🧠 Object Detection with OpenCV

A hands-on Jupyter Notebook project that demonstrates object detection using OpenCV in Python. The notebook processes the included image (people.webp) and applies a trained detection model (e.g., Haar cascades or pre‑trained DNN) to identify and annotate objects in the image.

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📂 Repository Structure

├── Object_Detection_Case.ipynb # Jupyter Notebook outlining the detection process and code ├── people.webp # Sample image used for detection demo └── .gitignore # Files/folders to ignore in git

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🧪 Features & Workflow

• Load and display an image (people.webp)
• Initialize OpenCV’s object detection model (like Haar cascades or DNN)
• Detect objects and draw bounding boxes
• Visualize the results within the notebook for easy inspection

Great for learning or demonstrating:

• Basics of OpenCV object detection
• How to work with images, models, and bounding boxes
• How to use Jupyter notebooks for experimentation

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