Use Case and High-Level Description

Face detector based on MobileNetV2 as a backbone with a multiple SSD head for indoor/outdoor scenes shot by a front-facing camera. During training of this model training images were resized to 448x448.




Metric Value
AP (WIDER) 92.74%
GFlops 2.406
MParams 1.851
Source framework PyTorch*

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 64 x 64 pixels.



Name: "input" , shape: [1x3x448x448] - An input image in the format [BxCxHxW], where:

Expected color order - BGR.


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

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