Full FOV + Depth in Detection Network

lss5fc0d

If I use YoloSpatialDetectionNetwork to squeeze or letterbox my image (as described here) and then feed it to
YoloSpatialDetectionNetwork, should I expect the depth to work? It seems like there's no way for it to know how to align the disparity map. I've tried to figure this out experimentally but the results have been ambiguous. Is there a correct way to get full FOV and get the correct depth out of a Detection Network?

erik

Hello lss5fc0d ,
I would suggest displaying also passthrough depth frame and depth bounding boxes - as shown in this example, on the left frame of the video. That way, it will be clear if the mapping is done correctly or not.
THanks, Erik

tyler

I'm trying to do the same thing, and have displayed the depth frame and depth bounding boxes as shown in the example provided. The bounding boxes do not seem to match the bounding boxes from the stretched camera preview. What suggestions would you have for fixing this? I'm thinking I could split the YoloSpatialDetectionNetwork into a YoloDetectionNetwork and a SpatialLocationCalculator, and warp the bounding box that is output from the YoloDetectionNetwork according to how the feed was stretched, and then feed that into the SpatialLocationCalculator. Does this make sense, and/or are there other possible solutions?

erik

tyler Could you share the source code for this? From the post, it seems you would need to do something similar to this: https://docs.luxonis.com/projects/api/en/latest/tutorials/dispaying_detections/#edit-bounding-boxes
Thanks, Erik