使用ROI找球(Python/OpenCV)
Use ROI to find a ball (Python/OpenCV)
如下所述：
我需要在白色场地上追踪一个 white/black 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bug是这样的：
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
当我找到轮廓时，我将图像复制到 ROI 中，然后执行算法，有时它会工作，直到出现错误！
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()
在大小为 448 的数组中不能有索引 448（索引从 0 开始）。试着从你的计数器中减去一个。
例如
(b2, g2, r2) = img_Ball[i + yy2-1 , j + xx2-1]
如下所述：
我需要在白色场地上追踪一个 white/black 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bug是这样的：
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
当我找到轮廓时，我将图像复制到 ROI 中，然后执行算法，有时它会工作，直到出现错误！
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()
在大小为 448 的数组中不能有索引 448（索引从 0 开始）。试着从你的计数器中减去一个。
例如
(b2, g2, r2) = img_Ball[i + yy2-1 , j + xx2-1]