Getting Started

Set up your development environment and run your first OpenCV program.

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Prerequisites

Before starting this course, ensure you have:

• Python 3.8 or higher installed
• pip package manager
• Webcam (recommended for real-time projects)
• Basic familiarity with Python and NumPy

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Installation

Step 1: Clone the Repository

git clone https://github.com/marcus888-techstack/introduction-to-opencv.git
cd introduction-to-opencv

Step 2: Create a Virtual Environment (Recommended)

# Create virtual environment
python -m venv venv

# Activate it
# On macOS/Linux:
source venv/bin/activate

# On Windows:
venv\Scripts\activate

Step 3: Install Dependencies

pip install -r requirements.txt

This installs:

• opencv-python - Main OpenCV package
• opencv-contrib-python - Extra modules (face, tracking, etc.)
• numpy - Array operations
• pytesseract - OCR integration
• easyocr - Alternative OCR

Step 4: Verify Installation

import cv2
print(f"OpenCV version: {cv2.__version__}")

Expected output: OpenCV version: 4.x.x

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Repository Structure

introduction-to-opencv/
├── curriculum/              # Learning modules (11 + extras)
│   ├── 01_core/            # Core operations
│   ├── 02_imgproc/         # Image processing
│   ├── 03_io_gui/          # I/O and GUI
│   ├── 04_features2d/      # Feature detection
│   ├── 05_objdetect/       # Object detection
│   ├── 06_video/           # Video analysis
│   ├── 07_calib3d/         # Camera calibration
│   ├── 08_dnn/             # Deep learning
│   ├── 09_ml/              # Machine learning
│   ├── 10_photo/           # Computational photography
│   ├── 11_stitching/       # Image stitching
│   └── extras/             # Face, tracking, OCR
│
├── projects/               # 6 practical projects
│   ├── 01_document_scanner/
│   ├── 02_face_attendance/
│   ├── 03_license_plate/
│   ├── 04_object_counting/
│   ├── 05_quality_inspection/
│   └── 06_gesture_control/
│
├── assets/                 # Sample images and data
├── utils/                  # Shared utilities
├── requirements.txt        # Dependencies
└── README.md

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Running Tutorials

Each curriculum module contains Python scripts you can run directly:

# Run Core basics tutorial
python curriculum/01_core/01_basics.py

# Run Image Processing filtering tutorial
python curriculum/02_imgproc/01_filtering.py

# Run Feature detection tutorial
python curriculum/04_features2d/01_corners.py

Interactive Controls

Most tutorials have keyboard controls:

Key	Action
q or ESC	Quit the program
s	Save current image
Space	Pause/resume video
+ / -	Adjust parameters

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Running Projects

Projects are complete applications with a main.py entry point:

# Document Scanner
cd projects/01_document_scanner
python main.py

# Face Attendance System
cd projects/02_face_attendance
python main.py

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Sample Images

The assets/ folder contains sample images for testing:

assets/
├── images/         # Sample images (lena.png, etc.)
├── videos/         # Sample video clips
└── models/         # Pre-trained model files

If you need additional test images, you can:

1. Use your own images
2. Use OpenCV’s built-in samples:

   import cv2
   img = cv2.imread(cv2.samples.findFile('lena.jpg'))
   

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Webcam Setup

Many tutorials use your webcam. Test it with:

import cv2

cap = cv2.VideoCapture(0)  # 0 = default camera
while True:
    ret, frame = cap.read()
    if not ret:
        break
    cv2.imshow('Webcam Test', frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
cap.release()
cv2.destroyAllWindows()

Troubleshooting Webcam Issues

• No camera found: Try VideoCapture(1) or VideoCapture(2)
• Permission denied (macOS): Grant camera access in System Preferences > Privacy
• Virtual camera: Install OBS Virtual Camera for testing

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Learning Path

Recommended order for completing the curriculum:

Week 1: Foundations
├── Day 1: 01_core + 03_io_gui (basics)
├── Day 2: 02_imgproc (filtering, morphology)
└── Day 3: 02_imgproc (contours, histograms)

Week 2: Features & Detection
├── Day 1: 04_features2d (detectors, matchers)
├── Day 2: 05_objdetect (Haar, templates)
└── Day 3: 06_video (tracking, optical flow)

Week 3: Advanced Topics
├── Day 1: 07_calib3d (calibration, 3D)
├── Day 2: 08_dnn (deep learning)
└── Day 3: 09_ml + 10_photo

Week 4: Projects
├── Day 1-2: Project implementation
└── Day 3: 11_stitching + extras

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Getting Help

• Module README files: Each curriculum folder has a README with algorithm explanations
• Official Docs: OpenCV Python Tutorials
• GitHub Issues: Report bugs or ask questions in the repository

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Next Steps

Ready to start learning? Begin with the first module:

Start with Core Operations View All Modules