A Detailed Guide to the Powerful SIFT Technique for Image Matching (with Python code)

The keen-eyed among you will also have noticed that each image has a different background, is captured from different angles, and also has different objects in the foreground (in some cases). I'm sure all of this took you a fraction of a second to figure out. It doesn't matter if the image is rotated at a weird angle or zoomed in to show only half of the Tower. This is primarily because you have seen the images of the Eiffel Tower multiple times and your memory easily recalls its features. We naturally understand that the scale or angle of the image may change but the object remains the same.