Image Labels Generator

This project demonstrates how to use Flask and Amazon Rekognition to build an image labels generator. Users can upload images, which are stored in Amazon S3 and analyzed using Rekognition to generate descriptive labels with confidence scores.

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Features

• Upload Images: Upload images to Amazon S3 via a POST request.
• Analyze Images: Use Amazon Rekognition to identify objects, scenes, and other details in images.
• Output Results: Get a JSON response with labels and confidence scores.

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How to Run the Project

Prerequisites

1. AWS Account:

   • Set up an S3 bucket and enable Amazon Rekognition.
   • Ensure the IAM role associated with your project has the following policies:
     • AmazonS3FullAccess
     • AmazonRekognitionFullAccess

2. Python Environment:

   • Install Python 3.9+.
   • Install pip (Python package manager).

Steps to Run Locally

1. Clone the repository:

   git clone https://github.com/Harrygithubportfolio/Image-Labels-Generator.git

Navigate to the project directory:

bash Copy code cd Image-Labels-Generator Set up a virtual environment:

bash Copy code python3 -m venv rekognition_env source rekognition_env/bin/activate # For macOS/Linux rekognition_env\Scripts\activate # For Windows Install dependencies:

bash Copy code pip install -r requirements.txt Run the Flask application:

bash Copy code python3 app.py Test the endpoints:

Upload an image: bash Copy code curl -X POST -F "file=@/path/to/image.jpg" http://127.0.0.1:5000/upload Analyze the uploaded image: bash Copy code curl -X POST -H "Content-Type: application/json"
-d '{"filename": "image.jpg"}'
http://127.0.0.1:5000/analyze AWS Services Used Amazon S3: For image storage. Amazon Rekognition: For analyzing images and generating descriptive labels. Future Enhancements Add a frontend with a simple file upload form and results display. Deploy the application using AWS Elastic Beanstalk or EC2. Implement user authentication to manage access to the service. Sample Output Here’s an example of the JSON response returned by the /analyze endpoint:

json Copy code { "labels": [ { "Name": "Person", "Confidence": 99.99 }, { "Name": "Portrait", "Confidence": 98.75 }, { "Name": "Photography", "Confidence": 96.50 } ] } Author Harry Graham This project was created to demonstrate cloud and Python development skills using AWS services.