Pytorch Size Mismatch Tensor Forward Feed Image Rgb

PyTorch – How to resize an image to a given size?

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The Resize() transform resizes the input image to a given size. It's one of the transforms provided by the torchvision.transforms module. Resize() accepts both PIL and tensor images. A tensor image is a torch tensor with shape [C, H, W], where C is the number of channels, H is the image height, and W is the image width.

This transform also accepts a batch of tensor images, which is a tensor with [B, C, H, W]where B is the number of images in the batch. 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.

Syntax

torchvision.transforms.Resize(size)(img)

Parameterss

• Size – Size to which the input image is to be resized. size is a sequence like (h, w), where h and w are the height and width of the output image. If size is an int, then the resized image will be a square image.

It returns a resized image of given size.

Steps

We could use the following steps to resize an input image to a given size.

• Import the required libraries. In all the following examples, the required Python libraries are torch, Pillow, and torchvision. Make sure you have already installed them.

import torch import torchvision import torchvision.transforms as T from PIL import Image import matplotlib.pyplot as plt

• Read the input image. The input image is a PIL image or a torch tensor or a batch of torch tensors.

img = Image.open('lounge.jpg')        

• Define a transform to resize the image to a given size. For example, the given size is (300,350) for rectangular crop and 250 for square crop. Change the crop size according your need.

# transform for rectangular resize transform = T.Resize((300,350))  # transform for square resize transform = T.Resize(250)

• Apply the above-defined transform on the input image to resize the input image.

resized_img = transform(img)        

• Show the resized image.

plt.imshow(resized_img)

Input Image

This image is used as the input file in all the following examples.

Example 1

The input image is resized to (300, 350). The original image is of size (700,700)

# import the required libraries import torch import torchvision.transforms as T from PIL import Image import matplotlib.pyplot as plt  # read the input image img = Image.open('lounge.jpg')  # compute the size(width, height) of image size = img.size print("Size of the Original image:", size)  # define transformt o resize the image with given size transform = T.Resize(size = (250,450))  # apply the transform on the input image img = transform(img) print("Size after resize:", img.size) plt.imshow(img) plt.show()

Output

It will return the resized image and also print the size of the original image and the output image on the console.

Size of the Original image: (640, 427) Size after resize: (450, 250)

Example 2

Let's take another example −

import torch import torchvision.transforms as T from PIL import Image import matplotlib.pyplot as plt  img = Image.open('lounge.jpg') size = img.size print("Size of Original image:", size)  transform = T.Resize(size = (400,200)) img = transform(img)  plt.imshow(img) print("Size after resize:", img.size) plt.show()

Output

It will produce the following output −

Size of the Original image: (640, 427) Size after resize: (200, 400)

Updated on 06-Jan-2022 11:38:02

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Source: https://www.tutorialspoint.com/pytorch-how-to-resize-an-image-to-a-given-size

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