How to set cov_center_x and cov_radius_x in bbox_rasterizer_config on DetectNet_v2 training

Accelerated Computing Intelligent Video Analytics TAO Toolkit
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• Hardware (3080ti)
• Network Type (Detectnet_v2)
• TLT Version (Please run “tlt info --verbose” and share “docker_tag” here)
• Training spec file(If have, please share here)
• How to reproduce the issue ? (This is for errors. Please share the command line and the detailed log here.)

In DetectNet_v2 document, bbox_rasterizer_config’s parameter are following.

cov_center_x (float): x-coordinate of the center of the object
cov_center_y (float): y-coordinate of the center of the object
cov_radius_x (float): x-radius of the coverage ellipse
cov_radius_y (float): y-radius of the coverage ellipse
bbox_min_radius (float): The minimum radius of the coverage region to be drawn for boxes

all of these are float value. how to set them?If it is own same value for different object class, such as car, person and truck.
Thank you very much.

3

There is no update from you for a period, assuming this is not an issue anymore.
Hence we are closing this topic. If need further support, please open a new one.
Thanks

Refer to DetectNet_v2 — TAO Toolkit 3.22.05 documentation
DetectNet_v2 generates 2 tensors, cov and bbox. The image is divided into 16x16 grid cells. The cov tensor (short for “coverage” tensor) defines the number of grid cells that are covered by an object. The bbox tensor defines the normalized image coordinates of the object top left (x1, y1) and bottom right (x2, y2) with respect to the grid cell. For best results, you can assume the coverage area to be an ellipse within the bbox label with the maximum confidence assigned to the cells in the center and reducing coverage outwards.

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