OpenCV cv2.imread()

Example of OpenCV cv2.imread() Method

In this section, we will see examples to understand Python's cv2.imread() method.

Reading color image using imread() Method

The default method used to read a color image is cv2.IMREAD_COLOR. The BGR (Blue-Green-Red) color format is read from the image.

import cv2
#reading image
image= cv2.imread('./cat.jpg')
#printing its shape
print('Image Dimensions :', image.shape)


#Displaying Image
cv2.imshow("Image", img)

cv2.waitKey(0) 
# Closing all windows

cv2.destroyAllWindows()

Output

Explanation

The (height, width, number_of_channels) tuple returned by img.shape. The image consists of three color channels with a 225-pixel height and 224-pixel width. The cv2.imshow() will display the image.

Reading image as greyscale using imread() Method

The input image can be used as color or grayscale images. If the flag argument is cv2.IMREAD GRAYSCALE reads the image in a grayscale image.

import cv2

 img = cv2.imread('./cat.jpg', cv2.IMREAD_GRAYSCALE)

 print('Image Dimensions:', img.shape)

#Displaying Image

cv2.imshow("Image", img)

cv2.waitKey(0) 

# Closing all windows

cv2.destroyAllWindows()

Output

Explanation

The (height, width, number_of_channels) tuple returned by img.shape. The image consists of a 225-pixel height and 224-pixel width. The cv2.imshow() will display the grey image.

Reading image with transparency channel using imread() Method

The cv2.IMREAD_UNCHANGED method is used to read an image with an alpha channel. The image is read in BGR color format.

import cv2

 img = cv2.imread('./cat.jpg', cv2.IMREAD_UNCHANGED)

 print('Image Dimensions :', img.shape)

#Displaying Image

cv2.imshow("Image", img)

cv2.waitKey(0) 

# Closing all windows

cv2.destroyAllWindows()

Output

Explanation

The (height, width, number_of_channels) tuple returned by img.shape. The image consists of a 225-pixel height and 224-pixel width. The cv2.imshow() will display the image.

OpenCV cv2.imread() and Color Channels

The  imread() function decodes the image into a matrix, with the color channels saved in the following order: blue, green, red, and transparency.

# Get blue channel
r1 = image[:,:,0]
# Get green channel
g1 = image[:,:,1] 
# Get red channel
b1 = image[:,:,2] 

Exception of OpenCV cv2.imread() Method

Some exceptions of OpenCV cv2.imread() Method are:-

• You may have a "File not found" error if the image file location provided is wrong, or the file doesn't exist. A try and except block can handle this and capture the FileNotFoundError.
   
• OpenCV may throw an exception if you try to load an image in an unsupported format. You can manage this by catching the cv2.error exception.
   
• A MemoryError may appear if you try to load a picture more significant than your available memory. You can handle this by catching the MemoryError.
   
• The cv2.imread() method will throw a "UnicodeError" exception if the supplied file path contains non-ASCII characters or is too long.
   
• If the supplied file is encrypted or password-protected, the cv2.imread() method will throw a "cv2.error" exception.

Frequently Asked Questions

What is the purpose of the flags parameter in cv2.imread()?

The flags parameter controls how the image should be loaded. It establishes the loaded image's color space and channel settings.  To describe how the picture should be loaded, you can use predefined flags like cv2.IMREAD_COLOR,  cv2.IMREAD_GRAYSCALE, and cv2.IMREAD_UNCHANGED.

How should exceptions be handled when using cv2.imread()?

Try and except blocks can handle errors thrown by cv2.imread(). This enables one to respond appropriately to failures, display illuminating notifications, and handle them graciously.

What are some common preprocessing steps after loading images with cv2.imread()?

Typical preprocessing procedures after loading images include scaling, normalization, noise reduction, and conversion to alternative color spaces as required for specific image processing or analytic jobs.

Conclusion

The OpenCV cv2.imread() method is essential for loading and reading pictures in various formats. Developers and researchers can efficiently load and modify images to support a variety of computer vision tasks by understanding their specifications, color channel options, and best practices.

We hope this blog has helped you to gain knowledge of OpenCV cv2.imread(). Do not stop learning! We recommend you read some of our related articles to OpenCV : 

• OpenCV Python Tutorial
• Introduction to OpenCV
• Image Read-Write-Display in OpenCV
   

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