Working with IPython.core.display.Image

I compared different methods of loading image from url. And using IPython.display.Image(url) is the fastest. So Is it possible to work with IPython.core.display.Image in dataset?

from IPython.display import Image
from torchvision.transforms import Resize
import torch 
a = IPython.display.Image(url)

a = Resize(512)(a)

print("durée: {:.2} min {:.4} sec".format((stop - start) // 60,(stop - start) % 60))

I got this error:
img should be PIL Image. Got <class 'IPython.core.display.Image

Is this error anything related to pytorch?:thinking:

The error was generated when using Resize transform from torchvision

I expect a pytorch function wouldn’t expect a IPython image, try changing it into Tensor.

It gives an error

TypeError                                 Traceback (most recent call last)
<ipython-input-79-f4dfad644a8d> in <module>()
      3 import torch
      4 start=time.time()
----> 5 a = torch.Tensor(IPython.display.Image(url))
      7 a = Resize(512)(a)

TypeError: new(): data must be a sequence (got Image)

I think it is preferred to use torch.tensor instead of using torch.Tensor directly. Tho i’m not familiar with IPython image, but there must some way that can convert it into 2/3 D array that can be further use to create tensors. PS: look at the Docs before asking :slight_smile: .

torchvision.transforms work currently with PIL.Images or tensors, so you would have to convert IPython.display.Image to a PIL.Image somehow to use the transformations.

1 Like

thx for correcting me

I see thank you for the info!