Slice or downsize (resize) image for neural networks

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Given a dataset of images with very big resolution, 8000x6000, which is the best method to train a neural network? For image segmentation and not only.

As the title says, should I slice them for 800x600 each patch of image or should I resize the whole image to 800x600?

In the first case I'd lose the content aware and in second case I'd lose a lot of details but it will be content aware of the full image.

Thank you!

image-segmentation training-data machine-learning neural-network dataset
1 Answers

Resizing is a better option. Often your neural network does not require all the details from a super high resolution, and a smaller resolution suffices. The content of the image, on the other hand, is important and it may become problematic depending on what part of the image you crop it.

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