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• Hardware (T4/V100/Xavier/Nano/etc) RTX3050
• Network Type (Detectnet_v2/Faster_rcnn/Yolo_v4/LPRnet/Mask_rcnn/Classification/etc) Classification, LPRnet
• TLT Version (Please run “tlt info --verbose” and share “docker_tag” here)
• Training spec file(If have, please share here)
• How to reproduce the issue ? (This is for errors. Please share the command line and the detailed log here.)
Hi, i have some questions to ask about replacing the LPRnet with Classification models. Just wanna ask can i train a classification model to detect license plate instead of using LPRnet.
Lets just say if i only want to detect 10 different license plate only, where each license plate have a different FOV in my training set, and each license plate contains 50 different images. In my label file, i will only put 10 labels for this license plate. For example, “ABC123”, “EFG567”, etc. Is it recommended and what are the drawbacks of using a classification model instead of a LPR model. Besides, what should i take note if i use a classification model to use as a license plate recognition model. Please advice.
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