import cv2
import numpy as np
import sys
import time
import os
cap = cv2.VideoCapture(0)
while( cap.isOpened() ) :
ret,img = cap.read()
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray,(5,5),0)
ret,thresh1 = cv2.threshold(blur,70,255,cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)
contours, hierarchy = `enter code here`
cv2.findContours(thresh1,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
drawing = np.zeros(img.shape,np.uint8)
max_area=0
enter code here
for i in range(len(contours)):
cnt=contours[i]
area = cv2.contourArea(cnt)
if(area>max_area):
max_area=area
ci=i
cnt=contours[ci]
hull = cv2.convexHull(cnt)
moments = cv2.moments(cnt)
if moments['m00']!=0:
cx = int(moments['m10']/moments['m00']) # cx = M10/M00
cy = int(moments['m01']/moments['m00']) # cy = M01/M00
centr=(cx,cy)
cv2.circle(img,centr,5,[0,0,255],2)
cv2.drawContours(drawing,[cnt],0,(0,255,0),2)
cv2.drawContours(drawing,[hull],0,(0,0,255),2)
cnt = cv2.approxPolyDP(cnt,0.01*cv2.arcLength(cnt,True),True)
hull = cv2.convexHull(cnt,returnPoints = False)
if(1):
defects = cv2.convexityDefects(cnt,hull)
mind=0
maxd=0
i=0
for i in range(defects.shape):
s,e,f,d = defects[i,0]
start = tuple(cnt[s][0])
end = tuple(cnt[e][0])
far = tuple(cnt[f][0])
cv2.line(img,start,end,[0,255,0],2)
cv2.circle(img,far,5,[0,0,255],-1)
print(i)
cv2.imshow('output',drawing)
cv2.imshow('input',img)
k = cv2.waitKey(10)
if k == 27:
break
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