# define transformt o resize the image with given size Print('Size of the Original image:', size) # compute the size(width, height) of image The original image is of size (700,700) # import the required libraries The input image is resized to (300, 350). This image is used as the input file in all the following examples. Change the crop size according your need.Īpply the above-defined transform on the input image to resize the input image. For example, the given size is (300,350) for rectangular crop and 250 for square crop. The input image is a PIL image or a torch tensor or a batch of torch tensors.ĭefine a transform to resize the image to a given size. Make sure you have already installed them.

Import required Image library from PIL import Image Create an Image Object from an Image im Image.open('images/cat.jpg') Display actual image im.show() Make the new image half the width and half the height of the original image. In all the following examples, the required Python libraries are torch, Pillow, and torchvision. The program for resizing and saving the resized image is given below. We could use the following steps to resize an input image to a given size. It returns a resized image of given size. If size is an int, then the resized image will be a square image. size is a sequence like (h, w), where h and w are the height and width of the output image. Size – Size to which the input image is to be resized. If the image is neither a PIL image nor a tensor image, then we first convert it to a tensor image and then apply the Resize()transform. This transform also accepts a batch of tensor images, which is a tensor with where B is the number of images in the batch. Resizing, by default, does only change the width and height of the. A tensor image is a torch tensor with shape, where C is the number of channels, H is the image height, and W is the image width. To resize an image in Python, you can use cv2.resize() function of OpenCV library cv2. Resize() accepts both PIL and tensor images. It's one of the transforms provided by the ansforms module. The original image with dimensions has been resized to using resize() function.The Resize() transform resizes the input image to a given size. Output Original Dimensions : (149, 200, 4) Print('Resized Dimensions : ',resized.shape) Resized = cv2.resize(img, dim, interpolation = cv2.INTER_AREA) Height = int(img.shape * scale_percent / 100) Width = int(img.shape * scale_percent / 100) Scale_percent = 60 # percent of original size Print('Original Dimensions : ',img.shape) Img = cv2.imread('/home/img/python.png', cv2.IMREAD_UNCHANGED) We will use this scale_percent value along with original image’s dimensions to calculate the width and height of output image. Providing a value <100 downscales the image provided. In the following example, scale_percent value holds the percentage by which image has to be scaled. Resize only the height (Increase or decrease the height of the image keeping width unchanged)įollowing is the original image with dimensions (149,200,4) (height, width, number of channels) on which we shall experiment on :Įxample 1 – Resize and Preserve Aspect Ratio Downscale with resize().Resize only the width (Increase or decrease the width of the image keeping height unchanged).Upscale (Increase the size of the image).

Downscale (Decrease the size of the image).Preserve Aspect Ratio (height to width ratio of image is preserved).We will look into examples demonstrating the following resize operations. Resizing an image can be done in many ways. INTER_CUBIC – a bicubic interpolation over 4×4 pixel neighborhood INTER_LANCZOS4 – a Lanczos interpolation over 8×8 pixel neighborhood But when the image is zoomed, it is similar to the INTER_NEAREST method. It may be a preferred method for image decimation, as it gives moire’-free results. INTER_NEAREST – a nearest-neighbor interpolation INTER_LINEAR – a bilinear interpolation (used by default) INTER_AREA – resampling using pixel area relation. flag that takes one of the following methods. The syntax of resize function in OpenCV is cv2.resize(src, dsize]]])

Image resize python