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When to use resize, downscale, and resize?


Asked by Luis McCoy on Dec 10, 2021 FAQ



Resize serves the same purpose, but allows to specify an output image shape instead of a scaling factor. Note that when down-sampling an image, resize and rescale should perform Gaussian smoothing to avoid aliasing artifacts. See the anti_aliasing and anti_aliasing_sigma arguments to these functions.
Similarly,
Rescale, resize, and downscale Rescale operation resizes an image by a given scaling factor. The scaling factor can either be a single floating point value, or multiple values - one along each axis. Resize serves the same purpose, but allows to specify an output image shape instead of a scaling factor.
Furthermore, Sometimes, it is necessary to transform the loaded image. In the image processing, we need to resize the image to perform the particular operation. Images are generally stored in Numpy ndarray (array). The ndarray.shape is used to obtain the dimension of the image.
Keeping this in consideration,
Resize images with the CSS max-width property¶ There is a better way for resizing images responsively. If the max-width property is set to 100%, the image will scale down if it has to, but never scale up to be larger than its original size. The trick is to use height: auto; to override any already present height attribute on the image.
In this manner,
To resize image in Python, OpenCV cv2.resize() can be used. cv2 resize can upscale, downscale, resize to a desired size while considering aspect ratio.