Sliding window processing of large images
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mzur commented
MAIA disallows processing of images that are too large to fit into GPU memory. We could implement processing in a sliding window fashion (on smaller image crops, e.g. 4096x4096) if the image is too large. This could allow processing of tiled images or otherwise too large images and make #91 unnecessary.
Ideally, the sliding window should have an overlap so objects are not cut in half and missed. How to merge the detections in the overlap regions? Maybe a greedy method where any two detections with more than 25% (50%?) overlap are merged. In case of many overlapping annotations, those with the largest overlap are preferred.
This could be implemented entirely in Python, using pyvips to cut the images.