Getting error : Invalid bounding boxes
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Hello everyone, I have this kind of problem and i need help.
Error using validateInputData
Bounding box data must be M-by-4 matrices of positive integer values. The following images have invalid bounding box data:
E:\ADRIAN\BAKALARKA\DATASET\vsetko2\panasonic_fullhd_01-090-045-202111091200.jpg
E:\ADRIAN\BAKALARKA\DATASET\vsetko2\panasonic_fullhd_01-090-045-202109091600.jpg
E:\ADRIAN\BAKALARKA\DATASET\vsetko2\panasonic_fullhd_01-090-270-202101091700.jpg
there are so many more images which have invalid boundig boxes... I want to ask : Can i remove these images somehow ? Or how can I solve this problem ?
for example : bounding boxes for this image : E:\ADRIAN\BAKALARKA\DATASET\vsetko2\panasonic_fullhd_01-090-045-202111091200.jpg
[] [] [] [1407,101.500000000000,179,979] []
I hope someone can help, so many thanks.
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Answers (1)
Ranjeet
on 8 May 2023
Edited: Ranjeet
on 8 May 2023
Hello Adrian,
As evident from the example you gave, the image has a valid bounding box [1407,101.500000000000,179,979] but the blank brackets “[]” are responsible for producing the error.
One way would be to remove the empty brackets.
Also make sure that each sample (image) has at-least one bounding box (this means it has at-least one object in the image that can be used for training/testing).
If an image is having multiple bounding boxes, then they should be represented as [bbx1; bbx2; bbx3; …] as represented in the example Object Detection using YOLO v3 Deep Learning. You may try the example with your dataset and see if it still gives empty bracket like “[] [] [] [1407,101.500000000000,179,979] []”.
3 Comments
Image Analyst
on 8 May 2023
@Adrian Kleffler maybe try using isempty and cellfun. Attach your variable in a .mat file if you can't figure it out.
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