Use Case and High-Level Description

Face detector based on MobileNetV2 as a backbone with a multiple SSD head for indoor and outdoor scenes shot by a front-facing camera. During the training of this model, training images were resized to 256x256.

Example

Specification

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.

Performance

Inputs

Name: input, shape: [1x3x256x256] - An input image in the format [BxCxHxW], where:

• B - batch size
• C - number of channels
• H - image height
• W - image width

Expected color order: BGR.

Outputs

The net outputs a blob with the 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:

• image_id - ID of the image in the batch
• label - predicted class ID
• conf - confidence for the predicted class
• (x_min, y_min) - coordinates of the top left bounding box corner
• (x_max, y_max) - coordinates of the bottom right bounding box corner

Legal Information

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