Opencv python template matching

opencv (open source computer vision library) is a powerful library for computer vision, image processing, and machine learning. one common task in image processing is template matching, which is the process of finding a template image within a larger image.

in this tutorial, we will walk through how to perform template matching using opencv in python. the template matching algorithm slides the template image over the input image, comparing the template and patch of the input image under the template image. it returns a grayscale image where each pixel denotes how much does the neighbourhood of that pixel match with the template.

here is a step-by-step guide to perform template matching using opencv in python:

### step 1: import necessary libraries

### step 2: load the input image and the template image

### step 3: perform template matching using opencv's `matchtemplate` function

### step 4: find the location of the matched template in the input image

### step 5: draw a rectangle around the matched template

### step 6: display the result

template matching can be useful in various applications such as object detection, image recognition, and image registration. experiment with different template images and input images to see how the algorithm performs in different scenarios.

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