In the next technique, the image can be changed to grayscale with the help of cv2.cvtColor() of OpenCV module which is used for colorspace change. Image Grayscale Conversion with OpenCV – cv2.cvtColor() Window_name='Grayscale Conversion OpenCV'Ĭv2.namedWindow(window_name, cv2.WINDOW_NORMAL)Ĥ. In this first approach, the image can be changed to grayscale while reading the image using cv2.imread() by passing the flag value as 0 along with the image file name. OpenCV is the most popular image processing package out there and there are a couple of ways to transform the image to grayscale. Image Grayscale Conversion with OpenCV – cv2.imread() The ‘L’ parameter is used to convert the image to grayscale.ģ. In this example, the image is read with Image.open() and then it is transformed with convert() by passing ‘L’ as the parameter. Pillow is another image processing library of Python which can be used to convert image to grayscale with its img.convert() function. Image Grayscale Conversion with Pillow (PIL) – convert() In the below example, the image is read using io.imread() and then it is converted to grayscale with color.rgb2gray() and finally it is displayed with io.imshow()Ģ. Any color image can be converted to grayscale with the help of color.rgb2gray() function of Skimage. Scikit Image or Skimage is a Python based open-source package for various image processing algorithms. Image Grayscale Conversion with Skimage (Scikit Image) – color.rgb2gray() Different Ways to Convert Image to Grayscale in Python Input Imageįor all the examples, the below dog image is going to be used as input.ġ. Each of the ways will be shown with examples for easy understanding. In this tutorial, we are going to show you multiple ways in which you can convert any image into Grayscale in Python by using different libraries like Skimage, Pillow, and OpenCV. Image Grayscale Conversion with OpenCV – cv2.cvtColor() Introduction 2 Different Ways to Convert Image to Grayscale in Python.
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