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import cv2 import numpy as np image = cv2.imread('abbey_road.jpg',-1) paper = cv2.resize(image,(500,500)) ret, thresh_gray = cv2.threshold(cv2.cvtColor(paper, cv2.COLOR_BGR2GRAY), 200, 255, cv2.THRESH_BINARY) contours, hier = cv2.findContours(thresh_gray, cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE) for c in contours: print(c) rect = cv2.minAreaRect(c) box = cv2.boxPoints(rect) # convert all coordinates floating point values to int box = np.int0(box) # draw a green 'nghien' rectangle cv2.drawContours(paper, [box], 0, (0, 255, 0),1)

cv2.imshow('paper', paper)

cv2.imwrite('paper.jpg',paper) cv2.waitKey(0)

I tried the above code for zebra detection,but it end up with detecting all thewhite boxes but not the whole are.Is there any way to solve this?

.

import cv2
import numpy as np
image = cv2.imread('abbey_road.jpg',-1)
paper = cv2.resize(image,(500,500))
ret, thresh_gray = cv2.threshold(cv2.cvtColor(paper, cv2.COLOR_BGR2GRAY),
                        200, 255, cv2.THRESH_BINARY)
contours, hier = cv2.findContours(thresh_gray, cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)
for c in contours:
    print(c)
    rect = cv2.minAreaRect(c)
    box = cv2.boxPoints(rect)
    # convert all coordinates floating point values to int
    box = np.int0(box)
    # draw a green 'nghien' rectangle
    cv2.drawContours(paper, [box], 0, (0, 255, 0),1)
0),1)
 cv2.imshow('paper', paper)
 
cv2.imshow('paper', paper)
 
cv2.imwrite('paper.jpg',paper)
cv2.waitKey(0)cv2.waitKey(0)![image description](/upfiles/1581660638287198.jpg)

I tried the above code for zebra detection,but it end up with detecting all thewhite boxes but not the whole are.Is there any way to solve this?

.

import cv2
import numpy as np
image = cv2.imread('abbey_road.jpg',-1)
paper = cv2.resize(image,(500,500))
ret, thresh_gray = cv2.threshold(cv2.cvtColor(paper, cv2.COLOR_BGR2GRAY),
                        200, 255, cv2.THRESH_BINARY)
contours, hier = cv2.findContours(thresh_gray,  cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)
for c in contours:
    print(c)
    rect = cv2.minAreaRect(c)
    box = cv2.boxPoints(rect)
    # convert all coordinates floating point values to int
    box = np.int0(box)
    # draw a green 'nghien' rectangle
    cv2.drawContours(paper, [box], 0, (0, 255, 0),1)
0),1)
  
cv2.imshow('paper', paper)
paper)  
cv2.imwrite('paper.jpg',paper)
cv2.waitKey(0)![image description](/upfiles/1581660638287198.jpg)

I tried the above code for zebra detection,but it end up with detecting all thewhite boxes but not the whole are.Is there any way to solve this?

import cv2 import numpy as np image = cv2.imread('abbey_road.jpg',-1) paper = cv2.resize(image,(500,500)) ret, thresh_gray = cv2.threshold(cv2.cvtColor(paper, cv2.COLOR_BGR2GRAY), 200, 255, cv2.THRESH_BINARY) contours, hier = cv2.findContours(thresh_gray, cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE) for c in contours: print(c) rect = cv2.minAreaRect(c) box = cv2.boxPoints(rect) # convert all coordinates floating point values to int box = np.int0(box) # draw a green 'nghien' rectangle cv2.drawContours(paper, [box], 0, (0, 255, 0),1)

cv2.imshow('paper', paper)
 
paper)

cv2.imwrite('paper.jpg',paper)
cv2.waitKey(0)cv2.waitKey(0)

Code:

import cv2
 import numpy as np
 image = cv2.imread('abbey_road.jpg',-1)
 paper = cv2.resize(image,(500,500))
 ret, thresh_gray = cv2.threshold(cv2.cvtColor(paper, cv2.COLOR_BGR2GRAY),
                         200, 255, cv2.THRESH_BINARY)
 contours, hier = cv2.findContours(thresh_gray,  cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)
 for c in contours:
     print(c)
     rect = cv2.minAreaRect(c)
     box = cv2.boxPoints(rect)
     # convert all coordinates floating point values to int
     box = np.int0(box)
     # draw a green 'nghien' rectangle
     cv2.drawContours(paper, [box], 0, (0, 255, 0),1)
0),1)
  
cv2.imshow('paper', paper)

cv2.imwrite('paper.jpg',paper)
cv2.waitKey(0)
 
 
I tried the above code for zebra detection,but it end up with detecting all thewhite boxes but not the whole are.Is there any way to solve this?