https://bugs.kde.org/show_bug.cgi?id=497491
Bug ID: 497491
Summary: Feature Request: Option to Rebuild Face Recognition
Model from User-Tagged Data
Classification: Applications
Product: digikam
Version: 8.5.0
Platform: Other
OS: Other
Status: REPORTED
Severity: wishlist
Priority: NOR
Component: Faces-Workflow
Assignee: digikam-bugs-n...@kde.org
Reporter: t...@basien.de
Target Milestone: ---
Dear Digikam Development Team,
I would like to suggest a feature that could significantly improve the
usability and accuracy of the face recognition functionality in Digikam.
Currently, the face recognition model often misidentifies non-face regions as
faces, requiring a lot of manual corrections. This issue persists even with the
latest version (8.5.0), which I am using on Linux.
To address this, I propose adding an option to rebuild the face recognition
model from scratch, using user-provided training data. For example, I have over
10,000 images with properly tagged face regions and associated person tags. It
would be ideal if I could:
1. Delete the existing face recognition model.
2. Re-train a new model based entirely on my tagged dataset.
This feature would greatly enhance the flexibility of Digikam's face
recognition, particularly for users with large collections of accurately tagged
data. It could also help to refine the accuracy of the model over time as new
data is added.
Thank you for considering this suggestion. I hope it aligns with the ongoing
development goals of Digikam.
Best regards,
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