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Pytorch Implementation For LPRNet, A High Performance And Lightweight License Plate Recognition Framework.

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除了94x24大小的所有图片都会报这个错,出什么问题了? > Traceback (most recent call last):  File "test_LPRNet.py", line 176, in    test()  File "test_LPRNet.py", line 74, in test    Greedy_Decode_Eval(lprnet, test_dataset, args)  File "test_LPRNet.py", line 105, in Greedy_Decode_Eval    prebs =...

Hi thank you for your great work . Can I use synthetic data for training and predict on real images ?

图片尺寸需要改成,256 * 32 共有37种字符,英文+数字+额外一种符号 字符在10~20个,lpr_max_len = 20 想知道该怎么该这个网络才能用

Hi, when i training model with custom data set, the accuracy is always 0. I modified the list of CHARS and license plate length, what could be the problem? ![image](https://user-images.githubusercontent.com/72374407/186277358-f36b737a-51ad-445a-97e9-05e403337ae3.png)

test_accuracy是0.0是啥情况?

Is there any reference to someone's knowledge which explains how to compute the accuracy of the LPRNet model output? I'm not interested into computing WER or CER, but an overall...