Face detector for driver monitoring and similar scenarios. The network features a default MobileNet backbone that includes depth-wise convolutions to reduce the amount of computation for the 3x3 convolution block.
|AP (head height >10px)||37.4%|
|AP (head height >32px)||84.8%|
|AP (head height >64px)||93.1%|
|AP (head height >100px)||94.1%|
|Min head size||90x90 pixels on 1080p|
input, shape: [1x3x384x672] - 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. The results are sorted by confidence in decreasing order. Each detection has the format [
image_id- ID of the image in the batch
label- predicted class ID
conf- confidence for the predicted class
y_min) - coordinates of the top left bounding box corner
y_max) - coordinates of the bottom right bounding box corner.
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