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Using Yolov5 + CRNN, half-finshed

dataset

  • orginal data:label.csv ./data
  • data for yolo: ./datayolo ./yolodata
  • data for CRNN: ./dataCRNN ./CRNN/lmdb*-->data turned into lmdb
    • using ./utils to generate the dataset for the two

train

according to official github

weight trained

  • yolo:./weights/yolov5_best.pth
  • CRNN:./CRNN/expr2/best.pth

intergrated demo.py for implement

./demo.py

  • input path: ./data1/
  • ouput csv: ./result.csv

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