python - cv2.drawContours 不会绘制填充轮廓

Question

我正在尝试使用 OpenCV 中的 cv2.drawContours 函数显示填充轮廓。我已经根据 Canny 检测得出的边缘图像开发了一个轮廓列表，并且正在为层次结构定义启用 RETR_EXTERNAL 找到轮廓。然而，我遇到了一个问题，尽管在 cv2.drawContours 命令中使用了 -1 标志来指示填充轮廓，但只有轮廓本身(即边缘)是显示。例如:

mask = np.zeros(rawimg.shape, np.uint8)
cv2.drawContours(mask, contours[246], -1, (0,255,255), -1)

导致仅显示轮廓 246 的轮廓。因为我只是检索外部轮廓，所以我不认为我只看到在每个边缘发现的内部和外部轮廓之间的差异，所以我对它为什么显示轮廓而不是填充感到有点困惑-1 标志会建议它应该这样做。

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编辑:完整代码包含在下面。问题在于该行: cv2.drawContours(mask, cnt, 2, (0,255,255), -1)虽然这是按照 Dan 建议的方式进行格式化，但结果如下图:

. cnt 是单个轮廓，因此它指的是轮廓中的单个点是有道理的。当行更改为:

cv2.drawContours(mask, cnt, -1, (0,255,255), -1)

轮廓像以前一样打印，但是轮廓仍然没有填充，因为命令末尾的 -1 标志表明应该填充。

测试图片:

import os
import cv2
import numpy as np
from matplotlib import pyplot as plt
import copy as cp

path = 'C:\\Users\\...deleted...\\Desktop\\testimage6.jpg'



#Determine largest contour in the image
def maxContour(contours):
    cnt_list = np.zeros(len(contours))
    for i in range(0,len(contours)):
        cnt_list[i] = cv2.contourArea(contours[i])

    max_value = np.amax(cnt_list)
    max_index = np.argmax(cnt_list)
    cnt = contours[max_index]

    return cnt, max_index


if os.path.isfile(path):
    # Import the raw image to a working location and save to an isolated     variable
    # Import the raw image to a working location and save to an isolated     variable
    img = cv2.imread(path)
    rawimg = cv2.imread(path)
    saveimg = cv2.imread(path)
    imgray = cv2.cvtColor(saveimg, cv2.COLOR_BGR2GRAY)
    saveimgray = cp.copy(imgray)

    f1 = plt.figure(1)
    f1.set_size_inches(8,10)
    plt.title('Original Image')
    plt.xticks([]), plt.yticks([])
    plt.imshow(rawimg, cmap='gray')
    plt.savefig('output1.jpg', dpi=300)
    cv2.imshow('Raw Image',rawimg)
    cv2.waitKey(0)
    cv2.destroyWindow('Raw Image')

    # Impose an opening function as a filter
    kernel = np.ones((3,3),np.uint8)    
    opening = cv2.morphologyEx(img, cv2.MORPH_OPEN, kernel)

    f2 = plt.figure(2)
    f1.set_size_inches(8,10)
    plt.title('Opened Image')
    plt.xticks([]), plt.yticks([])
    plt.imshow(opening, cmap='gray')
    plt.savefig('output2.jpg', dpi=300)
    cv2.imshow('Opened Image', opening)
    cv2.waitKey(0)
    cv2.destroyWindow('Opened Image')


    #Extract the edges from the filtered image
    edges = cv2.Canny(opening,10,100)
    cv2.imshow('Edges', edges)
    cv2.waitKey(0)
    cv2.destroyWindow('Edges')
    f3=plt.figure(3)
    f3.set_size_inches(16,8)
    plt.title('Edge Image')
    plt.xticks([]), plt.yticks([])
    plt.imshow(edges, cmap='gray')
    plt.savefig('output3.jpg', dpi=300)


    #Detect contours in the edge image
    image, contours, hierarchy = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
    cv2.drawContours(img, contours, -1, (0,255,255), 2)
    cv2.imshow('Contours Image', img)
    cv2.waitKey(0)
    cv2.destroyWindow('Contours Image')
    f4=plt.figure(4)
    f4.set_size_inches(16,8)
    plt.title('Contour Image')
    plt.xticks([]), plt.yticks([])
    plt.imshow(img)
    plt.savefig('output2.jpg', dpi=300)

    #Find maximum area contour    
    cnt, max_index = maxContour(contours)
    print(max_index)


    # Calculate contour-based statistics
    # TBD


    #Test of removing max contour
    #grayimg = cv2.cvtColor(rawimg, cv2.COLOR_BGR2GRAY)
    mask = np.zeros(rawimg.shape, np.uint8)
    cv2.drawContours(mask, cnt, 2, (0,255,255), -1) 
    #ret, mask = cv2.threshold(grayimg, 10, 255, cv2.THRESH_BINARY)
    mask_inv = cv2.bitwise_not(mask)
    cv2.imshow('Mask Image', mask)
    cv2.waitKey(0)
    cv2.destroyWindow('Mask Image')
    cv2.imshow('Mask Image', mask_inv)
    cv2.waitKey(0)
    cv2.destroyWindow('Mask Image')

    #Fit ellipse to contour and calculate ellipse statistics
    (x,y), (w,h), angle = cv2.fitEllipse(cnt)    
    rect = cv2.minAreaRect(cnt)
    box = cv2.boxPoints(rect)
    box = np.int0(box)
    x = np.int0(x)
    y = np.int0(y)
    w = np.int0(0.5*w)
    h = np.int0(0.5*h)


    #output2 = cv2.ellipse(img, center, dim, angle, 0, 360, (255,0,0), 12)
    output2 = cv2.ellipse(img, (x,y), (w,h), angle, 0, 360, (255,0,0), 2)
    output3 = cv2.drawContours(output2, [box], 0, (0,255,0), 2)
    cv2.imshow('Ellipse Image',output2)
    cv2.waitKey(0)
    cv2.destroyWindow('Ellipse Image')



else:
    print('file does not exist')`

Answer 1

function drawContours takes a list of contours as input .尝试:

cv2.drawContours(
    image=mask,
    contours=[cnt],
    contourIdx=-1,
    color=(0,255,255),
    thickness=cv2.FILLED)

代替:cv2.drawContours(mask, cnt, -1, (0,255,255), -1)。