🧩 Template Matching Module – Object Detection from Larger Image (OpenCV)

This module implements template matching using OpenCV to detect and localize smaller objects (templates) within a larger image. Designed as a plug-and-play component of a larger computer vision-based application, it serves use cases such as logo detection, icon recognition, and UI element localization.

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🔍 What It Does

• Takes a template image and a larger input image
• Uses cv2.matchTemplate() to scan for best matches
• Draws bounding boxes around the detected regions
• Returns coordinates and confidence scores

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🧠 Core Features

• ✅ Multiple Template Match Methods (TM_CCOEFF, TM_SQDIFF, etc.)
• 🖼️ Match Visualization with Bounding Boxes
• 📈 Match Confidence Threshold Control
• 🔄 Easily Integrable as a CV Module

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🛠️ Technologies Used

• Language: Python
• Libraries: OpenCV (cv2), NumPy, Matplotlib (for visualization)

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📂 Folder Structure

template-matching-module/
├── templates/               # Template images
├── inputs/                  # Larger input images
├── matched_outputs/         # Result images with bounding boxes
├── template_matcher.py      # Core matching logic
└── README.md

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🚀 Getting Started

# Clone this module
git clone https://github.com/yourusername/template-matching-module.git
cd template-matching-module

# Install dependencies
pip install opencv-python numpy matplotlib

# Run the template matcher
python template_matcher.py --template templates/logo.png --image inputs/screen.png --method TM_CCOEFF_NORMED

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⚙️ Parameters

• --template: Path to the template image
• --image: Path to the larger image
• --method: (Optional) Template match method (e.g., TM_CCOEFF, TM_SQDIFF)
• --threshold: (Optional) Match confidence threshold (default: 0.8)

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📦 Use Case Integration

You can import this as a module in larger applications:

from template_matcher import find_template_matches

matches = find_template_matches("inputs/image.jpg", "templates/icon.png", threshold=0.85)

Each match includes bounding box coordinates and confidence score.

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💡 Key Learnings

• Template matching works well for identical scale & rotation
• Performance drops if templates are scaled or transformed
• Useful for rapid prototyping and fixed-layout recognition tasks

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🤝 Contributing

Feel free to fork this and:

• Add scale-invariant or multi-scale support
• Improve threshold calibration
• Integrate with Flask or streamlit UI modules

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📄 License

This module is licensed under the MIT License.

“Find what you’re looking for — pixel by pixel.”