Poor recognition is typically a camera or model issue with the latter usually being the problem.
With all of the plate data captured and sent anonymously I was hoping for an improved license plate model.
I've gotten lots of images for the plate
detection model, which just identifies that there is a license plate in the frame, but because of the status with CPAI and the slow updates, almost no images for the actual OCR. Mike added the necessary data for the character recognition a while ago, but it took quite a while to be available for update through the codeproject UI. Furthermore, lots of users never really look at the CPAI web ui unless they're tinkering, so the lag on update distribution is heavy.
That being said, the images from the plate detection model are still quite valuable and absolutely could be used to make a significant improvement in the OCR. In order to do this, every single image would have to be annotated with the correct characters and a bounding box/pixel coordinates within the image where the actual numbers and letters are. The images then need to be cropped in to just the characters in the plate using those coordinates in order to train the OCR model. If anyone has suggestions for how to tackle that or wants to take on that task, I'm all ears. I can deal with training it if we can somehow acomplish that.
So
@algertc, what's in the next update? Are you working on the AI integration? Or auto correction of plates? I'd also like to put in a reminder request for a method of creating rules for notifications, etc.
When you correct a plate and enable "Correct all occurrences of this plate number", does it correct the future errors that are occuring?
Seems like I am making the same corrections over and over again, which would presume that future errors are not being corrected.
If this is the case, I would really like to have this as an option for future releases, understanding that it is possible there could be a real plate that has this corrected version and would be classified incorrectly in the database.
The "forward to correct plate" functionality is one of the most requested features. I understand the frustration with the detections because I experience the same thing, but it just feels wrong to me to add a workaround solution like this instead of addressing the problem where it's coming from. I'm not entirely opposed, but it would be a band-aid solution. It would be much better if we could deal with it either by improving the model or in a more flexible way.
I had been thinking about the notification rules/conditions and how to make them more granular and precise. I think i have a good approach and will focus on that as top priority.
Finishing off the requested MQTT improvements will come with that. Apologies for the absence. I haven't had any time to attend to this in a while. Still quite busy, but I'm going to try to make some improvements.
I think the most valuable improvement, by far, would be improving the computer vision. I'd pay a foreign freelancer to annotate them if someone can advise on how exactly that needs to be done and what instructions they would need to be provided.
Lastly, I've had to deal with some mobile development recently, and have found that the framework used to convert NextJS apps to mobile has improved massively since I last used it. Since I already dealt with all the requirements for PWA compatibility, it's actually fairly simple to package a proper app store app without much refactoring. I likely will do this because it would allow for push notifications and better integration for users who do not use HomeAssisant (I don't). Can do much better rich notifications, especially with the complex notification rules future functionality. A definite nice to have.
Lastly lastly, I've always been kind of annoyed that I can't watch my cameras on my TVs without using a clunky browser app on the smart TV. I use Apple TV, and I've always wished that there was a tvOS app for Blue Iris. I'm going to try to make this since I personally want it. If anyone else has Apple TVs, a BI app might be available on the store sometime soon.