Note
Click here to download the full example code
Hello world: Planet KorniaΒΆ
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)

Total running time of the script: ( 0 minutes 1.225 seconds)