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

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`Traceback (most recent call last): File "/opt/LPRNet_Pytorch/train_LPRNet.py", line 286, in train() File "/opt/LPRNet_Pytorch/train_LPRNet.py", line 208, in train Greedy_Decode_Eval(lprnet, test_dataset, args) File "/opt/LPRNet_Pytorch/train_LPRNet.py", line 237, in Greedy_Decode_Eval targets = np.array([el.numpy() for...

我往lprnet网络结构的顶端添加了一个stn,那个空间变换网络,但是似乎这个新结构训练难度很大,loss不下降。有人知道怎么做吗? i added a STN network(the spacial transforming network) to the top of LPRNet, but i find training this new structure quite difficult and the loss doesnt go down. anybody...

@sirius-ai Thank you very much for implementing **LPRNet**. During the training process, adding **residual connection** to SmallBasicBlock using ResNet can further improve performance (**LPRNet ->LPRNetPlus**); Meanwhile, adding the **STNet** module...

12 types of license plate recognition, implemented by C++ TneosrRT, with an accuracy rate of up to 99.5%!!!