如何在图像边缘填充圆形轮廓？

Question

In the image above, I want to eventually be able to fill in the contours of the colored circles. Unfortunately, the yellow circle on the bottom is right at the edge of the image, so cv2.findContours() doesn't work:

_, green_contours, _ = cv2.findContours(green_seg, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

Does anyone know how I can somehow fill in the yellow circle contour even though it's at the edge of the image? Since it's at the edge of the image, the pixel value on the bottom edge of the image doesn't complete the circle, isn't valued at 255, if that makes sense.

I looked online and some people say it's possible to draw a big box around the image and then do the contours, but if I do that, then opencv only draws the big contour around the entire image and not the circle.

Any other thoughts would be greatly appreciated!

EDIT: The image I show above is just one case I'm considering. I'm trying to think how I can make this general enough such that for any contour that is at the edge of the border, I can still fill in the contour with cv2.drawContour().

Answer 1

If you have (more or less) convex polygons, you actually CAN use cv2.findContours . Having the contours, try to find the center of mass, eg using cv2.moments , and then use this as the seed point in cv2.floodFill .

Please see the following code snippet. I assume, you can identify your polygons by color. Also, instead of some advanced finding of the center of mass, I just used the center point of the bounding rectangle of each contour. Maybe, that's also sufficient for your use case!?

import cv2
import numpy as np

# Set up test image
colors = [(0, 255, 0), (0, 0, 255)]
input = np.zeros((400, 400, 3), np.uint8)
cv2.circle(input, (100, 100), 50, colors[0], 10)
cv2.circle(input, (150, 350), 75, colors[1], 10)
output = input.copy()

# Iterate all colors...
for i, c in enumerate(colors):

    # Mask color
    img = np.all(output == c, axis=2).astype(np.uint8) * 255

    # Find contours with respect to OpenCV version
    cnts = cv2.findContours(img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
    cnts = cnts[0] if len(cnts) == 2 else cnts[1]

    # Get bounding rectangles; derive seed points for flood filling; flood fill
    rects = [cv2.boundingRect(c) for c in cnts]
    seeds = [(np.int32(r[0] + r[2] / 2), np.int32(r[1] + r[3] / 2)) for r in rects]
    [cv2.floodFill(output, mask=None, seedPoint=s, newVal=c) for s in seeds]

cv2.imshow('input', input)
cv2.imshow('output', output)
cv2.waitKey(0)
cv2.destroyAllWindows()

That's the input:

And, that's the output:

Hope that helps!

----------------------------------------
System information
----------------------------------------
Platform:    Windows-10-10.0.16299-SP0
Python:      3.8.1
NumPy:       1.18.1
OpenCV:      4.1.2
----------------------------------------

Answer 2

A simple way, perhaps not so precise, is to compute the convex hull for each contour and draw the interior with a fill color:

import cv2
import numpy as np
import sys

# load input image from the cmd-line
img = cv2.imread('test_images/partial_contour.png')
if (img is None):
    print('!!! Failed imread')
    sys.exit(-1)

output_img = img.copy()

# isolate just the colored drawings
ret, thres_bgr = cv2.threshold(img, 0, 255, cv2.THRESH_BINARY)
thres_bgr[np.where((thres_bgr == [255,255,255]).all(axis=2))] = [0,0,0] # replace white pixels for black

# convert from 3-channels (BGR) to a single channel (gray)
gray_img = cv2.cvtColor(thres_bgr, cv2.COLOR_BGR2GRAY)

# this loop processes all the contours found in the image
contours, hierarchy = cv2.findContours(gray_img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
for contourIdx, cnt in enumerate(contours):
    # compute a convex hull
    hull = cv2.convexHull(cnt)

    # fill the inside with red
    cv2.fillPoly(output_img, pts=[hull], color=(0, 0, 255))

cv2.imshow('output_img', output_img)
cv2.imwrite('fill_partial_cnt_output.png', output_img)
cv2.waitKey(0)