Converting an image from colour to grayscale using OpenCV (2024)

FAQs

How to convert color image to grayscale in OpenCV? ›

To convert an RGB image to grayscale using OpenCV and Python, you can use the cvtColor() function from the OpenCV library. Here is an example code that reads an RGB image, converts it to grayscale, and then displays the grayscale image: pythonCopy codeimport cv2 # Read the RGB image img_rgb = cv2.

Method 1: Using the cv2.

Import the OpenCV and read the original image using imread() than convert to grayscale using cv2. cvtcolor() function. destroyAllWindows() function allows users to destroy or close all windows at any time after exiting the script.

Method 1: Using imread() function

So to convert the color image to grayscale we will be usingcv2. imread("image-name. png",0)or you can also writecv2. IMREAD_GRAYSCALEin the place of 0 as it also denotes the same constant.

The rgb2gray function converts RGB images to grayscale by eliminating the hue and saturation information while retaining the luminance. If you have Parallel Computing Toolbox™ installed, rgb2gray can perform this conversion on a GPU.

Color() method to get Grayscale images. You can also simply apply the . Color() method with a value of 0 which will turn down all the RGB colors and turn in a grayscale image. The results you get with this method will be visually identical to converting the image to L or LA modes.

Write ndarray as an image file with cv2.

If 2D ndarray of row(height) x column(width) is specified as the argument of cv2. imwrite() , it is saved as a grayscale image file. If you want to save a color image (3D ndarray ) as a grayscale image file, convert it to grayscale with cv2. cvtColor() and cv2.

Changing Color-space

For color conversion, we use the function cv. cvtColor(input_image, flag) where flag determines the type of conversion. For HSV, hue range is [0,179], saturation range is [0,255], and value range is [0,255]. Different software use different scales.

Why do we convert images to grayscale? ›

It helps in simplifying algorithms and as well eliminates the complexities related to computational requirements. It makes room for easier learning for those who are new to image processing. This is because grayscale compressors an image to its barest minimum pixel. It enhances easy visualisation.

Write ndarray as an image file with cv2.

If 2D ndarray of row(height) x column(width) is specified as the argument of cv2. imwrite() , it is saved as a grayscale image file. If you want to save a color image (3D ndarray ) as a grayscale image file, convert it to grayscale with cv2. cvtColor() and cv2.