08/13/2023 at 21:49 •
So a couple things... but first
I've started on the auto-discovery-&-connect feature leveraging onvif. Because onvif on python is somewhat stale, I couldn't find any libraries that do exactly what I want. The closest thing is pyOnvif, so I forked it here in an effort to update and adapt it to my usecase.
Turns out my cameras aren't exactly compliant to the onvif schema standard, so they were completely invisible to the built-in discovery method of the library. A bit of cross-eyed examination revealed that my cameras have different xml leading characters from standard. Sooo I added some logic to handle such cases to my fork of the pyOnvif.
I'm currently on welfare, with required welfare activities. I'm trying to get some time off from those activities/work in order to do more work on this software.
In order to do that, I need to prove that there is an interest and a need for this software.
If you're a farmer, could you comment how a solution like what I'm trying to make here, would help you?
If a finished solution were to be sold as a product (either local, simple install or even easier Software-as-a-Service), what would you pay for it?
Can someone help me find funding?
06/16/2023 at 09:08 •
# So, this is the current state
## For users:
- Documentation is lacking.
- Ethical guidelines are lacking.
- You need to figure out yourself how to connect to your camera / video source.
- Alerts aren't implemented yet.
- The model is bog standard YOLO v8. ---> Predator recognition doesn't work yet.
- We need more relevant image datasets, to train the model.
## For developers:
- Documentation is lacking
- I'm trying to run Labelstudio locally, with auto-annotation. But having issues. Please help out if you know some way to do active learning or some other simple way of gradually improving recognition of ~20 object classes on a growing dataset.
- I don't want to make a mobile app, because it seems to be a fairly large and fragmented target. I'd rather make a webapp, and have people "install it" on their device of choice (by placing a shortcut on their desktop/homescreen). I don't know how to make a webapp either, so if anyone can help out with that, great.
- Planning to implement ONVIF video source recognition to ease setup. This I can do.
- Planning to eventually distribute on Pypi. I don't know how to package, but it seems at least somewhat straightforward.
- RE: following established coding guidelines... I am self taught, and coding guidelines with classes and separate subscripts for each major function is a little confusing for me. I'd still like the project to follow guidelines so that most capable people feel comfortable contributing and to ease maintenance. If you can help with that, please do.