This project demonstrates the use of AWS Rekognition to manage and verify faces in a collection. The core functionalities include adding a new face with an employee ID, checking if a face matches existing entries, and deleting a face from the collection. Prisma is used as the database for managing employee records and face IDs.
- Save a New Face
POST /save: Add a new face to the AWS Rekognition collection, ensuring that no duplicate employee ID or face exists. - Check Match
POST /checkmatch: Verify if a given face matches any face in the AWS Rekognition collection. - Delete Face `DELETE /delete/: Remove a face from AWS Rekognition using the associated employee ID.
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AWS Account: Ensure you have an AWS account with Rekognition service enabled.
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Environment Variables: Set the following environment variables in a
.envfile:AWS_ACCESS_KEY_ID: Your AWS access key.AWS_SECRET_ACCESS_KEY: Your AWS secret key.REKOGNITION_COLLECTION_ID: The ID of your Rekognition face collection.
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Database: Set up Prisma with a database (e.g., PostgreSQL) to manage employee records.
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Clone the repository:
git clone https://github.com/Labib2003/aws-rekognition-nodejs.git cd aws-rekognition-nodejs -
Install dependencies:
npm install
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Set up the environment variables by creating a
.envfile and adding the necessary AWS and Prisma configurations. -
Run Prisma migrations to set up the database schema:
npx prisma db push
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Start the application:
npm start
Once the application is running, use an API client like Postman to test the following endpoints:
POST /save: Save a new face.POST /checkmatch: Check if a face matches.DELETE /delete/:id: Delete a face by employee ID.
- 409 Conflict: Returned when there are conflicts such as duplicate employee IDs or faces.
- 404 Not Found: Returned when resources (faces or employee IDs) are not found.
- 500 Internal Server Error: Returned for any unhandled errors.
- Express: Web framework for API routing.
- Prisma: ORM for managing the database.
- AWS Rekognition: For face detection and recognition.