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, -- You are receiving this mail because: You are watching all bug changes.