im = cv2.imread("./ladder.png")
gray_img = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)

canny = cv2.Canny(gray_img, 30, 150)

lines = cv2.HoughLines(canny, 1, np.pi / 180, 180)
lines1 = lines[:, 0, :]
for rho, theta in lines1[:]:
    a = np.cos(theta)
    b = np.sin(theta)
    x0 = a * rho
    y0 = b * rho
    x1 = int(x0 + 3000 * (-b))
    y1 = int(y0 + 3000 * (a))
    x2 = int(x0 - 3000 * (-b))
    y2 = int(y0 - 3000 * (a))
    cv2.line(im, (x1, y1), (x2, y2), (0, 0, 255), 2)

import cv2
import numpy as np

def line_detect(image):
  # 將圖片轉(zhuǎn)換為HSV
  hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
  # 設(shè)置閾值
  lowera = np.array([0, 0, 221])
  uppera = np.array([180, 30, 255])
  mask1 = cv2.inRange(hsv, lowera, uppera)
  kernel = np.ones((3, 3), np.uint8)

  # 對(duì)得到的圖像進(jìn)行形態(tài)學(xué)操作（閉運(yùn)算和開運(yùn)算）
  mask = cv2.morphologyEx(mask1, cv2.MORPH_CLOSE, kernel) #閉運(yùn)算：表示先進(jìn)行膨脹操作，再進(jìn)行腐蝕操作
  mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)  #開運(yùn)算：表示的是先進(jìn)行腐蝕，再進(jìn)行膨脹操作

  # 繪制輪廓
  edges = cv2.Canny(mask, 50, 150, apertureSize=3)
  # 顯示圖片
  cv2.imshow("edges", edges)
  # 檢測(cè)白線  這里是設(shè)置檢測(cè)直線的條件，可以去讀一讀HoughLinesP()函數(shù)，然后根據(jù)自己的要求設(shè)置檢測(cè)條件
  lines = cv2.HoughLinesP(edges, 1, np.pi / 180, 40,minLineLength=10,maxLineGap=10)
  print "lines=",lines
  print "========================================================"
  i=1
  # 對(duì)通過霍夫變換得到的數(shù)據(jù)進(jìn)行遍歷
  for line in lines:
    # newlines1 = lines[:, 0, :]
    print "line["+str(i-1)+"]=",line
    x1,y1,x2,y2 = line[0]  #兩點(diǎn)確定一條直線，這里就是通過遍歷得到的兩個(gè)點(diǎn)的數(shù)據(jù) （x1,y1）(x2,y2)
    cv2.line(image,(x1,y1),(x2,y2),(0,0,255),2)   #在原圖上畫線
    # 轉(zhuǎn)換為浮點(diǎn)數(shù)，計(jì)算斜率
    x1 = float(x1)
    x2 = float(x2)
    y1 = float(y1)
    y2 = float(y2)
    print "x1=%s,x2=%s,y1=%s,y2=%s" % (x1, x2, y1, y2)
    if x2 - x1 == 0:
      print "直線是豎直的"
      result=90
    elif y2 - y1 == 0 :
      print "直線是水平的"
      result=0
    else:
      # 計(jì)算斜率
      k = -(y2 - y1) / (x2 - x1)
      # 求反正切，再將得到的弧度轉(zhuǎn)換為度
      result = np.arctan(k) * 57.29577
      print "直線傾斜角度為：" + str(result) + "度"
    i = i+1
  #   顯示最后的成果圖
  cv2.imshow("line_detect",image)
  return result

if __name__ == '__main__':
  # 讀入圖片
  src = cv2.imread("lines/line6.jpg")
  # 設(shè)置窗口大小
  cv2.namedWindow("input image", cv2.WINDOW_AUTOSIZE)
  # 顯示原始圖片
  cv2.imshow("input image", src)
  # 調(diào)用函數(shù)
  line_detect(src)
  cv2.waitKey(0)