just curiosity: AI image analysis ?

[support at hausoos.com]

Dear Mike,

If there is any need for help, just drop a line. Not a great coder  
(apart R), but can help.

Kind Regards

Corrado

Quoting Michael Miller <michael_miller at msn.com>:

> Hi everyone,
> I’m Mike, the digiKam developer responsible for the AI in digiKam.
>
> I really like the idea of a pluggable architecture to consume online  
> services for object identification and image classification.  On the  
> digiKam team, we take privacy very seriously which is why we haven’t  
> incorporated many external cloud services into digiKam (Google Maps  
> and online translation being the exceptions).  We believe your data  
> and images are yours, and we don’t want to do anything that could  
> cause a user to unknowingly share their data and images.
>
> Having said, that I think there are ways we could safeguard user  
> data and still allow a mechanism to consume cloud services.  The  
> AI/Machine Learning pipelines in digiKam are easily extended, and we  
> could add a generic pipeline that calls a user configurable command  
> in a shell.  As long as the command returns a value or values back  
> to digiKam in an agreed upon format, the end user could create their  
> own scripts to call cloud services.
>
> Since the user would have to create or install the scripts  
> themselves, I think it fair to assume the user knows the data is  
> being shared with a cloud service.
>
> I’ll talk with Gilles and Maik and get their opinion.  I’m just one  
> person on a talented team of developers, and I’d like to get their  
> thoughts.
>
> Cheers,
> Mike
>
>> On Mar 31, 2025, at 4:29 PM, Jens Benecke  
>> <jens-digikam at spamfreemail.de> wrote:
>>
>> Hello,
>>
>> I think this goes in the direction of something I proposed a few years ago.
>>
>> Situation:
>>
>> - There are a lot of online services offering specialized AI based  
>> $WHATEVER. Tagging, background removal, you name it.
>> - Most of these have an API where you can call some HTTP endpoint  
>> and either upload a (possibly reduced) version of your image, or a  
>> part of it.
>> - They then - usually - return an image or a set of text based  
>> data, like tags or free text.
>>
>> Digikam needs a system that can use these APIs in a flexible way,  
>> e.g. by incorporating scripts directly integrated into the app.  
>> There is a scripting interface but it cannot feed data back into  
>> Digikam or replace images.
>>
>> https://bugs.kde.org/show_bug.cgi?id=384444
>>
>> At the time, this idea was rejected for privacy reasons.
>> But IMHO, if you want to do specialized tagging using an online  
>> service, and remain API agnostic within Digikam, this is not  
>> necessarily a problem.
>>
>> Maybe reconsider?
>>
>> Regards,
>> Jens
>>
>>
>> Am 31.03.25 um 21:49 schrieb support at hausoos.com:
>>> Yes, of course! But if we had a way to integrate specialised image  
>>> recognition, running locally or through an API on connection, it  
>>> would be interesting for some people (of course, niche groups, but  
>>> still ....).For example, Plantnet has an API which can connect to  
>>> the AI recognition engine. Plantnet can reach > 85% accuracy with  
>>> good set of pictures for example (that varies across taxa, and  
>>> across geographies).
>>>
>>> There are quite a few other models, such as Flora Incognita, which  
>>> are very good for the plants in their database and have versions  
>>> of te models weighted that can be downloaded and run locally.
>>>
>>> That said, it would be very interesting to see whether it is  
>>> possible to at least identify down to the genus level, even if not  
>>> the species.
>>>
>>> The same could be done for other categories (trains, for example,  
>>> for those who are passionate about them, cars, buildings, fossils,  
>>> etc. .... :-) ....)
>>>
>>> Kind Regards
>>>
>>> Corrado
>>>
>>> Quoting Remco Viëtor <remco.vietor at wanadoo.fr>:
>>>
>>>> On dimanche 30 mars 2025 15:45:00 heure d’été d’Europe centrale Bill Allen
>>>> wrote:
>>>>> I did a couple of tests using the python API in which I fed my ex if
>>>>> metadata as part of the prompt which helped, but it's not going to work
>>>>> like, say, plant net for identification of plants.
>>>>
>>>> There are two big differences between systems like plantnet and digikam:
>>>> - in Digikam, the whole model is *local*, systems like plantnet  
>>>> can have many
>>>> more resources available;
>>>> - Plantnet is a *specialised* system, Digikam would need a general system
>>>>
>>>> Note that Plantnet, while good, can give wrong results. Other  
>>>> such systems can
>>>> do a lot worse (some specialised systems barely reach 50%  
>>>> success, and those
>>>> are the good ones *for their domain*).
>>>>
>>>> Remco
>>>
>>>
>>>
>> --
>> Regards, Jens
>>
>>