For this recipe, you need to perform the following steps:
- You can easily read an image with the cv2.imread function, which takes path to image and optional flags:
import argparse
import cv2
parser = argparse.ArgumentParser()
parser.add_argument('--path', default='../data/Lena.png', help='Image path.')
params = parser.parse_args()
img = cv2.imread(params.path)
- Sometimes it's useful to check whether the image was successfully loaded or not:
assert img is not None # check if the image was successfully loaded print('read {}'.format(params.path)) print('shape:', img.shape) print('dtype:', img.dtype)
- Load the image and convert it to grayscale, even if it had many color channels originally:
img = cv2.imread(params.path, cv2.IMREAD_GRAYSCALE) ...