GSoC/2020/StatusReports/KartikRamesh: Difference between revisions
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== Digikam : Face Management Workflow Improvements == | == Digikam : Face Management Workflow Improvements == | ||
DigiKam provides a great | DigiKam is a KDE Desktop Application for Photo Management. Apart from the standard functionality of being able to view photos, DigiKam provides the user with a lot of added features such as Image Tagging, Photo Editing, Image Metadata viewing/editing. At the heart of DigiKam's commendable functionality is the FaceEngine. DigiKam can detect faces in Photos, and recognize faces in new photos based on prior information. This allows for a great personalized experience for the user. | ||
A major breakthrough in the FaceEngine came last year when [[GSoC/2019/StatusReports/ThanhTrungDinh|Thanh Trung Dinh]] implemented OpenCV's DNN module to bring great improvements to performance. [[GSoC/2019/StatusReports/IgorAntropov|Igor Antropov]] implemented many changes to the workflow Interface, to make the overall experience much comfortable for the user. | |||
This project is in essence an extension to the work that Igor did last summer. As such, this project does not intend to implement one Major feature.Instead, it aims to rectify issues in the current workflow, as well as introduce new features in an effort to improve the user experience. | |||
'''Mentors''' : Maik Qualmann, Gilles Caulier, Trung Dinh | '''Mentors''' : Maik Qualmann, Gilles Caulier, Trung Dinh | ||
Revision as of 15:18, 9 June 2020
Digikam : Face Management Workflow Improvements
DigiKam is a KDE Desktop Application for Photo Management. Apart from the standard functionality of being able to view photos, DigiKam provides the user with a lot of added features such as Image Tagging, Photo Editing, Image Metadata viewing/editing. At the heart of DigiKam's commendable functionality is the FaceEngine. DigiKam can detect faces in Photos, and recognize faces in new photos based on prior information. This allows for a great personalized experience for the user.
A major breakthrough in the FaceEngine came last year when Thanh Trung Dinh implemented OpenCV's DNN module to bring great improvements to performance. Igor Antropov implemented many changes to the workflow Interface, to make the overall experience much comfortable for the user.
This project is in essence an extension to the work that Igor did last summer. As such, this project does not intend to implement one Major feature.Instead, it aims to rectify issues in the current workflow, as well as introduce new features in an effort to improve the user experience.
Mentors : Maik Qualmann, Gilles Caulier, Trung Dinh
Project Goals
This project aims to :
- Provide a Help Box to aid first time users of Facial Recognition.
- Provide notification about results of a Facial Recognition.
- Order People Sidebar, to show tags of Priority first.
- Order Face Item View, to display Unconfirmed Faces before Confirmed Faces.
- Provide new “Ignored” Category for Face Tags.
- Automatically Group Results in Unconfirmed Tag.
- Provide Functionality to reject Face Suggestions.
- Automatically add Icons to newly created face tags.