python - 使用 ROI 找球 (Python/OpenCV)

Question

如此处所述: Tracking white ball in white background (Python/OpenCV)

我需要在白色 field 上追踪一个白/黑球。问题是 OpenCV 中的函数不是 100% 准确的，这就是为什么我需要使用算法来确定找到的轮廓是否可能是球。

算法很简单，它说，检查检测到的轮廓中心上方和下方的 2 个矩形中的所有颜色并计算它们的平均值，然后比较它们。如果差别不大，那可能是一个球(可以是另一个物体，但它排除了很多物体，它变得更准确!)

我现在的小错误是:

Traceback (most recent call last):
  File "aaa.py", line 211, in <module>
  (b2, g2, r2) = img_Ball[i + yy2 , j + xx2]
IndexError: index 448 is out of bounds for axis 0 with size 448

当我找到一个轮廓时，我将图像复制到 ROI 中，然后执行算法，它有时会起作用，直到出现该错误!

这是我的代码:

import numpy as np
import imutils
import cv2


# Create a black image, a window
#imgs = np.zeros((300,512,3), np.uint8)
#cv2.namedWindow('trackbar')
#cv2.createTrackbar('p1','trackbar',24,255,nothing)    # 0 is always the minimum
#cv2.createTrackbar('p2','trackbar',65,255,nothing)


cv2.namedWindow('white')
cv2.createTrackbar('bl', 'white', 152, 255, nothing)  #0 black
cv2.createTrackbar('gl', 'white', 107, 255, nothing)  #0
cv2.createTrackbar('rl', 'white', 105, 255, nothing)  #0
cv2.createTrackbar('bh', 'white', 255, 255, nothing)  #59
cv2.createTrackbar('gh', 'white', 255, 255, nothing)  #37
cv2.createTrackbar('rh', 'white', 255, 255, nothing)  #18


#img = cv2.imread('hand_055.png')
camera = cv2.VideoCapture(0)



while True:
        (grabed ,img) = camera.read()

        #parameter1 = cv2.getTrackbarPos('p1','trackbar')
        #parameter2 = cv2.getTrackbarPos('p2','trackbar')

        bl_temp=cv2.getTrackbarPos('bl', 'white')
        gl_temp=cv2.getTrackbarPos('gl', 'white')
        rl_temp=cv2.getTrackbarPos('rl', 'white')
        bh_temp=cv2.getTrackbarPos('bh', 'white')
        gh_temp=cv2.getTrackbarPos('gh', 'white')
        rh_temp=cv2.getTrackbarPos('rh', 'white')

        resized = imutils.resize(img, width=600)
        mask = cv2.inRange(resized,(bl_temp,gl_temp,rl_temp),(bh_temp,gh_temp,rh_temp))


        #gray = cv2.cvtColor(thresh, cv2.COLOR_BGR2GRAY)
        blurred1 = cv2.GaussianBlur(mask, (5, 5), 0)
        edged = cv2.Canny(blurred1, 24 , 65 ) #parameter1, parameter2)


        contours_canny= cv2.findContours(edged.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)[-2]
        contours_canny = sorted(contours_canny , key=cv2.contourArea, reverse=True)

        contour_list = []
        k = 0
        centerLast = (0,0)

        minArea = 15 # 50

        img_copie = img.copy()

        for contour in contours_canny:
            approx = cv2.approxPolyDP(contour,0.01*cv2.arcLength(contour,True),True)
            area = cv2.contourArea(contour)
            if ((len(approx) > 8) & (len(approx) < 23) & (area > minArea)):
                M = cv2.moments(contour)
                center = (int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"]))

                ((x, y), radius) = cv2.minEnclosingCircle(contour)
                x = int(x)
                y = int(y)
                radius = int(radius)

                if  ( radius > 30 and radius < 90 and area > 40 and area < 100) or ( radius > 15 and radius < 50 and area > 750 and area < 5200) :


                        k = k + 1

                        #find error
                        distanceXX = abs ( center[0] - centerLast[0])
                        distanceYY = abs ( center[1] - centerLast[1])

                        if (center == centerLast) or ((distanceXX < 5) and (distanceYY < 5)):
                                print("duplicated objetct resolved !")
                                continue

                        y1 = y - radius
                        y2 = y + radius
                        x1 = x - radius
                        x2 = x + radius
                        if y1 < 0: y1 =0
                        if x1 < 0: x1 =0
                        if y2 < 0: y2 =0
                        if x2 < 0: x2 =0

                        roi_img = img_copie[ y1: y2 , x1: x2]  # y, y+h , x , x+w
                        #cv2.imshow("ROi_image", roi_img)

                        ####################################################avg , avg_summe = isBall(roi_img)
                        width_zoom = 600
                        img_Ball = imutils.resize(roi_img.copy(), width_zoom)
                        cv2.imshow('abccc', img_Ball)
                        s_w = 100
                        s_h = 100
                        ss = s_w * s_h

                        xx1 = 250 # w/2 - h/2
                        yy1 = 100

                        xx2 = 250
                        yy2 = 400

                        rr = 0
                        gg = 0
                        bb = 0

                        b_summe = 0
                        g_summe = 0
                        r_summe = 0


                        i = 0
                        j = 0

                        for i in range(s_w):    # for every pixel:
                            for j in range(s_h):
                                (b1, g1, r1) = img_Ball[i + yy1 , j + xx1]  # RGB = (B, G, R)
                                (b2, g2, r2) = img_Ball[i + yy2 , j + xx2]

                                ##summe
                                b_summe = b_summe + b1
                                g_summe = g_summe + g1
                                r_summe = r_summe + r1

                                ##
                                if (b1>b2):
                                    b = b1 - b2
                                else:
                                    b = b2 - b1
                                ##
                                if (g1>g2):
                                    g = g1 - g2
                                else:
                                    g = g2 - g1
                                ##
                                if (r1>r2):
                                    r = r1 - r2
                                else:
                                    r = r2 - r1


                                bb = bb+b
                                gg = gg+g
                                rr = rr+r



                        avg_r = int(rr / ss)
                        avg_g = int(gg / ss)
                        avg_b = int(bb / ss)
                        avg = (avg_b , avg_g , avg_r )

                        avg_r_summe = int(r_summe / ss)
                        avg_g_summe = int(g_summe / ss)
                        avg_b_summe = int(b_summe / ss)
                        avg_summe = (avg_b_summe , avg_g_summe , avg_r_summe )

                        ####################################################
                        print ( "Objekt ", k , " : center = ", center, " , radius = ", radius, " , lenght = ", len(approx) , " , area = " , area)



                        if ( (avg_r < 60) & (avg_g < 60) & (avg_b < 60) ):
                            contour_list.append(contour)
                            cv2.circle(img, center , 3, (0,255,0), 2)
                            cv2.circle(img, center , radius, (0,255,0), 2)
                            cv2.putText(img , str(k) , center , cv2.FONT_HERSHEY_SIMPLEX, 0.6, (40, 0 ,0 ),2) # hier center..
                            print("is ball : " , avg , avg_summe)

                        else:
                            cv2.circle(img, center , radius, (255,255,255), 2)
                            print("not ball : " , avg , avg_summe)

                        #cv2.imshow("ROi_image", roi_img)
                        #cv2.waitKey(0)
                        #cv2.destroyWindow("ROi_image")

                        centerLast = center
                        avg = (0,0,0)
                        print("---")


        #cv2.drawContours(img, contour_list,  -1, (255,0,0), 2)
        print ( "------------------------" )
        cv2.imshow('Objects Detected',img)
        cv2.imshow('Shape',edged)

        # if the 'q' key is pressed, stop the loop
        key = cv2.waitKey(1) & 0xFF

        if key == ord("s"):
            cv2.waitKey(0)

        if key == ord("q"):
                break

# cleanup the camera and close any open windows
camera.release()
cv2.destroyAllWindows()

Answer 1

在大小为 448 的数组中不能有索引 448(索引从 0 开始)。尝试从您的计数器中减去一个。

例如。

(b2, g2, r2) = img_Ball[i + yy2-1 , j + xx2-1]