aws-samples / amazon-rekognition-ppe

Detect Personal Protective Equipment using Amazon Rekognition

Detect Protective Equipment with Amazon Rekognition

Amazon Rekognition is a machine learning based image and video analysis service that enables developers to build smart applications using computer vision. Developers can quickly take advantage of different APIs to identify objects, people, text, scene and activities in images and videos, as well as inappropriate content.

With Amazon Rekognition PPE detection, you can analyze images from your on-premises cameras at scale to automatically detect if people are wearing the required protective equipment, such as face covers (surgical masks, N95 masks, cloth masks), head covers (hard hats or helmets), and hand covers (surgical gloves, safety gloves, cloth gloves). Using these results, you can trigger timely alarms or notifications to remind people to wear PPE before or during their presence in a hazardous area to help improve or maintain everyone’s safety.

You can also aggregate the PPE detection results and analyze them by time and place to identify how safety warnings or training practices can be improved or generate reports for use during regulatory audits. For example, a construction company can check if construction workers are wearing head covers and hand covers when they’re on the construction site and remind them if one or more PPE isn’t detected to support their safety in case of accidents. A food processing company can check for PPE such as face covers and hand covers on employees working in non-contamination zones to comply with food safety regulations. Or a manufacturing company can analyze PPE detection results across different sites and plants to determine where they should add more hazard warning signage and conduct additional safety training.

With Amazon Rekognition PPE detection, you receive a detailed analysis of an image, which includes bounding boxes and confidence scores for persons (up to 15 per image) and PPE detected, confidence scores for the body parts detected, and Boolean values and confidence scores for whether the PPE covers the corresponding body part. The following image shows an example of PPE bounding boxes for head cover, hand covers, and face cover annotated using the analysis provided by the Amazon Rekognition PPE detection feature.

Demo

The PPE Demo shows how you can have a serverless architecture to process frames from cameras for PPE detection.

Samples

This repository contains Python samples for different usecases of the Rekognition Detect PPE Operation.

Frame Extraction

This sample demonstrates how to extract frames from a video and upload them to an S3 Bucket

Image Detection

This sample demonstrates how to detect protective equipment in an image.

Stored Video

This sample demonstrates how to detect protective equipment in a stored video

Stream Processing

This sample demonstrates how to detect protective equipment on a streamed video

Amazon Rekognition DetectProtectiveEquipment API

To detect PPE in an image, you call the DetectProtectiveEquipment API and pass an input image. You can provide the input image (in JPG or PNG format) either as raw bytes or as an object stored in an Amazon Simple Storage Service (Amazon S3) bucket. You can optionally use the SummarizationAttributes (ProtectiveEquipmentSummarizationAttributes) input parameter to request summary information about persons that are wearing the required PPE, not wearing the required PPE, or are indeterminate.

License Summary

This library is licensed under the MIT-0 License. See the LICENSE file.

amazon-rekognition-ppe's Issues

Framework/tools used not stated in README or anywhere

After trying to deploy this solution and struggling a little bit to identify which tool was used, I found that AWS SAM was able to bundle the template to be uploaded.
The demo application states pre-built CloudFormation templates but if you want to build your own you need to dig and try which tools to use.

It would be nice to have the README updated with the tooling used to create the solution/steps.

How can I run/test this PPE Application locally

Hi Team,

Thanks for sharing sample application.

As per guidelines, I had deployed in AWS through Cloud Formation then got URL. I can able to run application with URL.

Now..

I would like to run this application locally before deploying in AWS through Cloud Formation and like to do some changes in source code.

Please help me.

Thanks and Regards
Ram

How to test demo with IP camera (RTSP)

Hi Team,

Thanks for sharing...
Please help me in below 2 points.

1. As per guidelines I can able to run demo from local machine, I placed some breakpoints but while running demo break points are not hit - directly executed. how can I run this demo with breakpoints to execute step by step in IDE: PyCham.

2. Demo application is working with Web Camera, how can I test with IP Camera in this demo. where I need to made required changes.

Thanks
Ramachandra Reddy

Using kinesis video streams

Hi,

How different is this architecture if i use Kinesis video stream for the input feed instead of API gateway ?
The downstream flow is same as your architecture. But i saw the same object detection using Kinesis video stream (uploading the frames to s3, and passing those frames to rekognition).

I'm very much interested to know how these twp architectures makes a difference. It would be very helpful if you share some insights.

Thanks

'Rekognition' object has no attribute 'detect_protective_equipment'

boto3 appears to be unaware of 'detect_protective_equipment'
boto3 - do i have to update anything?