https://bugs.kde.org/show_bug.cgi?id=432537
Bug ID: 432537
Summary: Improve face-recognition accuracy by visually
de-selecting "bad faces" to be used within the
faces-engine
Product: digikam
Version: 7.2.0
Platform: Microsoft Windows
OS: Microsoft Windows
Status: REPORTED
Severity: wishlist
Priority: NOR
Component: Faces-Recognition
Assignee: digikam-bugs-n...@kde.org
Reporter: cell...@hotmail.com
Target Milestone: ---
SUMMARY
Tagging people within photos does not always means strictly tagging "faces",
furhtermore when it comes to faces, not always the face i would like to tag is
"good for recognition" (even thoug it has been detected by the face-detection
algorithm) and generally speaking the fact that the section within digikam for
people is named "people" means that the tagging action is an act of marking the
presence of someone within a photo and not only its face.
When dealing with this kind of tagging at the same time with face-recognition
process, the latter is "damaged" (garbage in - garbage out).
Searching within the digikam forums i found that face recognition happens by
using only the last 100 confirmed people tags to avoid slowing the face enigne.
It could be really helpful for the common user to know which are the "last 100"
tags, i mean visually speaking, and to be able to select/deselect which tags
are actually to be ignored within the face-engine (small checkbox in a corner
of the face thumbnail?).
With checkboxes also the possibility to "change the 100 limit" could be a bonus
(it could become a user choice based on its own hardware capabilities)
STEPS TO REPRODUCE
To be more specific i could do 2 examples:
1) I would like to manually tag someone even though if it is turned back with
respect to the camera.
2) I would like to manually tag someone even though the face is completely out
of focus, blurred, really dark etc (example old phones)
And then i launch a face recognition process.
As bonus consideration, similar problems arise when child and adult version of
same person exist within the images dataset.
OBSERVED RESULT
When doing as above, the result is that the "face-recognition" process will use
within its algorithm some "faces" that are "not faces" or such bad quality
faces that the final suggestions results become quite poor.
EXPECTED RESULT
Improve face-recognition accuracy.
SOFTWARE/OS VERSIONS
Windows:
macOS:
Linux/KDE Plasma:
(available in About System)
KDE Plasma Version:
KDE Frameworks Version:
Qt Version:
ADDITIONAL INFORMATION
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