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Industry: Image Filtration Application

Image filtration Application

This use case focuses on developing an automated system to track and recognize gender in images and videos using AWS services. This solution provides valuable insights into the gender  demographics of audiences and enables businesses to tailor their offerings accordingly.

 

Business Use Cases

1:- Product Catalog Management

2:- Content Moderation

3:- Copyright Compliance

 

Services Implemented

Amazon Rekognition:

  • Amazon Rekognition is a deep learning-based image and video analysis service that can identify objects, people, text, scenes, and activities in images and
  • It provides APIs for various image analysis tasks, including object detection, facial recognition, text detection, celebrity recognition, and
  • You can use Amazon Rekognition to scan image objects for specific content, detect inappropriate content, identify objects, and perform various other image analysis tasks.

Amazon S3 Event Notifications:

  • Amazon S3 (Simple Storage Service) allows you to enable event notifications on S3
  • You can configure these notifications to trigger AWS Lambda functions, Amazon SQS queues,  or Amazon SNS topics in response to various S3 events, such as object creation, deletion, or restoration.
  • By integrating S3 event notifications with AWS Lambda, you can automatically process newly uploaded images and trigger scanning or analysis tasks using services like Amazon Rekognition.

AWS Lambda:

  • AWS Lambda is a serverless compute service that lets you run code in response to events without provisioning or managing
  • You can use Lambda functions to process image uploads, trigger image scanning tasks, and perform additional processing or actions based on the results.

Amazon DynamoDB:

  • Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless
  • You can use DynamoDB to store metadata, scan results, or other information related to scanned image
  • For example, you can store metadata about scanned images, such as timestamps, scanning results, or user identifiers, in a DynamoDB table for further analysis or

DynamoDB:

  • Create a DynamoDB table to store face embeddings along with corresponding object keys or S3
  • The table schema could have attributes like:
    • FaceId (Primary Key): Unique identifier for each face
    • Embedding: Face embedding generated by the Face Recognition
    • ObjectKey or S3URI: Reference to the S3 object where the face was detected

 

Workflow

 

Image/Video Upload:

  • Users upload images or videos containing human faces to an Amazon S3

Event Trigger:

  • Amazon S3 event notifications trigger an AWS Lambda function whenever new images or videos are uploaded to the designated

Lambda Function Execution:

  • The Lambda function is invoked in response to the S3 event
  • It retrieves the uploaded image or video from the S3 bucket for further

Gender Recognition:

  • Utilizing Amazon Rekognition, the Lambda function analyzes the uploaded media to identify human faces.
  • For each detected face, Amazon Rekognition estimates the gender of the individual based on facial features and context.

Metadata Storage:

  • The Lambda function stores the analysis results and metadata in an Amazon DynamoDB
  • Metadata includes information such as timestamps, media identifiers, detected faces, and estimated gender.

Feedback or Action:

  • Depending on the application requirements, additional actions may be taken based on the analysis
  • For instance, in retail environments, gender demographics can inform product placement and marketing

Monitoring and Management:

  • Monitoring tools such as Amazon CloudWatch can be utilized to monitor system performance and
  • Logs and metrics generated by the Lambda function and other AWS services are analyzed to identify issues and optimize system

Scalability and Optimization:

  • The architecture is designed to scale seamlessly with increasing media upload rates and data
  • Optimization techniques such as parallel processing and caching may be applied to enhance the efficiency of gender recognition tasks.

Maintenance and Updates:

  • Regular maintenance and updates are performed to ensure the reliability, security, and performance of the
  • AWS services receive regular updates with new features and improvements, which can be leveraged to enhance the functionality of the solution over.

 

Architecture Involved

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