OpenCV Documentation Tutorial 📚

Welcome to the OpenCV documentation guide! OpenCV (Open Source Computer Vision Library) is a powerful tool for image and video processing. Here's a quick overview to help you get started:

📌 What is OpenCV?

OpenCV is an open-source computer vision and machine learning software library. It provides Python, C++, and Java interfaces and includes over 2,500 optimized algorithms.

🛠 Installation Guide

1. Python: Use pip install opencv-python
2. C++: Download from OpenCV official site
3. Java: Install via Maven:

   <dependency>
       <groupId>org.openpnp</groupId>
       <artifactId>opencv</artifactId>
       <version>4.5.5-0</version>
   </dependency>
   

🔍 Core Features

• Image Processing: Edge detection, filtering, and transformations
• Video Analysis: Motion tracking, object detection, and background subtraction
• Machine Learning: Pre-trained models and custom training pipelines
• 3D Vision: Stereo vision and depth estimation

🌐 Learning Resources

• OpenCV Documentation Home
• Beginner Tutorials
• Advanced Topics

📁 Sample Code

import cv2
# Load an image
img = cv2.imread("test.jpg")
# Convert to grayscale
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Display the result
cv2.imshow("Grayscale Image", gray)
cv2.waitKey(0)

For more in-depth information, explore our OpenCV documentation hub! 🚀