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C++ application that analyzes images using Amazon Rekognition, reporting high-confidence labels and their associated files for AI-driven image classification.

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Image-Analysis-Using-Amazon-Rekognition

This project, developed as part of CS 211: Fundamentals of Computer Programming II, demonstrates foundational C++ skills through an AI-powered image analysis application.

Using Amazon's Rekognition service, the program analyzes a set of images and extracts high-confidence object labels (≥ 80% confidence). For each label, the program also tracks which images were associated with it.

🛠️ Key Features

  • Reads and processes .jpg images from a user-specified directory

  • Leverages a provided Rekognition C++ library to return image labels

  • Stores and displays the confidence score for each detected label

  • Tabulates and reports label-to-image associations

  • Filters results based on a minimum 80% confidence threshold

🔧 Technologies Used:

  • C++17

  • Amazon Rekognition (via provided C++ wrapper)

  • Standard Template Library (STL): vectors, strings, file I/O

  • Git for version control

📌 Concepts used in this project:

  • Image processing

  • Structs & vectors

  • Basic file system traversal

  • API interaction via libraries

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C++ application that analyzes images using Amazon Rekognition, reporting high-confidence labels and their associated files for AI-driven image classification.

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