如何解决opencv无法提取图像中的最大轮廓
考虑这张图片:
我只想提取代表图像中最大轮廓的数字,但opencv总是显示原始图像和小于数字的小轮廓。所以当我运行这个函数时
def contouTreat(image):
gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray,255,cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]
cnts = cv2.findContours(thresh,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
(cnts,_) = contours.sort_contours(cnts,method="left-to-right")
cv2.drawContours(image,cnts,-1,(0,0),3)
#cv2_imshow(image)
ROI_number = 0
arr=[]
v=True
for c in cnts:
area = cv2.contourArea(c)
if area != image.shape[1]*image.shape[0]:
x,y,w,h = cv2.boundingRect(c)
#if minc != x:
x,h = cv2.boundingRect(c)
#if area < 800 and area > 200:
#if area < 1620 and h>58 and w <50:
#if h>(70*image.shape[1])/100 and w>(60*image.shape[0])/100 :
if v:
ROI = image[y:y+h,x:x+w]
print(h)
print(w)
cv2_imshow(ROI)
return None
image=cv2.imread("/content/téléchargement (2).png")
contouTreat(image)
我得到了这个结果:
解决方法
您在同一幅图像上绘制轮廓,因此您通过绘制两个轮廓获得更大的 ROI。
建议的解决方案:
在填充零的临时图像上绘制每个轮廓,并从临时图像中裁剪 ROI。
-
创建用零填充的临时图像:
tmp_im = np.zeros_like(image)
-
绘制一个填充白色的轮廓,并将其用作蒙版:
cv2.drawContours(tmp_im,[c],(255,255,255),cv2.FILLED) # Draw white contour on black image tmp_im = cv2.bitwise_and(image,tmp_im) # Apply bitwise with `image` - required in case there are black regions inside the contour.
-
在轮廓周围画绿线(可能不需要):
cv2.drawContours(tmp_im,-1,(0,0),3) # Draw green line around the contour
-
裁剪投资回报率:
ROI = tmp_im[y:y + h,x:x + w]
完整的代码示例:
import numpy as np
import cv2
from imutils import contours
def contouTreat(image):
gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray,cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]
cnts = cv2.findContours(thresh,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
(cnts,_) = contours.sort_contours(cnts,method="left-to-right")
cv2.drawContours(image,cnts,3)
#cv2_imshow(image)
ROI_number = 0
arr = []
v = True
for c in cnts:
area = cv2.contourArea(c)
if area != image.shape[1] * image.shape[0]:
x,y,w,h = cv2.boundingRect(c)
if v:
tmp_im = np.zeros_like(image)
cv2.drawContours(tmp_im,cv2.FILLED) # Draw white contour on black image
tmp_im = cv2.bitwise_and(image,tmp_im) # Apply bitwise with `image` - required in case there are black regions inside the contour.
cv2.drawContours(tmp_im,3) # Draw green line around the contour
ROI = tmp_im[y:y + h,x:x + w]
print(h)
print(w)
cv2.imshow('ROI' + str(ROI_number),ROI)
ROI_number += 1
return None
image = cv2.imread("telechargement.png")
contouTreat(image)
cv2.waitKey()
cv2.destroyAllWindows()
结果:
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