cv2.drawContours不会绘制填充轮廓

我正在尝试使用显示填充轮廓cv2.drawContoursOpenCV 中的函数。我已经从边缘图像中开发了一个轮廓列表，该边缘图像源自Canny检测，并找到轮廓RETR_EXTERNAL为层次结构定义启用。然而我遇到了一个问题，尽管使用-1标志在cv2.drawContours命令指示填充轮廓，仅显示轮廓本身（即边缘）。例如：

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

结果仅显示轮廓246的轮廓。由于我只是检索外部轮廓，所以我认为我并没有看到每个边缘处发现的内部轮廓和外部轮廓之间的差异，所以我有点困惑为什么它显示轮廓，但没有填充为这-1flag 会建议它应该。

EDIT:完整的代码如下。问题在于该行： cv2.drawContours(掩码, cnt, 2, (0,255,255), -1) 虽然这是按照 Dan 建议的方式格式化的，但它会产生以下图像：

. cnt is a single contour, so this makes sense that it would be referring to a single point in the contour. When the line is changed to:

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 标志表明它应该是这样。

测试图像：

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')`

The 功能drawContours需要一个list轮廓作为输入. Try:

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).