The video used in the tutorial can be downloaded here.

A Yolov8 pre-trained model (YOLOv8n) was used to detect vehicles.

A licensed plate detector was used to detect license plates. The model was trained with Yolov8 using this dataset.

• The model is available here.

The sort module needs to be downloaded from this repository.

git clone https://github.com/abewley/sort

• Make an environment with python=3.10 using the following command

conda create --prefix ./env python==3.10 -y

• Activate the environment

source activate ./env

• Install the project dependencies using the following command

pip install -r requirements.txt

• Run main.py with the sample video file to generate the test.csv file

python main.py

• Run the add_missing_data.py file for interpolation of values to match up for the missing frames and smooth output.

python add_missing_data.py

• Finally run the visualize.py passing in the interpolated csv files and hence obtaining a smooth output for license plate detection.

python visualize.py