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RPSGenerator.py
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RPSGenerator.py
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import cv2
import numpy as np
import random
def generateImageRPN(width, height):
tar = np.zeros((width, height, 3), dtype=np.uint8)
# Contains all posible ponderized values
# 1 -> 40 % Green values
# 2 -> 20 % Brown values
# 3 -> 10 % yellow values
# 4 -> 10 % shine green values
# 5 -> 20 % black values
ponderizedBagOptions = [1,1,1,1,2,2,3,4,5,5]
for indRow in range(height):
for indCol in range(width):
randPos = random.randint(0, 9)
choose = ponderizedBagOptions[randPos]
if choose == 1:
tar[indRow, indCol] = [0, 255, 0]
elif choose == 2:
tar[indRow, indCol] = [0, 102, 204]
elif choose == 3:
tar[indRow, indCol] = [102, 255, 255]
elif choose == 4:
tar[indRow, indCol] = [204, 255, 102]
else:
tar[indRow, indCol] = [0, 0, 0]
cv2.imshow("tar", tar)
cv2.waitKey(1)
return tar
image = cv2.imread("test.jpg")
image = cv2.resize(image, (256,256))
contoured = cv2.Canny(image, 100, 500)
# Invert mask in order to apply it only in not border areas
# This way, we can terrize the floor without losing information
contoured = cv2.bitwise_not(contoured)
cv2.imshow("contoured_n", contoured)
# Generate Random ponderated noise
RPSNoise = generateImageRPS(256,256)
# Meld maks with RPS Noise
masked = cv2.bitwise_and(RPSNoise, RPSNoise, mask=contoured)
cv2.imshow("masked", masked)
cv2.imwrite("imageRPN.jpg", masked)
cv2.waitKey(0)