I am making some custom image detector for a project.
I labeled the images using Matlab imageLabeler, but after the labels were generated we changed the path of the images and moved some of them to another folder for testing purpouses.
For the traiing of the detectors I generated a table with the corrected file names and the labels (similar to the yolo example) and I tought that the missing images will be ignored (they do not exist in the specified path, nor have I included its path in any way). The thing is that training with the complete set (existing and non existing images paths) yields better results than removing the non-existing file names.
Any idea why this is happening?