https://github.com/nicolashaubricht/opencv-course

This repository contains Python scripts for basic image processing using OpenCV. The scripts were developed as part of a free OpenCV course, and the repository will be updated as I progress through the modules.
https://github.com/nicolashaubricht/opencv-course

computer-vision image-processing opencv python

Last synced: about 1 month ago
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This repository contains Python scripts for basic image processing using OpenCV. The scripts were developed as part of a free OpenCV course, and the repository will be updated as I progress through the modules.

• Host: GitHub
• URL: https://github.com/nicolashaubricht/opencv-course
• Owner: NicolasHaubricht
• Created: 2025-03-03T20:46:36.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-03-04T16:56:22.000Z (over 1 year ago)
• Last Synced: 2025-06-08T23:36:29.757Z (about 1 year ago)
• Topics: computer-vision, image-processing, opencv, python
• Language: Python
• Homepage:
• Size: 2.01 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# OpenCV Course

[![OpenCV](https://img.shields.io/badge/OpenCV-5.0-%235C3EE8?logo=opencv)](https://opencv.org/)

[![Python](https://img.shields.io/badge/Python-3.8%2B-blue?logo=python)](https://www.python.org/)

This repository contains Python scripts for basic image processing using OpenCV. The scripts were developed as part of a free OpenCV course, and the repository will be updated as I progress through the modules.  

## 🛠 Technologies Used  

- **Python 3.8+** - Core programming language

- **OpenCV (cv2)** - Computer vision operations

- **NumPy** - Array manipulations and mathematical operations

- **Matplotlib** - Image visualization and plotting

## 📌 Topics Covered  

The `main.py` file is organized into sections, each focusing on a specific OpenCV concept I studied. Below is an overview of the topics:

1. **Basic Image Loading and Display**

   - Loading grayscale and color images using `cv2.imread()`.

   - Inspecting image properties (shape, data type) with NumPy.

   - Displaying images using Matplotlib with proper color mapping.

2. **Working with Color Images**

   - Handling BGR vs. RGB color formats and converting between them.

   - Reversing color channels for proper visualization.

3. **Splitting and Merging Color Channels**

   - Splitting an image into its Red, Green, and Blue channels using `cv2.split()`.

   - Merging channels back into a full-color image with `cv2.merge()`.

4. **Converting Color Spaces**

   - Exploring grayscale and binary image manipulation.

   - Modifying pixel values and visualizing changes.

5. **Cropping Images**

   - Extracting regions of interest (ROI) from images using array slicing.

6. **Resizing Images**

   - Scaling images with different methods:

     - Using scaling factors (`fx`, `fy`) with `cv2.resize()`.

     - Specifying exact dimensions (with potential aspect ratio issues).

     - Maintaining aspect ratio for better quality.

7. **Saving Images**

   - Writing processed images to disk using `cv2.imwrite()`.

8. **Flipping Images**

   - Applying horizontal, vertical, and combined flips with `cv2.flip()`.

9. **Drawing Shapes**

   - Drawing lines with `cv2.line()`.

   - Drawing circles with `cv2.circle()`.

   - Drawing rectangles with `cv2.rectangle()`.

10. **Adding Text**

    - Overlaying text on images using `cv2.putText()` with customizable fonts, sizes, and colors.

11. **Combining Shapes and Text**

    - Integrating rectangles and text for annotations on images.

## 📂 Repository Structure  

```bash

opencv-course/

├── class/

├   ├── script.py

├── imports.py

├── main.py

└── README.md