Spot differences in images using Python and OpenCV


The output in this code represents the structural similarity index between the two input images. This value can fall into the range [-1, 1] with a value of 1 being a perfect match. SSIM index may not be restricted to image processing. In fact, because it is a symmetric measure, it can be thought of as a similarity measure for comparing any two signals. The signals can be either discrete or continuous, and can live in a space of arbitrary dimensionality.
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Veena has more than 22 years experience in the software industry. Veena is currently freelancing as a Deep Learning Consultant, speaker, author and trainer. For any consulting/ upskilling requirement on Python , machine learning and artificial intelligence, you can reach me at [email protected]