python+opencv識別紅燈

ID:704010 · 發(fā)表于 2020-3-7 13:13

# -*- coding: utf-8 -*-

#width = 256, 192
#YSU1100W fast-straight
#YSU1000W fast-left
#YSU0100W fast-right
#YSU1101W slow-s
#YSU1001W s-l
#YSU0101W s-r
#YSU0010W find

import numpy as np
import cv2
import serial
import time

#設(shè)定紅色閾值，HSV空間
redLower = np.array([0, 0, 230])
redUpper = np.array([10, 255, 237])
#初始化質(zhì)心
center = 0
#初始化串口
ser = serial.Serial("/dev/ttyUSB0",9600)
# s = 0
#打開攝像頭
camera = cv2.VideoCapture(0)
camera.set(3, 320)
camera.set(4, 240)
#遍歷每一幀，檢測信標(biāo)燈
while True:
# s = ser.read(8)
# # 如果讀到單片機(jī)傳過來的信號，倒車
# if s:
#    ser.write("YSU0000W".encode())
#    print("back")
#    time.sleep(3)
#    s = 0
#讀取幀
(ret, frame) = camera.read()
#判斷是否成功打開攝像頭
if not ret:
      # print ('No Camera')
      break
#轉(zhuǎn)到HSV空間
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
#根據(jù)閾值構(gòu)建掩膜黑白亮的為閾值內(nèi)區(qū)域
mask = cv2.inRange(hsv, redLower, redUpper)
#腐蝕操作  iterations：迭代次數(shù)
mask = cv2.erode(mask, None, iterations=1)
#膨脹操作，其實先腐蝕再膨脹的效果是開運(yùn)算，去除噪點(diǎn)
mask = cv2.dilate(mask, None, iterations=14)

#根據(jù)灰度值化為二值圖
# GrayImage=cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# ret, gray=cv2.threshold(GrayImage, 230, 255, cv2.THRESH_BINARY)
#把紅色分的二值圖和灰度二值圖疊加
# andout = cv2.bitwise_and(mask, gray)

#檢測尋找輪廓 cv2.RETR_EXTERNAL 只得到最外面的輪廓
#cv2.findContours()  opencv3會返回三個值,分別是img, countours, hierarchy
cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[-2]
#初始化圓形輪廓質(zhì)心
center = None
#如果存在輪廓
if len(cnts) > 0:
      #找到面積最大的輪廓
      c = max(cnts, key = cv2.contourArea)
      #確定面積最大的輪廓的最小外接圓
      ((x, y), radius) = cv2.minEnclosingCircle(c)
      #計算輪廓的矩
      M = cv2.moments(c)
      #計算質(zhì)心
      try:
         center = (int(M["m10"]/M["m00"]), int(M["m01"]/M["m00"]))
      except:
         continue
      #只有當(dāng)半徑大于1時，才執(zhí)行
      if radius >= 1:
         #畫輪廓圓：img,center,radius,color 厚度：負(fù)值就是實心
         cv2.circle(frame, (int(x), int(y)), int(radius), (0, 255, 255), 1)
         #在質(zhì)心中間畫半徑為5的點(diǎn)
         cv2.circle(frame, center, 5, (0, 0, 255), -1)
         #最關(guān)鍵的值pos，相對于畫面中心的x方向像素差
         pos = center[0]-160
         # print("x=%s"%pos)
         # print(radius)

         try:
            #通過x坐標(biāo)控制串口
            # if radius >= 60:
            #    t = 0
            #    while True:
            #       t += 0.05
            #       if t >= 0.4:
            #          break
            #       ser.write("YSU1101W".encode())
            #       time.sleep(0.05)
            #減速拐角大
            if radius >= 100:
                  #向左轉(zhuǎn)
                  if pos < -50:
                     ser.write("YSU1001W".encode())
                  #直線
                  elif -50 <= pos <= 50:
                     ser.write("YSU1101W".encode())
                  #向右轉(zhuǎn)
                  else:
                     ser.write("YSU0101W".encode())

            # 正常速度，拐角大
            elif 50 <= radius < 100:
                  if pos < -45:
                     ser.write("YSU0001W".encode())
                  elif -45 <= pos <= 45:
                     ser.write("YSU1100W".encode())
                  else:
                     ser.write("YSU0110W".encode())

            #正常速度,拐角小
            else:
                  #向左轉(zhuǎn)
                  if pos < -30:
                     ser.write("YSU1000W".encode())
                  #直線
                  elif - 30<= pos <= 30:
                     ser.write("YSU1100W".encode())
                  #向右轉(zhuǎn)
                  else:
                     ser.write("YSU0100W".encode())
         except:
            continue
      else:
         ser.write("YSU0010W".encode())

else:
      ser.write("YSU0010W".encode())

#cv2.imshow('Frame', frame)
#鍵盤檢測，檢測到esc鍵退出
k = cv2.waitKey(1)&0xFF
if k == 27:
      break

#攝像頭釋放
camera.release()
#銷毀所有窗口
# cv2.destroyAllWindows()

#關(guān)閉串口
ser.close()

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