The implemetation uses YoloV3 from darknet framework, pytorch, tensorflow-gpu and keras

1. Install darknet:

   cd darknet && make clean make all cp -f libdarknet.so ../. cd ..

2. Create an anaconda environment, using conda create -n <env_name>. If you don't have anaconda installed, install anaconda

3. Activate anaconda environment using conda activate <env_name>

4. Run source install.txt will install all the necessary conda packages. Just press y whenever prompted

python main.py /path/to/input/video/file

Output will be saved in output/<input_name>_result_tracker<input_img_size>.avi . The detected number plates will be stored at output/license_plates . The detected cars will be stored at output/cars . Average FPS will be printed on the console after output has been saved.

python main.py -h for more options