Python for Computer Vision: Object (Traffic Sign) Detection

Python for Computer Vision: Object (Traffic Sign) Detection udemy course

Learn how to develop an object detection application

In this course, you will learn how to develop a complete computer vision application for object detection from scratch, even if you are a beginner in Python or image processing. Unlike my other course, "Learn Computer Vision with OpenCV and Python," which covers advanced topics and specialized applications, this course is designed to take you step by step—from the fundamentals of Python programming to implementing a fully functional object detector using basic image processing techniques.

What You Will Learn:

1. Python Fundamentals for Beginners

   • Introduction to Python syntax, variables, loops, and functions.

   • Working with libraries like NumPy and Matplotlib for numerical computing and visualization.

   • Handling images as arrays and performing basic operations.

2. Image Processing Basics

   • Loading, displaying, and manipulating images using OpenCV.

   • Key techniques like filtering, edge detection, and thresholding.

   • Understanding color spaces (RGB, HSV, grayscale) and their role in detection.

3. Building a Simple Object Detector

   • Implementing contour detection and shape recognition.

   • Developing a basic object detection model using template matching or color-based segmentation.

   • Enhancing detection accuracy with morphological operations (erosion, dilation).

By the end of this course, you will have a strong foundation in Python programming for computer vision and the ability to build your own object detection applications. Whether you're a student, hobbyist, or aspiring AI developer, this course will be one of your best resources for mastering practical computer vision skills with clear, detailed explanations and real-world implementation.

Enroll now and start your journey into the exciting world of computer vision!