用python3 opencv3 實現相機學生證的實時跟蹤

準備材料：python3 opencv3

安裝opencv的方法可以看我的其他文章

目標：使用攝像頭0追蹤綠色的學生證並且在畫面上面標註出來

import numpy as np
import math
import cv2
import time

def nothing(x):
    pass

cap = cv2.VideoCapture(0)   #打開攝像頭0


var = cv2.CAP_PVAPI
LowerRed = np.array([24, 75, 37])


# 創建改變顏色的滾動條
cv2.namedWindow("fps")  #新建一個窗口
cv2.createTrackbar('R','fps',89,255,nothing)    #想要追蹤顏色的R值
cv2.createTrackbar('G','fps',254,255,nothing)   #想要追蹤顏色的G值
cv2.createTrackbar('B','fps',254,255,nothing)   #想要追蹤顏色的B值
cv2.createTrackbar('threshold','fps',19,255,nothing)    #二值化閾值

while(1):
    #滑動條賦值
    r = cv2.getTrackbarPos('R', 'fps')
    g = cv2.getTrackbarPos('G', 'fps')
    b = cv2.getTrackbarPos('B', 'fps')
    c = cv2.getTrackbarPos('threshold', 'fps')
    UpperRed = np.array([r, g, b])
    ret, frame = cap.read()#得到每一幀
    ret, frame1 = cap.read()  # 得到每一幀

    #hsv
    HSV= cv2.cvtColor(frame, cv2.COLOR_RGB2HSV)
    #遮罩
    mask = cv2.inRange(HSV, LowerRed, UpperRed)
    RED_Things = cv2.bitwise_and(frame, frame, mask=mask)
    img_gray = cv2.cvtColor(RED_Things, cv2.COLOR_BGR2GRAY)  # 灰度化
    ret, img_threshold = cv2.threshold(img_gray, c, 255, cv2.THRESH_BINARY)  # 二值化
    # 膨脹+腐蝕等形態學變化
    kerne1 = np.ones((3, 3), np.uint8)
    img_erosin = cv2.erode(img_threshold, kerne1, iterations=1)
    #cv2.imshow("dil",img_erosin)
    kerne2 = np.ones((45, 45), np.uint8)
    img_dilation = cv2.dilate(img_erosin, kerne2, iterations=1)
    kerne3 = np.ones((11, 11), np.uint8)
    img_dilation1 = cv2.dilate(img_dilation,kerne3,iterations=1)
    #cv2.imshow("ers",img_dilation1)
    kerne3 = np.ones((51, 51), np.uint8)
    img_erosin1 = cv2.erode(img_dilation1, kerne3, iterations=1)
    #圖像相與
    img_bit = cv2.bitwise_and(frame, frame, mask=img_erosin1)
    cv2.imshow("bit",img_bit)





    # 邊緣caany
    img_gray1 = cv2.cvtColor(img_bit, cv2.COLOR_BGR2GRAY)  # 灰度化
    ret, img_threshold1 = cv2.threshold(img_gray1, c, 255, cv2.THRESH_BINARY)  # 二值化
    canny = cv2.Canny(img_threshold1, 10, 200)  # apertureSize默認爲3
    #cv2.imshow("img1",img_threshold1)


    coutours = cv2.findContours(img_threshold1, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)[-2]#得到輪廓
    #由於可能遇到畫面中沒有綠色的場景避免程序意外中斷所以把計算寫入了try裏面
    try :

        cnt=coutours[-1]
        p=0
        for p in coutours:
            area = cv2.contourArea(cnt,True) #計算面積

            if area>=60:
                break
        M = cv2.moments(p) #計算中心
    except Exception as err1:
        print(err1)

        pass


    try :
        cx = int(M["m10"] / M["m00"])
        cy = int(M["m01"] / M["m00"])
        #得到中心然後在畫面上顯示
        cv2.circle(frame1, (cx, cy), 9, (255, 0, 255), -1)
        cv2.line(frame1,(cx,0),(cx,700),(255,0,0),3)
        cv2.line(frame1,(0,cy),(700,cy),(255,0,0),3)
    except Exception as err2:
        print(err2)

        pass

    cv2.imshow("fps", frame1)




    if cv2.waitKey(1) & 0xFF == ord('q'):   #按q保存一張圖片
        cv2.imwrite("E:\cpy\pictures\\pic.jpg", frame1)
        break
cap.release()
cv2.destroyAllWindows()

使用了滑動條建立的簡易ui方便用戶調整自己想要追蹤的顏色（滑動條改）（可能需要調顏色下限）