create mask with filled color using opencv-CodePudding

I have an input image where I have drawn the green boundaries which I need to mask. I am able to identify the boundary, but my mask is all black with baground is black. how can I fill the boundary region with different color. May be keep the background white and mask region as black

Input image

im = cv2.imread(imagePath)
plt.imshow(im)
#color boundaries [B, G, R]
lower = np.array([0,120,0])
upper = np.array([200,255,100])

# threshold on green color
thresh = cv2.inRange(im, lower, upper)
plt.imshow(thresh)
# get largest contour
contours = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
contours = contours[0] if len(contours) == 2 else contours[1]
big_contour = max(contours, key=cv2.contourArea)
x,y,w,h = cv2.boundingRect(big_contour)

# draw filled contour on black background
mask = np.zeros_like(im)
cv2.drawContours(mask, [big_contour], 0, (255,255,255), cv2.FILLED)
plt.imshow(mask)
# apply mask to input image
new_image = cv2.bitwise_and(im, mask)

Generated Output

I am expecting the green countor will be filled with some different color. May be white background with black countour. or transparent background

CodePudding user response：

To fill the contours drawn on the mask you should use the opencv's fillPoly function :

im = cv2.imread(imagePath)
plt.imshow(im)
#color boundaries [B, G, R]
lower = np.array([0,120,0])
upper = np.array([200,255,100])

# threshold on green color
thresh = cv2.inRange(im, lower, upper)
plt.imshow(thresh)
# get largest contour
contours = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
contours = contours[0] if len(contours) == 2 else contours[1]
big_contour = max(contours, key=cv2.contourArea)
x,y,w,h = cv2.boundingRect(big_contour)

# draw filled contour on black background
mask = np.zeros_like(im)
# cv2.drawContours(mask, [big_contour], 0, (255,255,255), cv2.FILLED)
mask = cv2.fillPoly(mask, pts =[big_contours], color=(255,255,255)) # fill the polygon
plt.imshow(mask)
# apply mask to input image
new_image = cv2.bitwise_and(im, mask)

CodePudding user response：

This code generated canny image and then generates contours, then it generates mask and after this all it shows the output as the mixture of original and the mask image: import cv2 import numpy as np

image = cv2.imread('image.png')
cv2.waitKey(0)

# Grayscale
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# Find Canny edges
edged = cv2.Canny(gray, 30, 200)
cv2.waitKey(0)

# Finding Contours
# Use a copy of the image e.g. edged.copy()
# since findContours alters the image
contours, hierarchy = cv2.findContours(edged,
    cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)

cv2.imshow('Canny Edges After Contouring', edged)


print("Number of Contours found = "   str(len(contours)))

# Draw all contours
# -1 signifies drawing all contours
cv2.drawContours(image, contours, -1, (0, 0, 255), 2)

mask = np.zeros_like(image)
# cv2.drawContours(mask, [big_contour], 0, (255,255,255), cv2.FILLED)
cv2.fillPoly(mask, pts =contours, color=(0,255,0)) # fill the polygon

new_image = cv2.bitwise_and(image, mask)

while True:
    cv2.imshow('Contours', image)
    cv2.imshow('mask', mask)
    cv2.imshow('new_image', new_image)
    cv2.waitKey(1)
# cv2.destroyAllWindows()

Original image:

Edged image:

contours found:

mask:

Final image: