Image Shape/Size | OpenCV vs Pillow | Python
Shape/size refers to the dimension of the image – width, height, and number of color channels. This tutorial will show you how to get the shape/size of an image in cv2 and PIL.
OpenCV
if cv2_img.ndim == 2:
height, width = cv2_img.shape
channels = 1
else:
height, width, channels = cv2_img.shapePillow
Note: It is hard to get the number of channels directly from a Pillow image object, the easier way is to first convert it to an OpenCV image (Numpy ndarray) and then get the shape.
width, height = pil_img.size
cv2_img = np.array(pil_img)
if cv2_img.ndim == 2:
channels = 1
else:
channels = cv2_img.shape[-1]Full Example
OpenCV
import cv2
# read image
cv2_img = cv2.imread("test_images/test1.jpg")
# get the image shape
if cv2_img.ndim == 2:
height, width = cv2_img.shape
channels = 1
else:
height, width, channels = cv2_img.shape
# print the shape
print(f"({height}, {width}, {channels})")Pillow
from PIL import Image
import numpy as np # remember to import numpy
# read image
pil_img = Image.open("test_images/test1.jpg")
# get the image shape
width, height = pil_img.size
cv2_img = np.array(pil_img)
if cv2_img.ndim == 2:
channels = 1
else:
channels = cv2_img.shape[-1]
# print the shape
print(f"({height}, {width}, {channels})")
