Use Case and High-Level Description

This is a person detector that is based on MobileNetV2 backbone with two SSD heads from 1/16 and 1/8 scale feature maps and clustered prior boxes for 512x512 resolution.




Metric Value
AP 91.21% (internal test set)
Pose coverage Standing upright, parallel to image plane
Support of occluded persons YES
Occlusion coverage <50%
Min person height 100 pixels (on 1080p)
GFlops 3.143
MParams 1.817
Source framework PyTorch*

Average Precision (AP) is defined as an area under the precision/recall curve. Intersection over union threshold of 0.5 is used for matching.



Name: input, shape: [1x3x512x512] - An input image in the format [BxCxHxW], where:

Expected color order is BGR.


The net outputs blob with shape: [1, 1, N, 7], where N is the number of detected bounding boxes. Each detection has the format [image_id, label, conf, x_min, y_min, x_max, y_max], where:

Legal Information

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