OpenCV Self-Paced Learning Exercises

OpenCV Android, C++ & Python Lab Monorepository

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Repository

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Introduction

Welcome to the OpenCV Android & C++ Lab monorepository! This project serves as an experimental sandbox and modular learning toolkit designed for exploring computer vision, image processing, and hardware sensor integration. Built with cross-platform portability in mind, the codebase bridges low-level C++ core logic with high-level Android application modules—featuring robust implementations for direct pixel manipulation (RGB/BGR gradients), alpha blending, geometric region-of-interest (ROI) filtering, split-and-merge channels, and real-time hardware camera ingestion using native GStreamer and libcamera pipelines.

Whether you are testing standalone algorithms or deploying accelerated video pipelines to mobile and embedded systems, this repository provides clean, well-structured examples to accelerate your computer vision development.

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Repository Structure

• android/ - Android Studio project containing modular getting-started activities (BlendTestActivity, CameraSnapActivity, CameraStreamActivity, etc.).
• native/ - Native C++ test harnesses and low-level processing modules.
• etc/ - License documentation and configuration files.

Getting Started

1. Clone the repository:

   git clone [https://github.com/baqwas/opencv.git](https://github.com/baqwas/opencv.git)

🎯 Repository Intent

The primary goal of this repository is twofold:

• The Learning Curve: To provide a structured, stepwise progression of C++ and Python exercises that scale from fundamental pixel manipulation to advanced deep learning-based inference and geometry transformations.
• The Unified Sandbox: To house independent project workflows—ranging from low-latency edge computing scripts on single-board hardware to mobile-optimized Android NDK modules—under a single, clean workspace.

📂 Repository Structure

opencv/
├── .github/
│   └── workflows/          # Automated CI pipeline checks
├── cpp/                    # CLion C++ Workspace (Stepwise learning exercises)
│   ├── CMakeLists.txt      # Master CMake build orchestration
│   ├── common/             # Shared helper utilities and visualization tools
│   ├── 01-getting-started/ # Core structures, matrices, and basic I/O
│   ├── 02-image-processing/# Filtering, color spaces, and thresholding
│   ├── 03-geometry-transforms/ # Affine, perspective, and resizing
│   └── ...                 # Advanced modules (contours, features, DNN)
├── python/                 # PyCharm Python Workspace (Scripts & notebooks)
│   ├── requirements.txt
│   └── exercises/
├── android/                # Android Studio Workspace (NDK / JNI integration)
└── README.md

🛠️ Technology Stack & Toolchain

• Core Engine: OpenCV 5 (5.x branch) with opencv_contrib modules.
• C++ Environment: Developed and built via CLion using modern CMake (C++17 standard).
• Python Environment: Prototyped in PyCharm with NumPy, Matplotlib, and integrated tooling.
• Mobile Environment: Handled via Android Studio utilizing native C++ layers through the Android NDK.
• CI/CD: Automated GitHub Actions workflows verifying syntax and compilation health on every push.

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📄 License

This project is open-source and available under the terms of the MIT License.

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