ImageVision

Overview

This project is a serverless application that uses AWS services to provide image description based on AWS Rekognition and Bedrock services. It's designed to help you analyze and describe the content of images.

Features

• Automatic image description using AWS Rekognition.
• Serverless architecture for cost-efficiency and scalability.
• API Gateway for easy integration with other services.

Prerequisites

Before you begin, ensure you have the following prerequisites:

• An AWS account.
• AWS CLI configured with necessary access permissions.
• AWS Serverless Application Model (AWS SAM) installed.
• Python installed for local development.

Getting Started

1. Clone this repository.

git clone https://github.com/your-username/image-vision-project.git
cd image-vision-project

2. Deploy the serverless application using AWS SAM.

sam build
sam deploy --guided --stack-name image-description-stack

3. Your application is now deployed, and the API Gateway endpoint is available.

Usage

You can use the provided API endpoint to get image descriptions. Send a PUT request to the endpoint with an image file as input. Replace <api-gateway-url> with the actual URL. Example using curl:

curl -X PUT -H "Content-Type: image/jpeg" --data-binary @your-image.jpg <api-gateway-url/bucket-name/object-name>

Upon making the GET request to the same you will be able to fetch the results.

curl -X GET <api-gateway-url/bucket-name/object-name>

Additional Configuration

• You can customize the IAM role for the Lambda function to fine-tune permissions for AWS Rekognition and Bedrock services.
• Modify the Lambda function code to handle image description based on your specific use case.

Copyright

Copyright 2023 Amazon.com, Inc. or its affiliates. All Rights Reserved.

Acknowledgments

• This project was made possible by the AWS Serverless ecosystem and community contributions.

Happy image describing!