本节介绍了如何在图像上绘制图形,并且如何用鼠标和滚动条实现用户交互。
OpenCV 提供了绘制直线的函数cv2.line()、绘制矩形的函数cv2.rectangle()、绘制圆的函数cv2.circle()、绘制椭圆的函数cv2.ellipse()、绘制多边形的函数cv2.polylines()、在图像内添加文字的函数cv2.putText()等多种绘图函数。
这些绘图函数有一些共有的参数,主要用于设置源图像、颜色、线条属性等。下面对这些共有参数做简单的介绍。
img = cv2.line( img, pt1, pt2, color[, thickness[, lineType ]])
import numpy as np
import cv2
n = 300
img = np.zeros((n+1,n+1,3), np.uint8)
img = cv2.line(img,(0,0),(n,n),(255,0,0),3)
img = cv2.line(img,(0,100),(n,100),(0,255,0),1)
img = cv2.line(img,(100,0),(100,n),(0,0,255),6)
winname = 'Demo19.1'
cv2.namedWindow(winname)
cv2.imshow(winname, img)
cv2.waitKey(0)
cv2.destroyAllWindows()
img = cv2.rectangle( img, pt1, pt2, color[, thickness[, lineType]] )
import numpy as np
import cv2
n = 300
img = np.ones((n,n,3), np.uint8)*255
img = cv2.rectangle(img,(50,50),(n-100,n-50),(0,0,255),-1)
winname = 'Demo19.1'
cv2.namedWindow(winname)
cv2.imshow(winname, img)
cv2.waitKey(0)
cv2.destroyAllWindows()
img = cv2.circle( img, center, radius, color[, thickness[, lineType]] )
import numpy as np
import cv2
d = 400
img = np.ones((d,d,3),dtype="uint8")*255
(centerX,centerY) = (round(img.shape[1] / 2),round(img.shape[0] / 2))
# 将图像的中心作为圆心,实际值为d/2
red = (0,0,255) # 设置白色变量
for r in range(5,round(d/2),12):
cv2.circle(img,(centerX,centerY),r,red,3)
# circle(载体图像,圆心,半径,颜色)
cv2.imshow("Demo19.3",img)
cv2.waitKey(0)
cv2.destroyAllWindows()
import numpy as np
import cv2
d = 400
img = np.ones((d,d,3),dtype="uint8")*255
# 生成白色背景
for i in range(0,100):
centerX = np.random.randint(0,high = d)
centerY = np.random.randint(0,high = d)
# 生成随机圆心centerY,确保在画布img 内
radius = np.random.randint(5,high = d/5)
# 生成随机半径,值范围为[5,d/5),最大半径是d/5
color = np.random.randint(0,high = 256,size = (3,)).tolist()
# 生成随机颜色,3 个[0,256)的随机数
cv2.circle(img,(centerX,centerY),radius,color,-1)
# 使用上述随机数在画布img 内画圆
# 生成随机圆心centerX,确保在画布img 内
cv2.imshow("demo19.4",img)
cv2.waitKey(0)
cv2.destroyAllWindows()
img=cv2.ellipse(img, center, axes, angle, startAngle, endAngle, color[, thickness[, lineType]])
import numpy as np
import cv2
d = 400
img = np.ones((d,d,3),dtype="uint8")*255
# 生成白色背景
center=(round(d/2),round(d/2))
# 注意数值类型,不可以使用语句center=(d/2,d/2)
size=(100,200)
# 轴的长度
for i in range(0,10):
angle = np.random.randint(0,361)
# 偏移角度
color = np.random.randint(0,high = 256,size = (3,)).tolist()
# 生成随机颜色,3 个[0,256)的随机数
thickness = np.random.randint(1,9)
cv2.ellipse(img, center, size, angle, 0, 360, color,thickness)
cv2.imshow("demo19.5",img)
cv2.waitKey(0)
cv2.destroyAllWindows()
img = cv2.polylines( img, pts, isClosed, color[, thickness[, lineType[, shift]]])
在使用函数cv2.polylines()绘制多边形时,需要给出每个顶点的坐标。这些点的坐标构建了一个大小等于“顶点个数×1×2”的数组,这个数组的数据类型必须为numpy.int32。下面的例子绘制了一个黄色的具有四个顶点的多边形。
import numpy as np
import cv2
d = 400
img = np.ones((d,d,3),dtype="uint8")*255
# 生成白色背景
pts=np.array([[200,50],[300,200],[200,350],[100,200]], np.int32)
# 生成各个顶点,注意数据类型为int32
pts=pts.reshape((-1,1,2))
# 第1 个参数为-1, 表明它未设置具体值,它所表示的维度值是通过其他参数值计算得到的
cv2.polylines(img,[pts],True,(0,255,0),8)
# 调用函数cv2.polylines()完成多边形绘图。注意,第3 个参数控制多边形是否封闭
cv2.imshow("demo19.6",img)
cv2.waitKey(0)
cv2.destroyAllWindows()
img=cv2.putText(img, text, org, fontFace, fontScale, color[, thickness[, lineType[, bottomLeftOrigin]]])
import numpy as np
import cv2
d = 400
img = np.ones((d,d,3),dtype="uint8")*255
# 生成白色背景
font=cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(img,'OpenCV',(0,200), font, 3,(0,255,0),15)
cv2.putText(img,'OpenCV',(0,200), font, 3,(0,0,255),5)
cv2.imshow("demo19.7",img)
cv2.waitKey(0)
cv2.destroyAllWindows()
import numpy as np
import cv2
d = 400
img = np.ones((d,d,3),dtype="uint8")*255
# 生成白色背景
font=cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(img,'OpenCV',(0,150),font, 3,(0,0,255),15)
cv2.putText(img,'OpenCV',(0,250),font, 3,(0,255,0),15,cv2.FONT_HERSHEY_SCRIPT_SIMPLEX,True)
cv2.imshow("demo19.7",img)
cv2.waitKey(0)
cv2.destroyAllWindows()
当用户触发鼠标事件时,我们希望对该事件做出响应。例如,用户单击鼠标,我们就画一个圆。通常的做法是,创建一个OnMouseAction()响应函数,将要实现的操作写在该响应函数内。响应函数是按照固定的格式创建的,其格式为:·
def OnMouseAction(event,x,y,flags,param):
定义响应函数以后,要将该函数与一个特定的窗口建立联系(绑定),让该窗口内的鼠标触发事件时, 能够找到该响应函数并执行。要将函数与窗口绑定, 可以通过函数
cv2.setMouseCallback()实现,其基本语法格式是:
cv2.setMouseCallback(winname,onMouse)
import cv2
import numpy as np
def Demo(event,x,y,flags,param):
if event == cv2.EVENT_LBUTTONDOWN:
print("单击了鼠标左键")
elif event==cv2.EVENT_RBUTTONDOWN :
print("单击了鼠标右键")
elif flags==cv2.EVENT_FLAG_LBUTTON:
print("按住左键拖动了鼠标")
elif event==cv2.EVENT_MBUTTONDOWN :
print("单击了中间键")
# 创建名称为Demo 的响应(回调)函数OnMouseAction
img = np.ones((300,300,3),np.uint8)*255
cv2.namedWindow('Demo19.9')
cv2.setMouseCallback('Demo19.9',Demo)
cv2.imshow('Demo19.9',img)
cv2.waitKey()
cv2.destroyAllWindows()
运行上述程序,先后单击左键、右键、滚轮、拖动鼠标,则程序运行结果如图所示。
说明:可以通过下面的方法查看OpenCV 所支持的鼠标事件:
import cv2
events=[i for i in dir(cv2) if 'EVENT'in i]
print(events)
实现一个双击鼠标绘制矩形的简单程序。在该程序中,首先创建响应函数draw(),在该函数内编写代码,实现:当双击鼠标时,以当前位置为顶点绘制大小随机、颜色随机的矩形。通过函数cv2.setMouseCallback()将函数draw()和新建窗口“Demo19.10”绑定。
import cv2
import numpy as np
d = 400
def draw(event,x,y,flags,param):
if event==cv2.EVENT_LBUTTONDBLCLK:
p1x=x
p1y=y
p2x=np.random.randint(1,d-50)
p2y=np.random.randint(1,d-50)
color = np.random.randint(0,high = 256,size = (3,)).tolist()
cv2.rectangle(img,(p1x,p1y),(p2x,p2y),color,2)
img = np.ones((d,d,3),dtype="uint8")*255
cv2.namedWindow('Demo19.10')
cv2.setMouseCallback('Demo19.10',draw)
while(1):
cv2.imshow('Demo19.10',img)
if cv2.waitKey(20)==27:
break
cv2.destroyAllWindows()
鼠标事件为用户与计算机之间的交互提供了接口,让用户能够非常灵活地与计算机之间实现交互。本节通过一个鼠标与键盘配合的例子,展示如何实现用户与计算机的交互。
import numpy as np
thickness=-1
mode=1
d=400
def draw_circle(event,x,y,flags,param):
if event==cv2.EVENT_LBUTTONDOWN:
a=np.random.randint(1,d-50)
r=np.random.randint(1,d/5)
angle = np.random.randint(0,361)
color = np.random.randint(0,high = 256,size = (3,)).tolist()
if mode==1:
cv2.rectangle(img,(x,y),(a,a),color,thickness)
elif mode==2:
cv2.circle(img,(x,y),r,color,thickness)
elif mode==3:
cv2.line(img,(a,a),(x,y),color,3)
elif mode==4:
cv2.ellipse(img, (x,y), (100,150), angle, 0, 360,color,thickness)
elif mode==5:
cv2.putText(img,'OpenCV',(0,round(d/2)),cv2.FONT_HERSHEY_SIMPLEX, 2,color,5)
img=np.ones((d,d,3),np.uint8)*255
cv2.namedWindow('image')
cv2.setMouseCallback('image',draw_circle)
while(1):
cv2.imshow('image',img)
k=cv2.waitKey(1)&0xFF
if k==ord('r'):
mode=1
elif k==ord('c'):
mode=2
elif k==ord('l'):
mode=3
elif k==ord('e'):
mode=4
elif k==ord('t'):
mode=5
elif k==ord('f'):
thickness=-1
elif k==ord('u'):
thickness=3
elif k==27:
break
cv2.destroyAllWindows()
import cv2
import numpy as np
d=400
centerx=round(d/2)
centery=round(d/2)
r=50
def Demo(event,x,y,flags,param):
global centerx,centery
if flags==cv2.EVENT_FLAG_LBUTTON:
if x>centerx-r and x<centerx+r and y>centery-r and y<centery+r:
centerx=x
centery=y
global img
img = np.ones((400,400,3),np.uint8)*255
cv2.circle(img,(centerx,centery),r,(0,0,255),-1)
print("yes")
# 创建名称为Demo 的响应(回调)函数OnMouseAction
img = np.ones((400,400,3),np.uint8)*255
cv2.circle(img,(centerx,centery),r,(0,0,255),-1)
cv2.namedWindow('test')
cv2.setMouseCallback('test',Demo)
while(1):
cv2.imshow('test',img)
if cv2.waitKey(20)==27:
break
cv2.destroyAllWindows()
当鼠标按下左键拖动,且鼠标的坐标在圆范围内时,即可拖动圆的位置。
滚动条(Trackbar)在OpenCV 中是非常方便的交互工具,它依附于特定的窗口而存在。通过调节滚动条能够设置、获取指定范围内的特定值。
cv2.createTrackbar(trackbarname, winname, value, count, onChange)
函数 cv2.createTrackbar()用于生成一个滚动条。拖动滚动条,就可以设置滚动条的值,并让滚动条返回对应的值。滚动条的值可以通过函数cv2.getTrackbarPos()获取,其语法格式为:
retval=getTrackbarPos( trackbarname,winname )
import cv2
import numpy as np
def changeColor(x):
r=cv2.getTrackbarPos('R','image')
g=cv2.getTrackbarPos('G','image')
b=cv2.getTrackbarPos('B','image')
img[:]=[b,g,r]
img=np.zeros((100,700,3),np.uint8)
cv2.namedWindow('image')
cv2.createTrackbar('R','image',0,255,changeColor)
cv2.createTrackbar('G','image',0,255,changeColor)
cv2.createTrackbar('B','image',0,255,changeColor)
while(1):
cv2.imshow('image',img)
k=cv2.waitKey(1)&0xFF
if k==27:
break
cv2.destroyAllWindows()
import cv2
Type=0 # 阈值处理方式
Value=0 # 使用的阈值
def onType(a):
Type= cv2.getTrackbarPos(tType, windowName)
Value= cv2.getTrackbarPos(tValue, windowName)
ret, dst = cv2.threshold(o, Value,255, Type)
cv2.imshow(windowName,dst)
def onValue(a):
Type= cv2.getTrackbarPos(tType, windowName)
Value= cv2.getTrackbarPos(tValue, windowName)
ret, dst = cv2.threshold(o, Value, 255, Type)
cv2.imshow(windowName,dst)
o = cv2.imread("lena512.bmp",0)
windowName = "Demo19.13" #窗体名
cv2.namedWindow(windowName)
cv2.imshow(windowName,o)
# 创建两个滚动条
tType = "Type" # 用来选取阈值处理方式的滚动条
tValue = "Value" # 用来选取阈值的滚动条
cv2.createTrackbar(tType, windowName, 0, 4, onType)
cv2.createTrackbar(tValue, windowName,0, 255, onValue)
if cv2.waitKey(0) == 27:
cv2.destroyAllWindows()
运行程序,在窗体对象内,同时显示控制阈值和阈值处理方式的两个滚动条。调整滚动条可以分别控制阈值处理时所使用的阈值和阈值处理方式。
有时也可将滚动条作为“开关”使用。此时,滚动条只有两种值“0”和“1”,当滚动条的值为0 时,代表False;当滚动条的值为1 时,代表True。
import cv2
import numpy as np
d=400
global thickness
thickness=-1
def fill(x):
pass
def draw(event,x,y,flags,param):
if event==cv2.EVENT_LBUTTONDBLCLK:
p1x=x
p1y=y
p2x=np.random.randint(1,d-50)
p2y=np.random.randint(1,d-50)
color = np.random.randint(0,high = 256,size = (3,)).tolist()
cv2.rectangle(img,(p1x,p1y),(p2x,p2y),color,thickness)
img=np.ones((d,d,3),np.uint8)*255
cv2.namedWindow('image')
cv2.setMouseCallback('image',draw)
cv2.createTrackbar('R','image',0,1,fill)
while(1):
cv2.imshow('image',img)
k=cv2.waitKey(1)&0xFF
g=cv2.getTrackbarPos('R','image')
if g==0:
thickness=-1
else:
thickness=2
if k==27:
break
cv2.destroyAllWindows()