![]() ![]() Call the thumbnail() method on the Image instance, passing a tuple argument with two integers to specify the width and height you desire:Īs shown under print, the size of the new instance is 400×350 pixels.Perform steps 1 and 2 of the above procedure.If you set the size of the new instance to be larger than that of the original, resize() “blows up” the instance, reducing its quality.Īs a solution, resize the image with the more advanced Pillow method, thumbnail():.Oftentimes, resizing to an exact width and height changes the image’s aspect ratio, leading to distortions.The resize() method has two drawbacks, however: Note: Instead of modifying the image file, this function returns a separate Image instance with the new dimensions. Call the resize() method on the new image instance, passing a tuple argument with two integers to specify the width and height you desire:.In case of failure, the command returns an OSError exception. The above command returns an Image object. Load the image from a file with the open() function:.To resize an image with Pillow’s resize() method: When you load an image from a file, create a new image, or generate separate instances for images, you create an instance of PIL’s Image class. Pillow is a fork of the Python Imaging Library (PIL) that supports Python 3 and numerous image formats, including PNG, JPEG, TIFF, and PPM. Resize and Crop Images in Python With Cloudinary Through Automation.Also explained is how to resize and crop Python images with Cloudinary through automation. This article describes how to resize images in bulk with the Pillow library, a popular fork of the Python Imaging Library (PIL) and, to maintain the quality and aspect ratio, in OpenCV, a robust library of programming functions for computer vision. Either way, the image’s aspect ratio changes, which results in distortion. ![]() Scaling up an image increases the number of its pixels but lowers quality. Reducing the size of an image means changing its dimensions by removing its pixels. Python is a popular object-oriented programming language for image-related tasks for webpages, visualizations, or when using Python for machine-learning operations through frameworks like OpenCV and Scikit Learn. ![]()
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