Automatic Number Plate Recognition

Group homework for the 7th semester class Image Processing at the Budapest University of Technology and Economics.

Dependencies

Install Python packages with pip:

pip install -r requirements.txt

Put images in the images folder.
./detect.sh
output_original.csv contains the results (in the root folder)
output.csv contains the results of each cutout
- good for debugging purposes, and matching these against the detections in images/cutouts/

Put images in the images folder.
Run YOLO object detection
- python yolov7-number-plates/detect.py --weights yolov7-number-plates/yolov7-number-plates-trained.pt --img-size 448 --source images --name number-plates-yolo --save-txt --save-conf --nosave --project images --exist-ok
Cut out detections
- move detected *.txt labels into folder images/labels
  - mv images/number-plates-yolo/labels images/labels
- python cutout.py images
- Results are now in the images/cutouts folder
Run OCR on detections
- python paddleOCR/main.py
output.csv contains the results (in the root folder)
Run python fix_csv.py to merge detections from the same image to the same line, with the original file names
The final results are in output_original.csv

License Plate Object Detection: https://github.com/bobarna/yolov7-number-plates
OCR: we implemented 2 different methods, and ended up using paddleOCR
- paddleOCR: paddleOCR folder
- custom OCR: LicensePlateOCR folder

See docs folder.