The block is used to perform preprocessing on the eval boxes either for the detection or tracking evaluation. First, add the distance between the boxes to the ego vehicle. Second, filter the boxes according to the calculated distance, number of lidar/radar points in the boxes, and either the object is a bicycle in the racks or not.
This block filters the input bounding boxes by excluding all the boxes that are located outside a desired region. The desired region can be fixed using a property or dynamic by using the second input port. A box is located inside the region if the center of the box is located inside the polygon representing that region.
This block blurs the input image by convolving the image with a low-pass filter kernel. It is useful for removing noises and high-frequency content from the image.
The block is used to stream all the datasets available under the Image Classification category offered by Tensorflow Datasets package in a batch mode to be used in training/ testing of models.
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