import cv2
import numpy as np
 
def generate_poly(image, n, area_thresh):
 """
 随机生成凸包
 :param image: 二值图
 :param n: 顶点个数
 :param area_thresh: 删除小于此面积阈值的凸包
 :return: 凸包图
 """
 row, col = np.where(image[:, :, 0] == 255) # 行,列
 point_set = np.zeros((n, 1, 2), dtype=int)
 for j in range(n):
  index = np.random.randint(0, len(row))
  point_set[j, 0, 0] = col[index]
  point_set[j, 0, 1] = row[index]
 hull = []
 hull.append(cv2.convexHull(point_set, False))
 drawing_board = np.zeros(image.shape, dtype=np.uint8)
 cv2.drawContours(drawing_board, hull, -1, (255, 255, 255), -1)
 cv2.namedWindow('drawing_board', 0), cv2.imshow('drawing_board', drawing_board), cv2.waitKey()
 
 # 如果生成面积过小，重新生成
 if cv2.contourArea(hull[0]) < area_thresh:
  drawing_board = generate_poly(image, n, area_thresh)
 
 # 如果生成洞，重新生成
 is_hole = image[drawing_board == 255] == 255
 if is_hole.all() == True: # 洞，则drawing_board所有为255的地方，image也是255，all()即为所有位置
  drawing_board = generate_poly(image, n, area_thresh)
 return drawing_board
 
 
img = np.zeros((256, 256, 3), np.uint8)
cv2.circle(img, (100, 100), 50, (255, 255, 255), -1)
cv2.namedWindow('img', 0), cv2.imshow('img', img), cv2.waitKey()
 
img_hull = generate_poly(img, 8, 100)
cv2.namedWindow('img_hull', 0), cv2.imshow('img_hull', img_hull), cv2.waitKey()

import cv2
import numpy as np
 
img = cv2.imread('img7.png',0)
ret,thresh = cv2.threshold(img,127,255,0)
im2,contours,hierarchy = cv2.findContours(thresh, 1, 2)
 
cnt = contours[0]
M = cv2.moments(cnt)
print( M )

import cv2
import numpy as np
 
img = cv2.imread('img8.png')
cv2.imshow('src',img)
imgray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(imgray, 127, 255, 0)
im2, contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
cnt = contours[1]
 
epsilon = 0.1*cv2.arcLength(cnt,True)
approx = cv2.approxPolyDP(cnt,epsilon,True)
cv2.polylines(img, [approx], True, (0, 0, 255), 2)
 
cv2.imshow('show',img)
cv2.waitKey()

import cv2
import numpy as np
 
img = cv2.imread('img8.png')
 
imgray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(imgray, 127, 255, 0)
im2, contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
cnt = contours[1]
 
hull = cv2.convexHull(cnt)

array([[[192, 135]],
  [[ 9, 135]],
  [[ 9, 12]],
  [[192, 12]]], dtype=int32)

array([[129],
  [ 67],
  [ 0],
  [142]], dtype=int32)

import cv2
import numpy as np
 
img = cv2.imread('img7.png')
 
imgray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(imgray, 127, 255, 0)
im2, contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
cnt = contours[0]
 
x,y,w,h = cv2.boundingRect(cnt)
cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)
 
cv2.imshow('show',img)
cv2.waitKey()

rect = cv2.minAreaRect(cnt)
box = cv2.boxPoints(rect)
box = np.int0(box)
cv2.drawContours(img,[box],0,(0,0,255),2)

(x,y),radius = cv2.minEnclosingCircle(cnt)
center = (int(x),int(y))
radius = int(radius)
cv2.circle(img,center,radius,(0,255,0),2)

rows,cols = img.shape[:2]
[vx,vy,x,y] = cv2.fitLine(cnt, cv2.DIST_L2,0,0.01,0.01)
lefty = int((-x*vy/vx) + y)
righty = int(((cols-x)*vy/vx)+y)
cv2.line(img,(cols-1,righty),(0,lefty),(0,255,0),2)