- Opencv convert to grayscale python
- Working with Images — Feature Detection and Description
- Working with Images — Drawing Functions
- Working with Videos
- Applications and Projects
- OpenCV Projects
- Getting Started
- Working with Images — Getting Started
- Working with Images — Feature Detection and Description
- Working with Images — Drawing Functions
- Working with Videos
- Applications and Projects
- OpenCV Projects
- Opencv convert to grayscale python
- Python OpenCV: Converting an image to gray scale
- Introduction
- The code
- Testing the code
- Related Posts
Opencv convert to grayscale python
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Opencv convert to grayscale python
How to convert color image to grayscale in OpenCV
Welcome, In this tutorial we are going to see how to read a image as grayscale as well as we will convert a color image into a grayscale image using opencv and python, if you do not know how to read a image in opencv, do check out this post here.
So to convert a color image to a grayscale image in opencv, we can have two solution
- Convert image to grayscale with imread() function
- Convert image to grayscale using cvtColor() function
Let’s discover how to do it with above mentioned functions.
Method 1: Using imread() function
imread() function is used to read an image in OpenCV but there is one more parameter to be considerd, that is flag which decides the way image is read. There three flag defined in OpenCV..
So to convert the color image to grayscale we will be using cv2.imread(«image-name.png»,0) or you can also write cv2.IMREAD_GRAYSCALE in the place of 0 as it also denotes the same constant.
# Reading color image as grayscale
gray = cv2.imread(«color-img.png»,0)
# Showing grayscale image
cv2.imshow(«Grayscale Image», gray)
# waiting for key event
cv2.waitKey(0)
# destroying all windows
cv2.destroyAllWindows()
cvtColor() function in OpenCV is very helpful in converting color channels from one to another such as BRG to HSV or BRG to RGB. The same method can be used to convert BRG to GRAY by using the cv2.cvtColor(img,cv2.BGR2GRAY)
# Reading color image
img = cv2.imread(«color-img.png»)
# Converting color image to grayscale image
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Showing the converted image
cv2.imshow(«Converted Image»,gray)
# waiting for key event
cv2.waitKey(0)
# destroying all windows
cv2.destroyAllWindows()
Output
Python OpenCV: Converting an image to gray scale
In this tutorial we will check how to read an image and convert it to gray scale, using OpenCV and Python.
Introduction
In this tutorial we will check how to read an image and convert it to gray scale, using OpenCV and Python.
If you haven’t yet installed OpenCV, you can check here how to do it. You also need to install Numpy, which can be done with pip, the Python package manager, by sending the following command on the command line:
The code
To get started, we need to import the cv2 module, which will make available the functionalities needed to read the original image and to convert it to gray scale.
To read the original image, simply call the imread function of the cv2 module, passing as input the path to the image, as a string.
For simplicity, we are assuming the file exists and everything loads fine, so we will not be doing any error check. Nonetheless, for a robust code, you should handle these type of situations.
As additional note, which will be important for the conversion to gray scale, the imread function will have the channels stored in BGR (Blue, Green and Red) order by default [1].
image = cv2.imread('C:/Users/N/Desktop/Test.jpg') Next, we need to convert the image to gray scale. To do it, we need to call the cvtColor function, which allows to convert the image from a color space to another.
As first input, this function receives the original image. As second input, it receives the color space conversion code. Since we want to convert our original image from the BGR color space to gray, we use the code COLOR_BGR2GRAY.
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
Now, to display the images, we simply need to call the imshow function of the cv2 module. This function receives as first input a string with the name to assign to the window, and as second argument the image to show.
We will display both images so we can compare the converted image with the original one.
cv2.imshow('Original image',image) cv2.imshow('Gray image', gray) Finally, we will call the waitKey function, which will wait for a keyboard event. This function receives as input a delay, specified in milliseconds. Nonetheless, if we pass the value 0, then it will wait indefinitely until a key event occurs.
Finally, once the user pressed a key, we call the destroyAllWindows function, which will destroy the previously created windows.
cv2.waitKey(0) cv2.destroyAllWindows()
The final code can be seen below.
import cv2 image = cv2.imread('C:/Users/N/Desktop/Test.jpg') gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) cv2.imshow('Original image',image) cv2.imshow('Gray image', gray) cv2.waitKey(0) cv2.destroyAllWindows() Testing the code
To test the code, simply run the previous program on the Python environment of your choice. Don’t forget to pass to the imread function the correct path to the image you want to test. You should get an output similar to figure 1, which shows the original image and the final one, converted to gray scale.