12/15/2023 0 Comments Showfoto vs digikam![]() The approach to resolve the problem took a wrong turn and that is why the deep Technical proof of concept, but not usable in production. The result was mostly demonstrative and very experimental, with poor computation speed results. Who worked on the integration of Neural Networks into the Face Management pipeline based on the Dlib library. Also, according to user feedback fromīugzilla, Face Recognition does not provides a good experience when it comes to an auto-tag mechanism for people.ĭuring the summer of 2017 we mentored a student, Yingjie Liu, Of user feedback to confirm whether or not what it has detected is really a face. ![]() This works, but does not provide a high level of positive results.įace detection is able to give 80% of good results, while analysis is not too bad but requires a lot Used the classical feature-based Cascade Classifierįrom the OpenCV library. Until now, the complex methodologies that analyzed image contents to isolate and tag people’s faces It had the problem of not being powerful enough to facilitate the faces-management workflow automatically. ![]() That included this feature (digiKam 2.0.0). The algorithms used in the background (not based on deep learning) were old and had been unchanged since the first revision Deep-Learning Powered Faces Managementįor many years, digiKam has provided an important feature dedicated to detecting and recognizing faces in photos. This version is a result of a long development that started one year ago and in which we have introduced new features and plenty of fixes.Ĭheck out some of the highlights listed below and discover all the changes in detail. You can also visit the digiKam Home Page for news of new releases and other digiKam related information.Just in time to get you into the holiday spirit, we are now proud to release digiKam 7.0.0 final release today. See the digiKam Users Mailing List joining instructions for details. You can start off by asking questions to other digiKam users and hopefully soon you will be answering the support questions of others. If you become a regular user of digiKam you are encouraged to join the digiKam Users Mailing List. Support ¶ĭigiKam is a community supported project, which means that users and developers support one another. It is fully 16 bit enabled including all available tools, supports RAW format conversion through libraw, DNG export and ICC color management work flow. While digiKam remains easy to use, it provides professional level features by the dozens. To compare visually images side by side, one other tool named Light Table is provided to select the best shots taken from a series. The images post processing can be easily done by a set of tools though the Batch Queue Manager, or by many import and export tools dedicated to work with remote web services. You can use the Image Editor to view your photographs, comment and rate them, correct, enhance and alter them. Of course, any media or card reader supported by your operating system will interface with digiKam.ĭigiKam incorporates a fast Image Editor with many image editing tools. More than 1000 digital cameras are supported by the gPhoto library. ![]() Thus, digiKam is a formidable Digital Asset Management (DAM) software including powerful image editing functions.Īn easy-to-use camera interface is provided as Import Tool, that will connect to your digital camera and download photographs directly into digiKam Albums. It has many features for viewing, organizing, processing and sharing your images. digiKam enables you to manage large numbers of digital photographs in Albums and to organize these photographs for easy retrieval using tags (keywords), captions, collections, dates, geolocation and searches. It provides a simple interface which makes importing and organizing digital photographs a snap. DigiKam is an advanced digital photo management application for Linux, macOS and Windows desktop.
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