- Keeps track of pedestrians and vehicles in the road.
- Tracks the movement and direction of all elements in the road.
- Estimates the speed of each object and a direction vector.
- Tracking performed based on object centroid position obtained from background subtraction and blob segmentation.
- Download OpenCV 4.2.0 and install it on your system (use scripts/install-opencv.sh).
- For optimal performance ensure that optimizations are enabled.
- If a NVIDIA is used ensure that the CUDA SDK is installed.
- Install CMAKE and setup your IDE for C++ development.
- Install GCC for linux development or Visual Studio for windows development.
- Dependencies can also be obtained from the conan package manager (https://conan.io/center/)
- To install dependencies run
conan install ..
- To install dependencies run
- Data for testing can be downloaded from youtube.
- The file scripts/dataset.sh can be used to obtain test data.
- Test video data is obtained from youtube might be suject to licensing and not available for commercial usage.
- YOLO model is used to classify moving objects such as cars and pedestrians.
- YOLO V5 is available on https://pytorch.org/hub/ultralytics_yolov5/ / https://github.com/ultralytics/yolov5, check the latest releases on github.
- The PyTorch models have to be converted into ONNX files.
- This project is distributed under MIT license and can be freely used for commercial applications.
- Project license is available on the Github page.