import cv2

import numpy as np

def stackImages(scale, imgArray):

  '''

  图像堆栈，可缩放，按列表排列，不受颜色通道限制

  '''

  rows = len(imgArray)

  cols = len(imgArray[0])

  rowsAvailable = isinstance(imgArray[0], list)

  width = imgArray[0][0].shape[1]

  height = imgArray[0][0].shape[0]

  if rowsAvailable:

    for x in range(0, rows):

      for y in range(0, cols):

        if imgArray[x][y].shape[:2] == imgArray[0][0].shape[:2]:

          imgArray[x][y] = cv2.resize(imgArray[x][y], (0, 0), None, scale, scale)

        else:

          imgArray[x][y] = cv2.resize(imgArray[x][y], (imgArray[0][0].shape[1], imgArray[0][0].shape[0]),

                        None, scale, scale)

        if len(imgArray[x][y].shape) == 2:

          imgArray[x][y] = cv2.cvtColor(imgArray[x][y], cv2.COLOR_GRAY2BGR)

    imageBlank = np.zeros((height, width, 3), np.uint8)

    hor = [imageBlank]*rows

    hor_con = [imageBlank]*rows

    for x in range(0, rows):

      hor[x] = np.hstack(imgArray[x])

    ver = np.vstack(hor)

  else:

    for x in range(0, rows):

      if imgArray[x].shape[:2] == imgArray[0].shape[:2]:

        imgArray[x] = cv2.resize(imgArray[x], (0, 0), None, scale, scale)

      else:

        imgArray[x] = cv2.resize(imgArray[x], (imgArray[0].shape[1], imgArray[0].shape[0]), None,scale, scale)

      if len(imgArray[x].shape) == 2:

        imgArray[x] = cv2.cvtColor(imgArray[x], cv2.COLOR_GRAY2BGR)

    hor = np.hstack(imgArray)

    ver = hor

  return ver

def empty(a):

  pass

cap = cv2.VideoCapture(0)

cv2.namedWindow("TrackBars")

cv2.resizeWindow("TrackBars", 640, 240)

cv2.createTrackbar("Hue Min", "TrackBars", 32, 179, empty)

cv2.createTrackbar("Hue Max", "TrackBars", 127, 179, empty)

cv2.createTrackbar("Sat Min", "TrackBars", 110, 255, empty)

cv2.createTrackbar("Sat Max", "TrackBars", 255, 255, empty)

cv2.createTrackbar("Val Min", "TrackBars", 133, 255, empty)

cv2.createTrackbar("Val Max", "TrackBars", 255, 255, empty)

while True:

  success, img=cap.read()

  imgHSV = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

  h_min = cv2.getTrackbarPos("Hue Min", "TrackBars")

  h_max = cv2.getTrackbarPos("Hue Max", "TrackBars")

  s_min = cv2.getTrackbarPos("Sat Min", "TrackBars")

  s_max = cv2.getTrackbarPos("Sat Max", "TrackBars")

  v_min = cv2.getTrackbarPos("Val Min", "TrackBars")

  v_max = cv2.getTrackbarPos("Val Max", "TrackBars")

  lower = np.array([h_min, s_min, v_min])

  upper = np.array([h_max, s_max, v_max])

  mask = cv2.inRange(imgHSV, lower, upper)

  imgResult = cv2.bitwise_and(img, img, mask=mask)

  try:

    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    blur_img = cv2.GaussianBlur(gray, (3, 3), 0)

    circles = cv2.HoughCircles(image=blur_img, method=cv2.HOUGH_GRADIENT,

                  dp=1,

                  minDist=200, # 两个圆之间圆心的最小距离.如果太小的，多个相邻的圆可能被错误地检测成了一个重合的圆。反之，这参数设置太大，某些圆就不能被检测出来。

                  param1=100,

                  param2=120,

                  minRadius=0, # 圆半径的最小值

                  maxRadius=20) # 圆半径的最大值

    circles = np.uint16(np.around(circles))

    for i in circles[0, :]:

      # 画圆

      cv2.circle(img, (i[0], i[1]), i[2], (0, 255, 255), 5)

      # 画圆心

      cv2.circle(img, (i[0], i[1]), 2, (0, 255, 255), 3)

      print('圆心坐标为（%.2f,%.2f）' % (i[0], i[1]))

      a = str(i[0])

      b = str(i[1])

      img = cv2.putText(img, "(" + a + " ," + b + ")", (i[0], i[1]), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 0, 0), 2, )

  except:

    print('无法识别到圆')

    imgStack = stackImages(0.6, ([gray, imgHSV, img], [mask, imgResult, img]))

  imgStack = stackImages(0.6, ([gray, imgHSV, img], [mask, imgResult, img]))

  cv2.imshow("Stack Images",imgStack)

  if cv2.waitKey(1) & 0xff == ord('q'):

    break