GSoc/2023/StatusReports/QuocHungTran: Difference between revisions
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The goal of this project is to develop a deep learning model that can recognize various categories of objects, scenes, and events in digital photos, and generate corresponding keywords that can be stored in Digikam's database and assigned to each photo automatically. The model should be able to recognize objects such as animals, plants, and vehicles, scenes such as beaches, mountains, and cities,... The model should also be able to handle photos taken in various lighting conditions and from different angles. | The goal of this project is to develop a deep learning model that can recognize various categories of objects, scenes, and events in digital photos, and generate corresponding keywords that can be stored in Digikam's database and assigned to each photo automatically. The model should be able to recognize objects such as animals, plants, and vehicles, scenes such as beaches, mountains, and cities,... The model should also be able to handle photos taken in various lighting conditions and from different angles. | ||
'''Mentors''' : Gilles Caulier, Maik Qualmann, Thanh Trung Dinh | '''Mentors''' : Gilles Caulier, Maik Qualmann, Thanh Trung Dinh | ||
==== Project Proposal ==== | ==== Project Proposal ==== | ||
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==== GitLab development branch ==== | ==== GitLab development branch ==== | ||
[https://invent.kde.org/graphics/digikam/-/tree/gsoc23-autotags-assignment?ref_type=heads gsoc23-autotags-assignment] | [https://invent.kde.org/graphics/digikam/-/tree/gsoc23-autotags-assignment?ref_type=heads gsoc23-autotags-assignment] | ||
== '''Contacts''' == | |||
'''Email''': [email protected] | |||
'''Github''': [https://github.com/quochungtran quochungtran] | |||
'''Invent KDE''': [https://invent.kde.org/quochungtran quochungtran] | |||
'''LinkedIn''': https://www.linkedin.com/in/tran-quoc-hung-6362821b3/ | |||
<br> | |||
== '''Project goals''' == | |||
== '''Links to Blogs and other writing''' == | |||
=== Main merge request === | |||
=== KDE repository for object detection and face recognition researching === | |||
=== Issue tracker === | |||
=== My blog for GSoC === | |||
My entire blog : | |||
* https://quochungtran.github.io/ | |||
===== (Week 1 - 2) ===== | |||
===== (Week 3 - 4) ===== | |||
===== (Week 5 - 6) ===== | |||
===== (Week 7 - 8) ===== | |||
===== (Week 9 - 10) ===== | |||
===== (Week 11 - 12) ===== | |||
Revision as of 06:18, 17 May 2023
Add Automatic Tags Assignment Tools and Improve Face Recognition Engine for digiKam
digiKam is an advanced open-source digital photo management application that runs on Linux, Windows, and macOS. The application provides a comprehensive set of tools for importing, managing, editing, and sharing photos and raw files.
The goal of this project is to develop a deep learning model that can recognize various categories of objects, scenes, and events in digital photos, and generate corresponding keywords that can be stored in Digikam's database and assigned to each photo automatically. The model should be able to recognize objects such as animals, plants, and vehicles, scenes such as beaches, mountains, and cities,... The model should also be able to handle photos taken in various lighting conditions and from different angles.
Mentors : Gilles Caulier, Maik Qualmann, Thanh Trung Dinh
Project Proposal
Automatic Tags Assignment Tools and Improve Face Recognition Engine for digiKam Proposal
GitLab development branch
Contacts
Email: [email protected]
Github: quochungtran
Invent KDE: quochungtran
LinkedIn: https://www.linkedin.com/in/tran-quoc-hung-6362821b3/
Project goals
Links to Blogs and other writing
Main merge request
KDE repository for object detection and face recognition researching
Issue tracker
My blog for GSoC
My entire blog :