This project aims to detect and track vehicles in a video stream. The project was done by associating HOG features, machine learning models, sliding windows and heatmaps.
The project structure is as follows: assets for report: Directory containing image assets used in the project report. models: Directory containing the machine learning models used in the project. monitoring: Directory containing monitoring images used in the project. notebooks: Directory containing Jupyter notebooks used in the project. results: Directory containing the results of the project. scripts: Directory containing bash scripts for downloading the dataset. instruction_utils.py: Python script containing the utility functions for the project. predict_test.py: Python script for testing the model on a single image. train_detection_model.py: Python script for training the machine learning model. utils.py: Python script containing utility functions for the project.
Clone the repository to your local machine.
Install the required dependencies: OpenCV, NumPy, Pandas, Scikit-learn, and Matplotlib.