Classify the entire image into a specific set of classes, ex. dog, cat, etc. Or a simple binary case of damage and no damage. The main drawback is it gives one class for the whole image, so if the image contains both a dog and a cat it will present a problem. This can be avoided by converting it to a multi-label classification, where multiple labels can be predicted for one image.