无法找到并绘制最大轮廓

Question

我想在此框架上找到并绘制最大轮廓。

我可以找到轮廓。但是当我尝试找到最大轮廓时，它会在框架上显示一个小的轮廓作为最大框架。当我绘制轮廓时，我可以清楚地看到物体周围有很大的轮廓

这是我的尝试：

import cv2
import numpy as np
#capture.release()
cv2.destroyAllWindows()
capture = cv2.VideoCapture(1)
panel = np.zeros([100, 700], np.uint8)
cv2.namedWindow('panel')
def nothing(x):
    pass

#some code about trackbar and panel here

while(True):

    ret, frame = capture.read()

    #some code about trackbar and panel here      
    roi = frame[s_r: e_r, s_c: e_c]
    roi =  cv2.GaussianBlur(roi, (5, 5), 0) #sigma = 0
    hsv = cv2.cvtColor( roi, cv2.COLOR_RGB2HSV)    

    #some code about trackbar and panel here


    mask = cv2.inRange(hsv, lower_green, upper_green)
    mask_inv = cv2.bitwise_not(mask)

    bg = cv2.bitwise_and( roi,  roi, mask=mask)
    fg = cv2.bitwise_and( roi,  roi, mask=mask_inv)
    gray = cv2.cvtColor(fg, cv2.COLOR_BGR2GRAY)
    contours, hierarchy = cv2.findContours(gray,cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)

    max_area = 0
    for contour in contours:
        area = cv2.contourArea(contour)
        if area > max_area:
            area = max_area
            x,y,w,h = cv2.boundingRect(contour)

    cv2.rectangle(fg,(x,y),(x+w,y+h),(0,255,0),2)

    cv2.imshow('bg', bg)
    cv2.imshow('fg', fg)
    cv2.imshow('panel', panel)

    if cv2.waitKey(30) == 27: #siradaki frame'e gecmeden once 30 ms bekle
        break

capture.release()
cv2.destroyAllWindows()

Answer 1

Python / OpenCV解决方案：

在轮廓上循环时，只需自己找到该轮廓的最大面积和相应的boundingRect。

max_area = 0
for contour in contours:
   area = cv2.contourArea(contour)
   if area > max_area:
      area = max_area
      x,y,w,h = cv2.boundingRect(contour)

或者，只要获得与您的图像有关的外轮廓（大概只有一个）即可。 （将来，请显示您的输入图像）。

contours, hierarchy = cv2.findContours(gray, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

Answer 2

此方法似乎在Python / OpenCV中对我有用。我做了一个简单的门槛。然后使用形态学平滑并填充一些。然后我得到轮廓并过滤区域。然后我在图像上绘制轮廓。请注意，它对形态核的大小很敏感，并且至少必须为10或11。但是，如果将其设置得太大，它将改变区域的形状。

输入：

import cv2
import numpy as np

# load image
img = cv2.imread("green_and_red_regions.png")

# convert to gray
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# threshold image
thresh = cv2.threshold(gray,4,255,0)[1]

# apply morphology open to smooth the outline
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (11,11))
thresh = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel)
thresh = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel)

# find contours
cntrs = cv2.findContours(thresh, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
cntrs = cntrs[0] if len(cntrs) == 2 else cntrs[1]

# Contour filtering to get largest area
area_thresh = 0
for c in cntrs:
    area = cv2.contourArea(c)
    if area > area_thresh:
        area = area_thresh
        big_contour = c

# draw the contour on a copy of the input image
results = img.copy()
cv2.drawContours(results,[big_contour],0,(0,0,255),2)


# write result to disk
cv2.imwrite("greengreen_and_red_regions_threshold.png", thresh)
cv2.imwrite("green_and_red_regions_big_contour.png", results)

cv2.imshow("THRESH", thresh)
cv2.imshow("RESULTS", results)
cv2.waitKey(0)
cv2.destroyAllWindows()

阈值和平滑图像：

在输入上绘制的轮廓轮廓：