Face recognition AI / DL and adding features

[cerp at eeos.biz]

Dear Gilles,

Thanks a lot. Some comments in the text.

Quoting Gilles Caulier <caulier.gilles at gmail.com>:

> Le lun. 17 août 2020 à 13:34, <cerp at eeos.biz> a écrit :
>>
>> Dear Gilles,
>>
>> Thanks for the link. I looked at the bugzilla thread, and it is very useful.
>>
>> In my case, I think we may need to start developing a DL classifier
>> earlier, I cannot wait for Digikam to have stabilised the face search,
>> so I may have to go a different way if I am not allowed to create a
>> Digikam plugin for plants classification. We have several 10s of
>> thousands of pictures, with many TB of pictures, and manual screening
>> is now impossible. I am happy to share my results of course.
>
> About plants we have this entry to create a new plugin :
> https://bugs.kde.org/show_bug.cgi?id=394544

Thank you! This is exceptionally useful.

>
>
>>
>> Thanks for the link to Photils, which seems to be useful for us. I am
>> not completely clear: is photils the engine that is currently used in
>> Digikam for face recognition with the new AI / DL approach, or is this
>> in the future?

I looked at Photils and tried it. I think it may be useful but not  
really optimal for our use. We need something that we can train at  
different levels of detail (initially plant /  not plan, then family,  
species, subspecies etc. etc.) , possibly based on Deep Learning.

>
> No. digiKam as a dedicated internal engine to process detection and
> recognition based on AI.

What technology does Digicam use? I assume Digikam is using DL, but  
what starting from which libraries? I assume you did not develop  
everything from the ground up, because there are so many interesting  
libraries available.

>
> Photils is an alternative which compute a fingerprint of images, send
> it to a AI engine which try to identify objects, monuments, animals,
> etc... It return a list of keywords.

I understood the mechanism, and trialled it, and it turns out to be  
too generic for our use. I would prefer something we can train, and  
that can be used at different level of details (initially plant /  not  
plant, then family, species, subspecies etc. etc.).


Thanks a lot.

>
> Gilles Caulier