Tracking Moving Objects Using Python
Analyzing videos manually to extract basic statistics requires significant human resources and time. Computer vision helps automate this process in many areas. It can be applied to almost anything, from counting birds in the sky to identifying foods in images.
In this project, we’ll learn how to detect and track objects. We’ll build a Python application and use the popular OpenCV library. We’ll use footage of traffic at an intersection to count the cars entering and leaving. We can also apply these CV techniques to other problems in this field, so feel free to experiment afterward.
This project uses OpenCV, Tkinter, NumPy, and pandas. We’ll extend our knowledge in computer vision with OpenCV, learn GUI interaction with Tkinter, and perform mathematical computations and data operations using NumPy and pandas.