Image Moderation System

Overview

This project analyzes the content of uploaded images to ensure compliance with moderation policies using AWS Rekognition. If an image violates these policies, it will not be uploaded to the system. Accepted images are stored in AWS S3, and metadata such as the image path, creation date, and AWS Rekognition analysis results are saved in a PostgreSQL database.

Tech Stack

Backend (API)

• Framework: Nest.js
• Database: PostgreSQL
• ORM: TypeORM
• Cloud Services: AWS S3, AWS Rekognition
• Language: TypeScript

Frontend (UI)

• Framework: React
• Build Tool: Vite
• Language: TypeScript
• Styling: CSS
• Libraries: Axios

Project Structure

API/
  ├── src/
  │   ├── constants/
  │   ├── controllers/
  │   ├── dto/
  │   ├── entities/
  │   ├── models/
  │   ├── services/
  │   ├── types/
  │   ├── utils/
  │   ├── app.module.ts
  │   ├── config.ts
  │   └── main.ts
  ├── test/
  ├── .env
  ├── .eslintrc.js
  ├── .prettierrc
  ├── nest-cli.json
  ├── package.json
  ├── tsconfig.build.json
  └── tsconfig.json
UI/
  ├── src/
  │   ├── components/
  │   ├── hooks/
  │   ├── models/
  │   ├── services/
  │   ├── App.tsx
  │   ├── App.css
  │   └── main.tsx
  ├── public/
  ├── .env
  ├── .gitignore
  ├── eslint.config.js
  ├── index.html
  ├── package.json
  ├── tsconfig.app.json
  ├── tsconfig.json
  ├── tsconfig.node.json
  └── vite.config.ts

Setup and Installation

Prerequisites

• Node.js (v20 or higher)
• npm or yarn
• PostgreSQL
• AWS Account with S3 and Rekognition services enabled

Backend (API)

1. Clone the repository:

   git clone https://github.com/cristofima/Demo-AWS-ImageModeration
   cd API

2. Install dependencies:

   npm install

3. Copy the .env file and rename it to .env.local:

   cp .env .env.local

4. Configure environment variables in .env.local:

   DB_NAME=
   DB_USER=
   DB_PASSWORD=
   DB_HOST=
   
   AWS_S3_ACCESS_KEY=
   AWS_S3_SECRET_ACCESS_KEY=
   AWS_S3_REGION=
   AWS_S3_BUCKET_NAME=
   AWS_S3_BUCKET_FOLDER=
   
   AWS_REKOGNITION_REGION=
   AWS_REKOGNITION_ACCESS_KEY=
   AWS_REKOGNITION_SECRET_ACCESS_KEY=

5. Run the application:

   npm run start:local

Frontend (UI)

1. Navigate to the UI directory:

   cd ../UI

2. Install dependencies:

   npm install

3. Configure environment variables in .env:

   REACT_APP_API_BASE_URL=http://localhost:3000/api

4. Run the application:

   npm run dev

Image Moderation

The system classifies images into different categories based on AWS Rekognition's analysis. If an image is flagged as inappropriate, it will either be blocked or blurred before being stored.

Example of Accepted Images

(No offensive content)

Example of Moderated Images (Blurred)

(Contains sensitive content, blurred for safety)

API Endpoints

Upload Image

• Endpoint: POST /api/Posts
• Description: Uploads an image (Post), processes it with AWS Rekognition, and stores it if it passes moderation.
• Request:

  {
    "image": "(binary file)"
  }
• Response:

    {
        "id": 41,
        "imageIsBlurred": false,
        "createdAt": "2025-03-01T02:20:34.639Z",
        "imagePath": "https://demo.s3.us-west-2.amazonaws.com/images/3.jpg"
    }

Get Images

• Endpoint: GET /api/Posts?page=1&limit=12
• Description: Retrieves images (Posts).
• Response:

    {
        "data": [
            {
                "id": 40,
                "imageIsBlurred": true,
                "createdAt": "2025-02-28T21:16:01.583Z",
                "imagePath": "https://demo.s3.us-west-2.amazonaws.com/images/2.jpg"
            },
            {
                "id": 39,
                "imageIsBlurred": true,
                "createdAt": "2025-02-27T01:44:18.111Z",
                "imagePath": "https://demo.s3.us-west-2.amazonaws.com/images/1.jpg"
            },
            ...
        ],
        "metadata": {
            "page": 1,
            "limit": 8,
            "totalRecords": 38,
            "totalPages": 5
        }
    }

Author

Cristopher Coronado

Contributing

If you wish to contribute, follow these steps:

1. Fork the repository.
2. Create a new branch: git checkout -b feature-branch-name
3. Commit your changes: git commit -m "Added new feature"
4. Push to the branch: git push origin feature-branch-name
5. Open a pull request.

Acknowledgements

• Nest.js
• React
• AWS S3
• AWS Rekognition
• TypeORM
• Vite