![]() ![]() Resizing, by default, only changes the width and the height of the image. To resize an image in Python, resize() function of the OpenCV library is used. It is often used to discard the unnecessary information. Smaller images consume lesser size on network and GPU.ĥ. Resizing is essential to prevent the loss of information.Ĥ. Machine learning models train substantially faster on smaller images.ģ. Resizing the image is a critical pre-processing step in computer vision processes. Image resizing is necessary to increase or decrease the total number of pixelsĢ. Image interpolation occurs on resizing or distorting the image from a one-pixel grid to another. Scaling of an image in OpenCV can also be accomplished using different interpolation methods. We can manually specify the scaling size of an image, or we can use the scaling factor. Reconstruction means we need to interpolate new pixels. ![]() When an image is resized, the pixel information changes, and hence, reducing the size of an image requires resampling of the pixels while increasing the size of an image requires reconstruction of the image. Resizing refers to the scaling of an image. We’ll also understand how we can implement these functions for our computer vision applications. In this article, we’ll look at how to resize and rotate image in opencv through the various built-in functions provided by OpenCV. ![]()
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