#OpenCV – How to convert to grayscale and show a single color an image 🖼️ using Python 🐍

#englishpost #codesample #effects

Hi !

Super quick post today with a cool scenario to support my TikTok videos in Spanish (I know 😀):

How to convert to grayscale an image and show a single color using python and opencv

Here is the output with an original photo from my office and a new image with this effect:

_ Disclaimer: I got this example in my notes from long time ago. I thik I got this code from a blog post or a public repository, however, I can’t find the original source. If you know it, please let me know so I can mention the author._

Sample code:

	# Copyright (c) 2022
	# Author : Bruno Capuano
	# Create Time : 2022 Feb
	# Change Log :
	# - Open a local image
	# - Convert an image to B&W, and resalt a specific color in RED
	#
	# The MIT License (MIT)
	#
	# Permission is hereby granted, free of charge, to any person obtaining a copy
	# of this software and associated documentation files (the "Software"), to deal
	# in the Software without restriction, including without limitation the rights
	# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
	# copies of the Software, and to permit persons to whom the Software is
	# furnished to do so, subject to the following conditions:
	#
	# The above copyright notice and this permission notice shall be included in
	# all copies or substantial portions of the Software.
	#
	# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
	# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
	# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
	# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
	# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
	# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
	# THE SOFTWARE.

	import numpy as np
	import cv2

	# open an image using opencv
	imgOriginal = cv2.imread('Office2.jpg')
	img = cv2.resize(imgOriginal, (324, 720))
	cv2.imshow('@ElBruno - Office', img)

	# get image height and width
	height, width, channels = img.shape

	#convert the BGR image to HSV colour space
	hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
	#obtain the grayscale image of the original image
	gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

	# set the bounds for the red hue
	lower_red = np.array([160,100,50])
	upper_red = np.array([180,255,255])

	# create a mask using the bounds set
	mask = cv2.inRange(hsv, lower_red, upper_red)
	# create an inverse of the mask
	mask_inv = cv2.bitwise_not(mask)
	# Filter only the red colour from the original image using the mask(foreground)
	res = cv2.bitwise_and(img, img, mask=mask)
	# Filter the regions containing colours other than red from the grayscale image(background)
	background = cv2.bitwise_and(gray, gray, mask = mask_inv)
	# convert the one channelled grayscale background to a three channelled image
	background = np.stack((background,)*3, axis=-1)
	# add the foreground and the background
	img_ca = cv2.add(res, background)

	cv2.imshow('@ElBruno - Captain America', img_ca)

	# save image using opencv
	cv2.imwrite('OfficeCaptainAmerica.jpg', img_ca)

	# key controller
	cv2.waitKey(0)
	cv2.destroyAllWindows()