 which we can visualize:   Copied >>> import matplotlib.pyplot as plt

>>> fig, axs = plt.subplots(1, 4, figsize=(16, 4))
>>> for i, image in enumerate(dataset[:4]["image"]):
...     axs[i].imshow(image)
...     axs[i].set_axis_off()
>>> fig.show()  The images are all different sizes though, so you’ll need to preprocess them first: Resize changes the image size to the one defined in config.image_size. RandomHorizontalFlip augments the dataset b