Python - Visualizing image in different color spaces


OpenCV-Python is a library of Python bindings designed to solve computer vision problems. OpenCV-Python makes use of Numpy, which is a highly optimized library for numerical operations with a MATLAB-style syntax. All the OpenCV array structures are converted to and from Numpy arrays.

Example

# read image as RGB
# Importing cv2 and matplotlib module
import cv2
import matplotlib.pyplot as plt
# reads image as RGB
img = cv2.imread('download.png')
# shows the image
plt.imshow(img)
# read image as GrayScale
# Importing cv2 module
import cv2
# Reads image as gray scale
img = cv2.imread('download.png', 0)
# We can alternatively convert
# image by using cv2color
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Shows the image
cv2.imshow('image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()
# read image as YCrCb color space
# Import cv2 module
import cv2
# Reads the image
img = cv2.imread('download.png')
# Convert to YCrCb color space
img = cv2.cvtColor(img, cv2.COLOR_BGR2YCrCb)
# Shows the image
cv2.imshow('image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()
# read image as HSV color space
# Importing cv2 module
import cv2
# Reads the image
img = cv2.imread('download.png')
# Converts to HSV color space
img = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
# Shows the image
cv2.imshow('image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()
# Heat map of image
# Importing matplotlib and cv2
import matplotlib.pyplot as plt
import cv2
# reads the image
img = cv2.imread('download.png')
# plot heat map image
plt.imshow(img, cmap ='hot')
# Spectral map of image
# Importing matplotlib and cv2
import matplotlib.pyplot as plt
import cv2
img = cv2.imread('download.png')
plt.imshow(img, cmap ='nipy_spectral')

Updated on: 06-Aug-2020

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