Lidar Object Detection Using Complex-YOLO v4 Network Example error when retraining

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Rogelio
Rogelio 2024-10-12
评论： Rogelio 2024-10-12
When it is modified the Region of Interest it crashes
in transformPCtoBev.m change
% labelsBEV(:,1) = int32(floor(labelsBEV(:,1)/gridParams{1,3}{1})) + 1;
labelsBEV(:,1) = int32(floor(labelsBEV(:,1)/gridParams{1,3}{1})+gridParams{1,2}{1}/2) + 1;
% loc(:,2) = int32(floor(loc(:,2)/gridW)) + 1;
loc(:,2) = int32(floor(loc(:,2)/gridW)+bevWidth/2) + 1;

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回答（1 个）

Cris LaPierre
Cris LaPierre 2024-10-12
编辑：Cris LaPierre 2024-10-12
The change is causing the code to fail the iCheckBoxes test inside validateInputDataComplexYOLOv4.m. This function checks that the bounding box position falls within the image size. The changes you are wanting to make position some of the bboxes outside the image.
Specifically, these tests:
classes = {'numeric'};
attrs = {'nonempty', 'nonnan', 'finite', 'positive', 'nonzero', 'nonsparse', '2d', 'ncols', 4};
attrsYaw = {'nonempty', 'nonnan', 'finite', 'nonsparse'};
validateattributes(boxes(:,1)+boxes(:,3)-1, classes, {'<=', imageSize(2)});
validateattributes(boxes(:,2)+boxes(:,4)-1, classes, {'<=', imageSize(1)});
imageSize is [608,608,3]
For comparison, here is what the same array looks like in the original code.
  1 个评论
Rogelio
Rogelio 2024-10-12
Hi, thank you for your reply. Definitely I missed something.
When I changed yMin to a value lower than 0, the tutorial raised an error. With these changes I was able to train it but I will need to check what I missed.

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