[digikam] [Bug 472031] New: Faces detection gets worse with lots of faces to train on

[iain]

https://bugs.kde.org/show_bug.cgi?id=472031

            Bug ID: 472031
           Summary: Faces detection gets worse with lots of faces to train
                    on
    Classification: Applications
           Product: digikam
           Version: 8.0.0
          Platform: macOS (DMG)
                OS: macOS
            Status: REPORTED
          Severity: normal
          Priority: NOR
         Component: Faces-Detection
          Assignee: digikam-bugs-null at kde.org
          Reporter: iain+kde at cardnell.co.uk
  Target Milestone: ---

I believe that using the "Clear and re-build all training data" for face
detection makes the detection worse with the more faces you have tagged.

Initially I manually tagged 4-5 faces of a few people and detected faces (I
have around 10000). The initial scan went well and I'd say it was 80% accurate.
As I tagged more people manually and rebuilt the training data the new
Recognise Faces runs got worse.
I now have 2000+ faces tagged over 50+ people and the accuracy is almost 0.

I believe that it now has too much training data and the faces are too
different across all the images to train a model properly. I'm not sure how
other engines cope with this problem. (e.g. I am now tagged over 1000 times in
my albums).

What might be a simple workaround is to allow a user to choose 4-5 good images
for each person and use those as the training set rather than trying to use
every example.

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