Object detection on large images

(John) #1

hi,

is there an example of doing object detection on large images, cropping them into smaller sizes and combining results after prediction ? I’m looking for a similar example as this paper describes

“Images in DOTA are so large that they cannot be directly sent to CNN-based detectors. Therefore, wecrop a series of 1024×1024 patches from the original images with a stride set to 512.”

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(Kushajveer Singh) #2

I have not read the paper, but I did a similar thing. I split the image into a 3x3 grid and then did object detection on the 9 patches + the original image (which you can skip). And then combine the predictions in to a single image.

The main repo is here. You only need these process_labels.py and make_splits.py.

Comment if you are not able to follow some code or approach.

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(John) #3

thank you very much, i will check it out ! :+1:

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