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Gradiant / pyodi

Python Object Detection Insights
https://gradiant.github.io/pyodi/
Mozilla Public License 2.0
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Image to labels validation functionality #190

Open merryHunter opened 1 year ago

merryHunter commented 1 year ago

Hi,

I am wondering, do you think it makes sense to introduce validation of image paths for annotations? like pyodi validate trainval.json --data-dir $DATA so that it outputs if there are any missing images while annotations for them do exist. Let me explain briefly the reasoning.

In my case, I often have issues with exporting datasets in COCO format from CVAT. Suppose I have a few projects where by some reason images have same name. Then, after I bring down images to a single folder, some images will be overwritten, or maybe they were missed from the beginning. Then, annotations may exist, but there is no easy out of the box tool to check the correspondence between annotations and images (particularly after all merge/random split operations).

Could it make sense to eliminate annotations for missing images automatically?

jorgenusan commented 1 year ago

Hi!

It might be a good idea! I think it would be good to add one more parameter to indicate a new resulting json with the new annotations instead of deleting them from the original json.

If you have time and want to add this functionality you can open a pull request! :)