![]() ![]() Despite all the positives, template matching quickly fails if there are factors of variation in your input images, including changes to rotation, scale, viewing angle, etc. Of course, template matching isn’t perfect. And with a basic extension, template matching can detect multiple instances of the same/similar object in an input image (which we’ll cover next week).It doesn’t require you to perform thresholding, edge detection, etc., to generate a binary image (such as contour detection and processing does). ![]() Template matching is computationally efficient.It’s simple to implement, requiring only 2-3 lines of code.Other than contour filtering and processing, template matching is arguably one of the most simple forms of object detection: In this tutorial, you will learn how to perform template matching using OpenCV and the cv2.matchTemplate function. ![]()
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