Welcome to the OpenCV tutorial! OpenCV (Open Source Computer Vision Library) is a powerful tool for image and video processing. Let's dive into the basics and explore how to get started.

Table of Contents

What is OpenCV? 🧠

OpenCV is an open-source computer vision and machine learning software library. It provides tools for real-time image processing, object detection, and more. 🌐

opencv logo

Figure 1: OpenCV Logo

Installation Guide 🛠️

Python

Install OpenCV via pip:

pip install opencv-python

C++

For C++ developers, use:

sudo apt-get install libopencv-dev

📌 Tip: Check out our OpenCV Basics Tutorial for more installation details.

Basic Operations 📌

  • Reading Images: Use cv2.imread() to load images.
  • Displaying Images: cv2.imshow() shows images in a window.
  • Saving Images: cv2.imwrite() saves processed images.

image processing

Figure 2: Image Processing Workflow

Advanced Topics 🔍

  • Object Detection: Use pre-trained models like Haar Cascades.
  • Video Analysis: Process video frames in real-time.
  • Machine Learning: Train custom models with OpenCV's ML module.

Resources 📚

Let me know if you'd like to explore specific topics further! 👇