKam is a rather straightforward procedure: you can use the dedicated buttons in the preview window to mark a face in the currently viewed photo and tag it with the person’s name. Tagging faces manually can be a daunting proposition, especially if you have a considerable number of photos of people. Fortunately, digiKam can do the donkey job of automatically identifying faces for you. Press the “Scan collection for faces” button in the People left sidebar, and you can use the Scanning faces interface to configure and run automatic face recognition. This functionality is hit and miss, though, and the final result requires manual clean up. Still, it’s an important feature to have, and, hopefully, it will improve with time.