Hi, I trained a CNN for doing image classification on (41, 41, 7) shape training images and the actual image size on which the prediction is to be applied is of the size (2048, 2048, 100). I create image patches and index the (x,y) co ordinate of the patch as I need that for overlaying results in the end. The prediction is running on GPU however it is running prediction for a single patch at a given time. Is there a way to accelerate this process, where I am able to run multiple patches, remember the patch startX and startY index and get the prediction for each patch and then pool in the results properly so that each patch prediction goes to it’s proper place?
In other words for people doing CNN for image classification, how do you guys apply the prediction of CNN on the real microscopy images which are 10 to 20 fold bigger in size?
Programming language is Python using tensorflow and Keras as backends.