I am working on a number plate detection system based upon the blog post at Creating a Real-Time License Plate Detection and Recognition App | NVIDIA Technical Blog and the code at GitHub - NVIDIA-AI-IOT/deepstream_lpr_app: Sample app code for LPR deployment on DeepStream
Ideally, I would like to be able to log individual cars, but I have found that lprnet often fails to read the plate correctly; I have been sing dashcam footage from California but it is sometimes giving a 99% confidence report in a plate value that is wrong.
My thinking is that if I can track an individual plate, I can record all values associated with said plate and determine which string is most likely to be correct. However, I am not sure how (or indeed whether) this can be achieved with lprnet.
The NvDsObjectMeta structure associated with each plate has the parent set to NULL, so I am unable to use the parent to identify the plate. The label_id and result_class_id of the NvDsLabelInfo are consistently 0 and 1 respectively.
The parser doesn’t seem to receive any unique information about the plate.
Is there a way to achieve what I want with lprnet?