Hi everybody !
I would like to know if some of you use this feature in Digikam.
After upgrading to 8.6.0, I did some tests on an Album containing few photos.
I found it quite slow and giving sometimes no or non relevant results.
Maybe it needs to be tweaked a bit or to learn by examples just like face recognition.
So, any experience or piece of advice are welcomed as it seems to be promising.
Regards.
Pierre
Hi @Pierre7602,
Yes, Autotagging can be slow. I recommend “Work on all processor cores” is enabled as this will speed things up considerably. Also, are you collections on a local drive, or some type of remote storage like NAS? Using NAS can also slow things down significantly.
As for models, I think YOLOv11 XLarge is the most accurate, but YOLOv11 Nano is by far the fastest. EfficientNet B7 is good for tagging the overall scene, and the YOLO models are good for finding objects in the image.
Yes, I use autotagging for all my images, but I’m also a bit biased. I wrote the autotagging feature. 
Cheers,
Mike
Extremely slow, English only and not very accurate either. I tested it but I’ll wait for a few more decades for it to become better…
I can confirm this although I didn’t test it recently.
Hi @Mike_Bing,
Yes. I agree. The models we use are the best available for local use. There are better ones, but they require sending the image to the could for processing. We take your privacy seriously, so we really try to not use any cloud services.
The only embedded cloud service we use is the tag translator. You can select to have the autotag translated when it is detected.
There is another option for non-english tags, but it’s quite technical. Any changes made this way will be overwritten when you install a new version of digiKam.
Cheers,
Mike
Hi Mike !
My collection is on a NAS. I’m always wondering myself if it would be better to have my collection on a local drive or on a NAS. The NAS is more silent and its capacity can be expanded. But that’s another subject.
I’m not sure to have checked “Work on all processor cores”.
Thank you for giving us more information about the models which are used.
Would you recommend using different models one after the other to get better results ? For example, EfficientNet B7 followed by YOLOv11 XLarge (or vice versa) ?
Cheers, Pierre.