Learn OPENCV with Real Code Examples

Install Python 3.8+

Install OpenCV via pip: pip install opencv-python

For full features including contrib modules: pip install opencv-contrib-python

Verify installation: import cv2; cv2.__version__

Optionally set up IDE or Jupyter notebook for experimentation

Install Python/C++ compiler

Install OpenCV via pip or build from source

Set up IDE or notebook environment

Configure optional GPU support

Verify installation by loading sample images/videos

main.py / main.cpp

data/ - images and videos

utils/ - filters and helper functions

models/ - pre-trained classifiers and DNNs

notebooks/ - prototyping and experiments

python main.py - run Python script

opencv_version - check OpenCV version

pip install opencv-python - install library

python -m pip show opencv-python - view package info

jupyter notebook - run interactive experiments

Supports Unicode text rendering

Handles images from any locale

Compatible with multi-language OCR pipelines

Works with datasets worldwide

Integrates with global ML/DL models

Cross-platform support

Available for multiple languages

Open-source and free

Community support and tutorials

Works for beginners and experts

Visualize images with OpenCV imshow

Use Matplotlib or Plotly for plotting

Draw shapes/text on images for annotation

Custom GUI via HighGUI, PyQt, or Tkinter

Highlight detected objects or features

Manage loaded images/videos in memory

Track transformations and preprocessing steps

Store intermediate results if needed

Manage model weights and configurations

Use version control for scripts and datasets

Organize images/videos in directories

Preprocess consistently across datasets

Annotate images for object detection

Store trained models securely

Handle large datasets efficiently