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