Supported content types: image/jpeg

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

The image must be at least 300x300. The model resizes the image to the size specified by the user 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 JSON object, that includes an array with individual elements for each face detected. Each element has three attributes:

1. box_points: includes the bounding box around the detected face. Each bounding box consists of four numbers in [X1 Y1 X2 Y2] format in the source image coordinates.
2. classes: dictionary with class names requested and probabilities. Probability score that the person in this bounding box has a requested item. Probability is given in percents (0..100 range)

Prediction method can take additional parameter “detection-elements”: List of the classes that model is requested to detect in people: 'no_helmet', 'no_glasses', 'no_glove' - for manufacturing environment 'lab_no_coat', 'lab_no_glasses', 'lab_no_glove', 'lab_no_mask' - for healthcare environment

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/tree/master/General-Purpose-PPE-Detector