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Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. With Amazon SageMaker, all the barriers and complexity that typically slow down developers who want to use machine learning are removed. The service includes models that can be used together or independently to build, train, and deploy your machine learning models.

PPE Detector for Worker Safety
Free Trial

By: VITech Lab Latest Version: 3.0

Image recognition and classification model for real-time PPE compliance monitoring in industrial environments.

Product Overview

The PPE Detector for Worker Safety - is a real-time image recognition and classification model for PPE monitoring in industrial settings. Trained on a synthetic dataset of 100,000 images, it analyzes live footage from high-resolution cameras to identify workers wearing protective gear. The solution detects the presence of seven object classes on a worker: Bare Head, Helmet, Ear Protection, Welding Mask, Bare Chest, High Visibility Vest, Person. The ML model can be used in manufacturing, construction, steel, oil & gas, and other industrial environments. We also have a ready to use software, PPE Monitoring Platform: https://aws.amazon.com/marketplace/pp/B08BT5CV2F We provide free support during the trial period! After you've succeeded with the subscription, reach out at: support@vitechlab.com

Key Data

Version
By VITech Lab
Categories
Type Model Package
Fulfillment Methods Amazon SageMaker

Usage Information

Fulfillment Methods

Amazon SageMaker

Supported content types: image/jpeg

This model accepts images in the mime-type specified above.

The image must be at least 320x320. The model resizes the image to 640x640 before performing the inference. Better results are achieved with 16:9 image proportions.

Content type: text/json

For every image, the model returns a single JSON file with all the detections.

The model returns a JSON object, that includes an array with individual elements for each person detected. Each element is a list of numbers: [X0, Y0, X1, Y1, confidence, class]

  1. [X0, Y0, X1, Y1] is the bounding box around the detected object.
  2. confidence: the probability (in percents) that given bounding box contains an object.
  3. class: integer index for the class in a following order: ['Bare Head', 'Helmet', 'Welding Mask', 'Ear Protection', 'NO Visibility Vest', 'High Visibility Vest', 'Person']

Prediction method takes no additional parameters.

We recommend using this model for real-time inference for better utilization of the endpoint. Optionally, batch transform is also available.

You can find more details here: https://github.com/VITechLab/aws-sagemaker-examples/blob/master/Construction-PPE-Detector/

Additional Resources

End User License Agreement

By subscribing to this product you agree to terms and conditions outlined in the product End User License Agreement (EULA)

Support Information

PPE Detector for Worker Safety

If you have any issues or feature requests, please write to us, and we will be happy to help you as soon as possible. We can also create custom software and models optimised for your specific use case. Reach us at: support@vitechlab.com

https://vitechlab.com

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Refund Policy

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