GSoC/2020/StatusReports/NghiaDuong: Difference between revisions
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== Digikam : DNN based Faces Recognition Improvements == | |||
DigiKam is a famous open-source photo management software. With a huge effort, the developers of digiKam have implemented face detection and facial recognition features in a module called faces engine. This module implements different methods to scan faces and then label them based on the pre-tagged photos given by users. | |||
Since last year, as a result of [[GSoC/2019/StatusReports/ThanhTrungDinh|Thanh Trung Dinh's project during GSoC 2019]], digiKam's faces engine has adopted new CNN based face processing methods. These methods have been proven to give a better performance than other traditional image processing methods implemented in digiKam. However, there still are some limitations in the current implementation of the faces engine, therefore the main goals of this project to continue [[GSoC/2019/StatusReports/ThanhTrungDinh|Thanh Trung Dinh's works]] and improve the performance of digiKam's faces engine. | |||
'''Mentors''' : Gilles Caulier, Maik Qualmann, Thanh Trung Dinh | |||
Revision as of 07:39, 27 June 2020
Digikam : DNN based Faces Recognition Improvements
DigiKam is a famous open-source photo management software. With a huge effort, the developers of digiKam have implemented face detection and facial recognition features in a module called faces engine. This module implements different methods to scan faces and then label them based on the pre-tagged photos given by users.
Since last year, as a result of Thanh Trung Dinh's project during GSoC 2019, digiKam's faces engine has adopted new CNN based face processing methods. These methods have been proven to give a better performance than other traditional image processing methods implemented in digiKam. However, there still are some limitations in the current implementation of the faces engine, therefore the main goals of this project to continue Thanh Trung Dinh's works and improve the performance of digiKam's faces engine.
Mentors : Gilles Caulier, Maik Qualmann, Thanh Trung Dinh