Lidar Object Detection Using Complex-YOLO v4 Network Example error when retraining
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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;
1 个评论
Cris LaPierre
2024-10-12
Here is a link to the example: Lidar Object Detection Using Complex-YOLO v4 Network
回答（1 个）
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.
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