Implementation details
The Detector uses a FPN-style backbone which extracts features from different convolutions of the MobileNetV3 model. By default the pre-trained model uses the output of the 13th InvertedResidual block and the output of the Convolution prior to the pooling layer but the implementation supports using the outputs of more stages.