text: """
  
  Hello world: Planet Kornia
  ==========================
  
  Welcome to Planet Kornia: a set of tutorial to learn about Computer Vision in PyTorch.
  
  This is the first tutorial showing how one can simply load an image and convert from BGR to RGB using Kornia.
  
  """
  
  import torch
  import kornia
  import cv2
  import numpy as np
  
  import matplotlib.pyplot as plt
  
  #############################
  # We use OpenCV to load an image to memory represented in a numpy.ndarray
  img_bgr: np.ndarray = cv2.imread('./data/arturito.jpeg')  # HxWxC
  
  #############################
  # The image is convert to a 4D torch tensor
  x_bgr: torch.tensor = kornia.image_to_tensor(img_bgr)  # 1xCxHxW
  
  #############################
  # Once with a torch tensor we can use any Kornia operator
  x_rgb: torch.tensor = kornia.bgr_to_rgb(x_bgr)  # 1xCxHxW
  
  #############################
  # Convert back to numpy to visualize
  img_rgb: np.ndarray = kornia.tensor_to_image(x_rgb.byte())  # HxWxC
  
  #############################
  # We use Matplotlib to visualize de results
  fig, axs = plt.subplots(1, 2, figsize=(32, 16))
  axs = axs.ravel()
  
  axs[0].axis('off')
  axs[0].imshow(img_bgr)
  
  axs[1].axis('off')
  axs[1].imshow(img_rgb)
  