Image Analysis API

Overview

[NOTE] This project is experimental and is not intended for production use. It is provided as-is, without any warranties or guarantees. Use at your own risk.

Welcome to the Image Analysis API, a robust and efficient service built with C# .NET Core. This API is designed to process image files and extract valuable metadata, providing a programmatic way to analyze various aspects of your images. Whether you're building a content management system, a photo organizer, or simply need to programmatically access image properties, this API offers a solid foundation.

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Features

• Basic Metadata Extraction: Retrieve essential metadata (like dimensions, file format, creation date, camera model, etc.) from uploaded image files.
• Subject identification: Identify subjects (people, place, animals, ect.) using AI

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Technologies Used

• C#: The core language for the API.
• .NET Core: The framework providing cross-platform capabilities and high performance.
• ASP.NET Core: For building the web API endpoints.
• MetadataExtractor: A powerful library for reading metadata from various image file formats.

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Getting Started

Follow these steps to get your local copy of the Image Analysis API up and running.

Prerequisites

Before you begin, ensure you have the following installed:

• .NET SDK (version 8.0 or newer recommended)
• Git

Installation

1. Clone the repository:

   git clone [https://github.com/your-username/ImageAnalysisApi.git](https://github.com/your-username/ImageAnalysisApi.git)
   cd ImageProcessor

   (Replace your-username with your actual GitHub username and ImageAnalysisApi with your repository name)

2. Restore NuGet packages:

   dotnet restore

3. Build the project:

   dotnet build

Running the API

You can run the API directly from the command line:

dotnet run --project ImageProcessor.Api

dotnet test

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Current Limitations

• No Persistent Storage: The API currently operates without a database or any form of persistent storage. All data from processed images is held in-memory and will be lost when the application restarts.

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Roadmap

Here are some of the features and improvements planned for future releases:

• Expanded Image Format Support: Add support for more image formats like HEIC, WebP, and SVG.
• Advanced Analysis: Implement more advanced analysis features, such as:
  • Color palette extraction.
  • Object detection and recognition.
  • Facial recognition and analysis.
• Cloud Storage Integration: Allow processing images directly from cloud storage providers like AWS S3, Azure Blob Storage, or Google Cloud Storage.
• Authentication and Authorization: Add user authentication and authorization to secure the API endpoints.
• Batch Processing: Allow users to upload and process multiple images in a single request.

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