Project performed as a part of Embedded Systems subject. Developed with purpose of recognition licence plates with usage of Raspberry pi 3B.
Project is created with:
- Python 3.8
- Raspberry pi 3B
- OpenCV
- Flask
- Tesseract
Program consist of few runnable files depending on purpose we want to achieve
- main - hosts webapp that visualize camera view and predictions. Run in main dir by
python main.py - detection_contours - uses contours detection as engine. Depending on chosen mode. If debug = True app shows camera Run in main dir by
python -m src.experiments.detection_contoursview with rectangles that contains detected object also prints predictions. If debug = False, only prints predictions - detection_text_fields - uses text fields detection as engine. As above, works in to modes. Run in main dir by
python -m src.experiments.detection_text_fields - comparison - compare two detection engines using static pictures, measure time of detection, visualise results. Run in main dir by
python -m src.experiments.comparison
