face-detection-retail-0004

Use Case and High-Level Description

Face detector based on SqueezeNet light (half-channels) as a backbone with a single SSD for indoor/outdoor scenes shot by a front-facing camera. The backbone consists of fire modules to reduce the number of computations. The single SSD head from 1/16 scale feature map has nine clustered prior boxes.

Example

face-detection-retail-0001.png

Specification

Metric Value
AP (WIDER) 83.00%
GFlops 1.067
MParams 0.588
Source framework Caffe*

Average Precision (AP) is defined as an area under the precision/recall curve. All numbers were evaluated by taking into account only faces bigger than 60 x 60 pixels.

Performance

Inputs

Name: input, shape: [1x3x300x300] - An input image in the format [BxCxHxW], where:

Expected color order: BGR.

Outputs

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

[*] Other names and brands may be claimed as the property of others.