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Master Comparator (Fake Product Detection) AI-powered web application designed to detect counterfeit products. It uses Computer Vision and digital scanning to verify the authenticity of a suspect item by comparing it against a verified reference product.


✨ How It Works

The system evaluates products in two distinct phases:

  1. Phase 1: Visual Verification** Shape Similarity: Uses the ORB (Oriented FAST and Rotated BRIEF) algorithm via OpenCV to detect and match key geometric features between the real and suspect products. Color Similarity: Converts images to HSV format and compares their color histograms to ensure the exact shades and dyes match the original.

  2. Phase 2: Digital Verification** Barcode / QR Scanning: Uses zxing-cpp to scan product tags or boxes, extracting hidden digital signatures or URLs to verify the supply chain.

Based on these combined scores, the AI generates a final verdict of MATCH CONFIRMED or MISMATCH DETECTED.

🛠️ Tech Stack

Frontend: HTML5, CSS3, Vanilla JavaScript (Fetch API) Backend: Python, Flask Computer Vision: OpenCV (opencv-python-headless), Numpy Decoding: ZXing-CPP Deployment: Render

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