CODEWITHSUNDEEP
pythonopencvcolorspython-imaging-library
metalaureate
metalaureate

Reputation: 7732

Changing a color range in an image to a different color texture

I successfully changed a range of colors in an image to a single other color. I would like to make it more realistic by changing the colors to match the distribution of a swatch or, at the very least, a narrow band of random hues.

Some brown-looking grass

enter image description here

changed to very artificial green-looking grass

enter image description here

My code:

import cv2 as cv
import os
import numpy as np
import random

# Load the image and convert to HSV colourspace
image = cv.imread('brown_grass.jpg') 
hsv=cv.cvtColor(image,cv.COLOR_BGR2HSV)

# Define lower and uppper limits of what we call "brown"
brown_lo=np.array([18,0,0])
brown_hi=np.array([28,255,255])

# Mask image to only select browns
mask=cv.inRange(hsv,brown_lo,brown_hi)

# Change image to green where we found brown
image[mask>0]=(74,183,125) # how do change it to a nice realistic texture swatch?
cv.imwrite('result.jpg',image)

(Thanks to I want to change the colors in image with python from specific color range to another color for the first part of the solution)

Upvotes: 3

Views: 1223

Answers (1)

metalaureate
metalaureate

Reputation: 7732

Thanks to @MarkSetchell for the idea; the way to shade the masked area in a more natural way is to exploit the fact that brown and green are adjacent on the HSV color model, and add the delta between them, plus a boost for saturation and value.

hsv[mask>0]=hsv[mask>0]+(25,30,10) #  add an HSV vector
image2=cv.cvtColor(hsv,cv.COLOR_HSV2BGR) # convert image back into RGB color space
cv.imwrite('result.jpg', image2)

Exaggerating the effect here:

enter image description here

Upvotes: 3

Related Questions