Hi !
Super quick post today with a cool scenario to support my TikTok videos in Spanish (I know π):
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 canβt 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() |
Happy coding!
Greetings
El Bruno
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