Comments (2)
I used the code on Openvino as a reference. I haven't seen any differences.
from korean-license-plate-recognition.
Wow,find another version ! paper LPRNet: License Plate Recognition via Deep Neural Networks 's basic block network architectureis show as follow ,is similar to your's small_fire_block ,except padding parts. this repo show another version model trained by torch . these model use different method to cal ctc loss
from korean-license-plate-recognition.
Related Issues (9)
- ValueError: Output tensors to a Model must be the output of a TensorFlow `Layer` (thus holding past layer metadata). Found: Tensor("Softmax:0", shape=(?, 88, 46), dtype=float32) HOT 1
- labeling json format
- How can I get a graph of accuracy? HOT 2
- What labeling tool did you use? Or How can I change your code to be trained on pascalvoc format dataset? HOT 2
- Train with Variable Length Labels HOT 1
- Empty vector output resultant of training using given training data HOT 5
- 2 line license plate HOT 1
- pre trained model cannot download HOT 2
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from korean-license-plate-recognition.