How to generate and display a grid of images in PyTorch with plt.imshow and torchvision.utils.make_grid?

How to generate and display a grid of images in PyTorch with plt.imshow and torchvision.utils.make_grid?

You can generate and display a grid of images in PyTorch using torchvision.utils.make_grid to arrange the images in a grid and plt.imshow from the matplotlib.pyplot library to visualize the grid. Here's how you can do it:

import matplotlib.pyplot as plt import torchvision from torchvision import transforms # Assume you have a tensor of images (batch) with shape (batch_size, channels, height, width) # You can replace this with your actual tensor batch_of_images = ... # Create a grid of images using torchvision.utils.make_grid grid = torchvision.utils.make_grid(batch_of_images, nrow=4) # nrow defines the number of images per row in the grid # Convert the grid tensor to a NumPy array and transpose the dimensions grid_np = grid.permute(1, 2, 0).numpy() # Define the transformations for visualization (optional) transform = transforms.Compose([ transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]), ]) # Apply the inverse transformation to the grid grid_np = transform.inverse(transform(grid_np)) # Display the grid of images using plt.imshow plt.imshow(grid_np) plt.axis('off') # Turn off axes plt.show()

In this example, replace batch_of_images with your actual tensor of images. The code first creates a grid of images using torchvision.utils.make_grid and then converts the grid tensor to a NumPy array. The permute operation reorders the dimensions of the grid tensor to match the expected format for visualization with plt.imshow.

You can apply optional transformations (e.g., normalization) to the grid if you want. Finally, plt.imshow is used to display the grid of images with the option to turn off the axes.

Make sure you have the required libraries, such as matplotlib and torchvision, installed in your environment before running the code.

Examples

  1. "PyTorch display grid of images"

    • Description: This query seeks information on how to generate and display a grid of images in PyTorch using plt.imshow and torchvision.utils.make_grid.
    • Code Implementation:
      import torch import torchvision import matplotlib.pyplot as plt # Generate a tensor of images (batch_size, channels, height, width) images = torch.randn(8, 3, 32, 32) # Make grid of images grid_img = torchvision.utils.make_grid(images) # Display grid of images using plt.imshow plt.imshow(grid_img.permute(1, 2, 0)) plt.axis('off') plt.show()

  2. "PyTorch visualize grid of images"

    • Description: This query looks for ways to visualize a grid of images in PyTorch using plt.imshow and torchvision.utils.make_grid.
    • Code Implementation:
      import torch import torchvision import matplotlib.pyplot as plt # Generate a tensor of images (batch_size, channels, height, width) images = torch.randn(8, 3, 32, 32) # Make grid of images grid_img = torchvision.utils.make_grid(images) # Display grid of images using plt.imshow plt.figure(figsize=(10, 10)) plt.imshow(grid_img.permute(1, 2, 0)) plt.axis('off') plt.show()

  3. "PyTorch show multiple images in grid"

    • Description: This query aims to find a method to show multiple images in a grid layout using PyTorch and plt.imshow.
    • Code Implementation:
      import torch import torchvision import matplotlib.pyplot as plt # Generate a tensor of images (batch_size, channels, height, width) images = torch.randn(8, 3, 32, 32) # Make grid of images grid_img = torchvision.utils.make_grid(images) # Display grid of images using plt.imshow plt.imshow(grid_img.permute(1, 2, 0)) plt.axis('off') plt.show()

  4. "PyTorch plot grid of images"

    • Description: This query looks for methods to plot a grid of images in PyTorch using plt.imshow and torchvision.utils.make_grid.
    • Code Implementation:
      import torch import torchvision import matplotlib.pyplot as plt # Generate a tensor of images (batch_size, channels, height, width) images = torch.randn(8, 3, 32, 32) # Make grid of images grid_img = torchvision.utils.make_grid(images) # Display grid of images using plt.imshow plt.imshow(grid_img.permute(1, 2, 0)) plt.axis('off') plt.show()

  5. "PyTorch display batch of images"

    • Description: This query aims to display a batch of images in PyTorch as a grid using plt.imshow and torchvision.utils.make_grid.
    • Code Implementation:
      import torch import torchvision import matplotlib.pyplot as plt # Generate a tensor of images (batch_size, channels, height, width) images = torch.randn(8, 3, 32, 32) # Make grid of images grid_img = torchvision.utils.make_grid(images) # Display grid of images using plt.imshow plt.imshow(grid_img.permute(1, 2, 0)) plt.axis('off') plt.show()

  6. "PyTorch visualize multiple images"

    • Description: This query seeks methods to visualize multiple images in PyTorch as a grid using plt.imshow and torchvision.utils.make_grid.
    • Code Implementation:
      import torch import torchvision import matplotlib.pyplot as plt # Generate a tensor of images (batch_size, channels, height, width) images = torch.randn(8, 3, 32, 32) # Make grid of images grid_img = torchvision.utils.make_grid(images) # Display grid of images using plt.imshow plt.imshow(grid_img.permute(1, 2, 0)) plt.axis('off') plt.show()

  7. "PyTorch plot images in grid"

    • Description: This query looks for methods to plot images in a grid layout using PyTorch and plt.imshow.
    • Code Implementation:
      import torch import torchvision import matplotlib.pyplot as plt # Generate a tensor of images (batch_size, channels, height, width) images = torch.randn(8, 3, 32, 32) # Make grid of images grid_img = torchvision.utils.make_grid(images) # Display grid of images using plt.imshow plt.imshow(grid_img.permute(1, 2, 0)) plt.axis('off') plt.show()

  8. "PyTorch display images in grid"

    • Description: This query aims to display images in a grid layout using PyTorch and plt.imshow.
    • Code Implementation:
      import torch import torchvision import matplotlib.pyplot as plt # Generate a tensor of images (batch_size, channels, height, width) images = torch.randn(8, 3, 32, 32) # Make grid of images grid_img = torchvision.utils.make_grid(images) # Display grid of images using plt.imshow plt.imshow(grid_img.permute(1, 2, 0)) plt.axis('off') plt.show()

  9. "PyTorch visualize images in grid"

    • Description: This query seeks methods to visualize images in a grid layout using PyTorch and plt.imshow.
    • Code Implementation:
      import torch import torchvision import matplotlib.pyplot as plt # Generate a tensor of images (batch_size, channels, height, width) images = torch.randn(8, 3, 32, 32) # Make grid of images grid_img = torchvision.utils.make_grid(images) # Display grid of images using plt.imshow plt.imshow(grid_img.permute(1, 2, 0)) plt.axis('off') plt.show()

  10. "PyTorch plot multiple images in grid"

    • Description: This query aims to plot multiple images in a grid layout using PyTorch and plt.imshow.
    • Code Implementation:
      import torch import torchvision import matplotlib.pyplot as plt # Generate a tensor of images (batch_size, channels, height, width) images = torch.randn(8, 3, 32, 32) # Make grid of images grid_img = torchvision.utils.make_grid(images) # Display grid of images using plt.imshow plt.imshow(grid_img.permute(1, 2, 0)) plt.axis('off') plt.show()

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