在 opencv numpy 中找到轮廓的边界点

Question

complete noob at open cv and numpy here. here is the image: here is my code:

import numpy as np
import cv2

im = cv2.imread('test.jpg')
imgray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
imgray = cv2.medianBlur(imgray, ksize=7)

ret, thresh = cv2.threshold(imgray, 0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)
_, contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)

print ("number of countours detected before filtering %d -> "%len(contours))
new = np.zeros(imgray.shape)

new = cv2.drawContours(im,contours,len(contours)-1,(0,0,255),18)

cv2.namedWindow('Display',cv2.WINDOW_NORMAL)
cv2.imshow('Display',new)
cv2.waitKey()

mask = np.zeros(imgray.shape,np.uint8)
cv2.drawContours(mask,[contours[len(contours)-1]],0,255,-1)
pixelpoints = cv2.findNonZero(mask)
cv2.imwrite("masked_image.jpg",mask)

print(len(pixelpoints))
print("type of pixelpoints is %s" %type(pixelpoints))

the length of pixelpoints is nearly 2 million since it contains all the point covered by the contours. But i only require the bordering point of that contour. How do I do it? I have tried several methods from opencv documentation but always errors with tuples and sorting operations. please...help?

I only require the border points of the contour:(

Answer 1

Is this what you mean by border points of a contour?

The white lines you see are points that I have marked out in white against the blue drawn contours. There's a little spot at the bottom right because I think its most likely that your black background isn't really black and so when I did thresholding and a floodfill to get this,

there was a tiny white speck at the same spot. But if you play around with the parameters and do a more proper thresholding and floodfill it shouldn't be an issue. In openCV's drawContours function, the cnts would contain lists of contours and each contour will contain an array of points. Each point is also of type numpy.ndarray. If you want to place all points of each contour in one place so it returns you a set of points of boundary points (like the white dots outline in the image above), you might want to append them all into a list. You can try this:

#rgb is brg instead
contoured=cv2.drawContours(black, cnts, -1, (255,0,0), 3)

#list of ALL points of ALL contours
all_pixels=[]

for i in range(0, len(cnts)):
    for j in range(0,len(cnts[i])):
        all_pixels.append(cnts[i][j])

When I tried to

print(len(all_pixels))

it returned me 2139 points.

Do this if you want to mark out the points for visualization purposes (eg like my white points):

#contouredC is a copy of the contoured image above
contouredC[x_val, y_val]=[255,255,255]

If you want less points, just use a step function when iterating through to draw the white points out. Something like this:

In python, for loops are slow so I think there's better ways of replacing the nested for loops with a np.where() function or something instead. Will update this if/when I figure it out. Also, this needs better thresholding and binarization techniques. Floodfill technique referenced from: Python 2.7: Area opening and closing binary image in Python not so accurate .

Hope it helps.