This is a vehicle 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 384x384 resolution.
|AP @ [ IoU=0.50:0.95 ]||0.323 (internal test set)|
Average Precision (AP) is defined as an area under the precision/recall curve.
input, shape: [1x3x384x384] - 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- ID of the image in the batch
label- predicted class ID (0 - vehicle)
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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