How to access image properties in OpenCV using Python?

OpenCV is one of the most popular computer vision libraries that has been used for various image editing and processing tasks. In this article, we will be discussing how to access image properties in OpenCV using Python. This will include learning what image properties are, how to access them, and viewing some sample code to help us understand the process.

Understanding Image Properties in OpenCV

Before diving into the process, we need to understand what image properties are in OpenCV. Image properties refer to the basic information about an image, such as size, type, and color space. OpenCV has a set of functions that can be used to access these properties, and by doing so, we can perform different image processing tasks.

Accessing Image Properties in OpenCV

To access image properties in OpenCV, we use the cv2.imread() function to load the image and then use the cv2.imshow() function to display the image. Once we have loaded the image, we can access its properties using the following functions:

Image Size

The size of an image can be accessed using the shape function in OpenCV. The shape function returns a tuple, where the first value is the height of the image, and the second value is the width of the image. Here’s an example code snippet that demonstrates how to access the size of an image:

import cv2

image = cv2.imread('image.jpg')
height, width = image.shape[:2]

print("Image size: {} x {}".format(width, height))

Image Type

The type of an image refers to the bit depth and number of channels in the image. The image type can be accessed using the dtype function in OpenCV. Here’s an example code snippet that demonstrates how to access the type of an image:

import cv2

image = cv2.imread('image.jpg')
image_type = image.dtype

print("Image type: {}".format(image_type))

Image Color Space

The color space of an image refers to the way in which color information is represented in the image. The color space can be accessed using the cvtColor function in OpenCV. Here’s an example code snippet that demonstrates how to access the color space of an image:

import cv2

image = cv2.imread('image.jpg')
color_space = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)

print("Image color space: {}".format(color_space))

Sample Code

Now that we have demonstrated how to access different image properties, let’s take a look at some sample code that uses these functions. In this code snippet, we will load an image, access its properties, and then display the image using OpenCV:

import cv2

image = cv2.imread('image.jpg')

# Access image size
height, width = image.shape[:2]

# Access image type
image_type = image.dtype

# Access image color space
color_space = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)

print("Image size: {} x {}".format(width,height))
print("Image type: {}".format(image_type))
print("Image color space: {}".format(color_space))

# Display the image
cv2.imshow('Image', image)
cv2.waitKey(0)
cv2.destroyAllWindows()

Conclusion

In this article, we have learned how to access image properties in OpenCV using Python. We have learned that image properties refer to the basic information about an image, such as size, type, and color space. We have demonstrated how to access these properties using the shape, dtype, and cvtColor functions in OpenCV. Finally, we have viewed some sample code that uses these functions to load an image, access its properties, and display the image using OpenCV.