1、显示图片、视频、电脑摄像头
import cv2
#LOAD AN IMAGE USING 'IMREAD'
img = cv2.imread("Resources/lena.png")
# # DISPLAY
cv2.imshow("Lena Soderberg",img)
#图像显示时间
cv2.waitKey(0)
import cv2
frameWidth = 640
frameHeight = 480
cap = cv2.VideoCapture("Resources/test_ video.mp4")
while True:
success, img = cap.read()
img = cv2.resize(img, (frameWidth, frameHeight))
cv2.imshow("Result", img)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
import cv2
frameWidth = 640
frameHeight = 480
#0 默认的是电脑自带的摄像头
cap = cv2.VideoCapture(0)
#cap.set函数中的3为帧的宽度、4为高度、10为亮度
cap.set(3, frameWidth)
cap.set(4, frameHeight)
cap.set(10,150)
while True:
success, img = cap.read()
cv2.imshow("Result", img)
#按下q键后break
if cv2.waitKey(1) & 0xFF == ord('q'):
break
2、图片处理
import cv2
import numpy as np
# kernel:卷积核,一般用一个5行5列的全是1的数组，生成：kernel=np.ones((5,5),np.uint8)
# iterations:迭代次数,要进行多少次腐蚀
# iterations默认情况下，迭代次数是1，根据需要可以进行多次腐蚀操作。
img = cv2.imread("Resources/lena.png")
kernel = np.ones((5,5),np.uint8)
# 灰度图、模糊图片、提取边缘、边缘膨胀、边缘细化
imgGray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
imgBlur = cv2.GaussianBlur(imgGray,(7,7),0)
imgCanny = cv2.Canny(img,150,200)
imgDialation = cv2.dilate(imgCanny,kernel,iterations=1)
imgEroded = cv2.erode(imgDialation,kernel,iterations=1)
cv2.imshow("Gray Image",imgGray)
cv2.imshow("Blur Image",imgBlur)
cv2.imshow("Canny Image",imgCanny)
cv2.imshow("Dialation Image",imgDialation)
cv2.imshow("Eroded Image",imgEroded)
cv2.waitKey(0)
import cv2
import numpy as np
img = cv2.imread("Resources/shapes.png")
print(img.shape)
# 缩放
imgResize = cv2.resize(img,(1000,500))
print(imgResize.shape)
# 裁剪
imgCropped = img[46:119,352:495]
cv2.imshow("Image",img)
#cv2.imshow("Image Resize",imgResize)
cv2.imshow("Image Cropped",imgCropped)
cv2.waitKey(0)
3、画框文字
import cv2
import numpy as np
img = np.zeros((512,512,3),np.uint8)
#print(img)
#img[:]= 255,0,0
cv2.line(img,(0,0),(img.shape[1],img.shape[0]),(0,255,0),3)
cv2.rectangle(img,(0,0),(250,350),(0,0,255),2)
cv2.circle(img,(400,50),30,(255,255,0),5)
cv2.putText(img," OPENCV ",(300,200),cv2.FONT_HERSHEY_COMPLEX,1,(0,150,0),3)
cv2.imshow("Image",img)
cv2.waitKey(0)
4、图像扭曲
import cv2
import numpy as np
img = cv2.imread("Resources/cards.jpg")
width,height = 250,350
pts1 = np.float32([[111,219],[287,188],[154,482],[352,440]])
pts2 = np.float32([[0,0],[width,0],[0,height],[width,height]])
matrix = cv2.getPerspectiveTransform(pts1,pts2)
imgOutput = cv2.warpPerspective(img,matrix,(width,height))
cv2.imshow("Image",img)
cv2.imshow("Output",imgOutput)
cv2.waitKey(0)
5、图像拼接
import cv2
import numpy as np
#图片堆栈
def stackImages(scale,imgArray):
rows = len(imgArray)
cols = len(imgArray[0])
rowsAvailable = isinstance(imgArray[0], list)
width = imgArray[0][0].shape[1]
height = imgArray[0][0].shape[0]
if rowsAvailable:
for x in range ( 0, rows):
for y in range(0, cols):
if imgArray[x][y].shape[:2] == imgArray[0][0].shape [:2]:
imgArray[x][y] = cv2.resize(imgArray[x][y], (0, 0), None, scale, scale)
else:
imgArray[x][y] = cv2.resize(imgArray[x][y], (imgArray[0][0].shape[1], imgArray[0][0].shape[0]), None, scale, scale)
if len(imgArray[x][y].shape) == 2: imgArray[x][y]= cv2.cvtColor( imgArray[x][y], cv2.COLOR_GRAY2BGR)
imageBlank = np.zeros((height, width, 3), np.uint8)
hor = [imageBlank]*rows
hor_con = [imageBlank]*rows
for x in range(0, rows):
hor[x] = np.hstack(imgArray[x])
ver = np.vstack(hor)
else:
for x in range(0, rows):
if imgArray[x].shape[:2] == imgArray[0].shape[:2]:
imgArray[x] = cv2.resize(imgArray[x], (0, 0), None, scale, scale)
else:
imgArray[x] = cv2.resize(imgArray[x], (imgArray[0].shape[1], imgArray[0].shape[0]), None,scale, scale)
if len(imgArray[x].shape) == 2: imgArray[x] = cv2.cvtColor(imgArray[x], cv2.COLOR_GRAY2BGR)
hor= np.hstack(imgArray)
ver = hor
return ver
img = cv2.imread('Resources/lena.png')
imgGray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
imgStack = stackImages(0.5,([img,imgGray,img],[img,img,img]))
#纵向拼接
# imgHor = np.hstack((img,img))
#横向拼接
# imgVer = np.vstack((img,img))
# cv2.imshow("Horizontal",imgHor)
# cv2.imshow("Vertical",imgVer)
cv2.imshow("ImageStack",imgStack)
cv2.waitKey(0)
6、颜色提取
import cv2
import numpy as np
def empty(a):
pass
def stackImages(scale,imgArray):
rows = len(imgArray)
cols = len(imgArray[0])
rowsAvailable = isinstance(imgArray[0], list)
width = imgArray[0][0].shape[1]
height = imgArray[0][0].shape[0]
if rowsAvailable:
for x in range ( 0, rows):
for y in range(0, cols):
if imgArray[x][y].shape[:2] == imgArray[0][0].shape [:2]:
imgArray[x][y] = cv2.resize(imgArray[x][y], (0, 0), None, scale, scale)
else:
imgArray[x][y] = cv2.resize(imgArray[x][y], (imgArray[0][0].shape[1], imgArray[0][0].shape[0]), None, scale, scale)
if len(imgArray[x][y].shape) == 2: imgArray[x][y]= cv2.cvtColor( imgArray[x][y], cv2.COLOR_GRAY2BGR)
imageBlank = np.zeros((height, width, 3), np.uint8)
hor = [imageBlank]*rows
hor_con = [imageBlank]*rows
for x in range(0, rows):
hor[x] = np.hstack(imgArray[x])
ver = np.vstack(hor)
else:
for x in range(0, rows):
if imgArray[x].shape[:2] == imgArray[0].shape[:2]:
imgArray[x] = cv2.resize(imgArray[x], (0, 0), None, scale, scale)
else:
imgArray[x] = cv2.resize(imgArray[x], (imgArray[0].shape[1], imgArray[0].shape[0]), None,scale, scale)
if len(imgArray[x].shape) == 2: imgArray[x] = cv2.cvtColor(imgArray[x], cv2.COLOR_GRAY2BGR)
hor= np.hstack(imgArray)
ver = hor
return ver
path = 'Resources/lambo.png'
cv2.namedWindow("TrackBars")
cv2.resizeWindow("TrackBars",640,240)
cv2.createTrackbar("Hue Min","TrackBars",0,179,empty)
cv2.createTrackbar("Hue Max","TrackBars",19,179,empty)
cv2.createTrackbar("Sat Min","TrackBars",110,255,empty)
cv2.createTrackbar("Sat Max","TrackBars",240,255,empty)
cv2.createTrackbar("Val Min","TrackBars",153,255,empty)
cv2.createTrackbar("Val Max","TrackBars",255,255,empty)
while True:
img = cv2.imread(path)
imgHSV = cv2.cvtColor(img,cv2.COLOR_BGR2HSV)
h_min = cv2.getTrackbarPos("Hue Min","TrackBars")
h_max = cv2.getTrackbarPos("Hue Max", "TrackBars")
s_min = cv2.getTrackbarPos("Sat Min", "TrackBars")
s_max = cv2.getTrackbarPos("Sat Max", "TrackBars")
v_min = cv2.getTrackbarPos("Val Min", "TrackBars")
v_max = cv2.getTrackbarPos("Val Max", "TrackBars")
print(h_min,h_max,s_min,s_max,v_min,v_max)
lower = np.array([h_min,s_min,v_min])
upper = np.array([h_max,s_max,v_max])
mask = cv2.inRange(imgHSV,lower,upper)
imgResult = cv2.bitwise_and(img,img,mask=mask)
# cv2.imshow("Original",img)
# cv2.imshow("HSV",imgHSV)
# cv2.imshow("Mask", mask)
# cv2.imshow("Result", imgResult)
imgStack = stackImages(0.6,([img,imgHSV],[mask,imgResult]))
cv2.imshow("Stacked Images", imgStack)
cv2.waitKey(1)
7、图像画框
import cv2
import numpy as np
def stackImages(scale,imgArray):
rows = len(imgArray)
cols = len(imgArray[0])
rowsAvailable = isinstance(imgArray[0], list)
width = imgArray[0][0].shape[1]
height = imgArray[0][0].shape[0]
if rowsAvailable:
for x in range ( 0, rows):
for y in range(0, cols):
if imgArray[x][y].shape[:2] == imgArray[0][0].shape [:2]:
imgArray[x][y] = cv2.resize(imgArray[x][y], (0, 0), None, scale, scale)
else:
imgArray[x][y] = cv2.resize(imgArray[x][y], (imgArray[0][0].shape[1], imgArray[0][0].shape[0]), None, scale, scale)
if len(imgArray[x][y].shape) == 2: imgArray[x][y]= cv2.cvtColor( imgArray[x][y], cv2.COLOR_GRAY2BGR)
imageBlank = np.zeros((height, width, 3), np.uint8)
hor = [imageBlank]*rows
hor_con = [imageBlank]*rows
for x in range(0, rows):
hor[x] = np.hstack(imgArray[x])
ver = np.vstack(hor)
else:
for x in range(0, rows):
if imgArray[x].shape[:2] == imgArray[0].shape[:2]:
imgArray[x] = cv2.resize(imgArray[x], (0, 0), None, scale, scale)
else:
imgArray[x] = cv2.resize(imgArray[x], (imgArray[0].shape[1], imgArray[0].shape[0]), None,scale, scale)
if len(imgArray[x].shape) == 2: imgArray[x] = cv2.cvtColor(imgArray[x], cv2.COLOR_GRAY2BGR)
hor= np.hstack(imgArray)
ver = hor
return ver
def getContours(img):
contours,hierarchy = cv2.findContours(img,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)
for cnt in contours:
area = cv2.contourArea(cnt)
print(area)
if area>500:
cv2.drawContours(imgContour, cnt, -1, (255, 0, 0), 3)
peri = cv2.arcLength(cnt,True)
#print(peri)
approx = cv2.approxPolyDP(cnt,0.02*peri,True)
print(len(approx))
objCor = len(approx)
x, y, w, h = cv2.boundingRect(approx)
if objCor ==3: objectType ="Tri"
elif objCor == 4:
aspRatio = w/float(h)
if aspRatio >0.98 and aspRatio <1.03: objectType= "Square"
else:objectType="Rectangle"
elif objCor>4: objectType= "Circles"
else:objectType="None"
cv2.rectangle(imgContour,(x,y),(x+w,y+h),(0,255,0),2)
cv2.putText(imgContour,objectType,
(x+(w//2)-10,y+(h//2)-10),cv2.FONT_HERSHEY_COMPLEX,0.7,
(0,0,0),2)
path = 'Resources/shapes.png'
img = cv2.imread(path)
imgContour = img.copy()
imgGray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
imgBlur = cv2.GaussianBlur(imgGray,(7,7),1)
imgCanny = cv2.Canny(imgBlur,50,50)
getContours(imgCanny)
imgBlank = np.zeros_like(img)
imgStack = stackImages(0.8,([img,imgGray,imgBlur],
[imgCanny,imgContour,imgBlank]))
cv2.imshow("Stack", imgStack)
cv2.waitKey(0)
8、人脸识别
import cv2
faceCascade= cv2.CascadeClassifier("Resources/haarcascade_frontalface_default.xml")
img = cv2.imread('Resources/lena.png')
imgGray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(imgGray,1.1,4)
for (x,y,w,h) in faces:
cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
cv2.imshow("Result", img)
cv2.waitKey(0)
9、小例子
例子1：VR画笔
import cv2
import numpy as np
#####################################################################
frameWidth = 640
frameHeight = 480
cap = cv2.VideoCapture(1)
cap.set(3, frameWidth)
cap.set(4, frameHeight)
cap.set(10,150)
myColors = [[5,107,0,19,255,255],
[133,56,0,159,156,255],
[57,76,0,100,255,255],
[90,48,0,118,255,255]]
myColorValues = [[51,153,255], ## BGR
[255,0,255],
[0,255,0],
[255,0,0]]
myColorValues = [[51,153,255], ## BGR
[255,0,255],
[0,255,0],
[255,0,0]]
myPoints = [] ## [x , y , colorId ]
######################################################################
def findColor(img,myColors,myColorValues):
imgHSV = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
count = 0
newPoints=[]
for color in myColors:
lower = np.array(color[0:3])
upper = np.array(color[3:6])
mask = cv2.inRange(imgHSV,lower,upper)
x,y=getContours(mask)
cv2.circle(imgResult,(x,y),15,myColorValues[count],cv2.FILLED)
if x!=0 and y!=0:
newPoints.append([x,y,count])
count +=1
#cv2.imshow(str(color[0]),mask)
return newPoints
def getContours(img):
contours,hierarchy = cv2.findContours(img,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)
x,y,w,h = 0,0,0,0
for cnt in contours:
area = cv2.contourArea(cnt)
if area>500:
#cv2.drawContours(imgResult, cnt, -1, (255, 0, 0), 3)
peri = cv2.arcLength(cnt,True)
approx = cv2.approxPolyDP(cnt,0.02*peri,True)
x, y, w, h = cv2.boundingRect(approx)
return x+w//2,y
def drawOnCanvas(myPoints,myColorValues):
for point in myPoints:
cv2.circle(imgResult, (point[0], point[1]), 10, myColorValues[point[2]], cv2.FILLED)
while True:
success, img = cap.read()
imgResult = img.copy()
newPoints = findColor(img, myColors,myColorValues)
if len(newPoints)!=0:
for newP in newPoints:
myPoints.append(newP)
if len(myPoints)!=0:
drawOnCanvas(myPoints,myColorValues)
cv2.imshow("Result", imgResult)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
例子2：文档校正
import cv2
import numpy as np
###################################
widthImg=540
heightImg =640
#####################################
cap = cv2.VideoCapture(1)
cap.set(10,150)
def preProcessing(img):
imgGray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
imgBlur = cv2.GaussianBlur(imgGray,(5,5),1)
imgCanny = cv2.Canny(imgBlur,200,200)
kernel = np.ones((5,5))
imgDial = cv2.dilate(imgCanny,kernel,iterations=2)
imgThres = cv2.erode(imgDial,kernel,iterations=1)
return imgThres
def getContours(img):
biggest = np.array([])
maxArea = 0
contours,hierarchy = cv2.findContours(img,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)
for cnt in contours:
area = cv2.contourArea(cnt)
if area>5000:
#cv2.drawContours(imgContour, cnt, -1, (255, 0, 0), 3)
peri = cv2.arcLength(cnt,True)
approx = cv2.approxPolyDP(cnt,0.02*peri,True)
if area >maxArea and len(approx) == 4:
biggest = approx
maxArea = area
cv2.drawContours(imgContour, biggest, -1, (255, 0, 0), 20)
return biggest
def reorder (myPoints):
myPoints = myPoints.reshape((4,2))
myPointsNew = np.zeros((4,1,2),np.int32)
add = myPoints.sum(1)
#print("add", add)
myPointsNew[0] = myPoints[np.argmin(add)]
myPointsNew[3] = myPoints[np.argmax(add)]
diff = np.diff(myPoints,axis=1)
myPointsNew[1]= myPoints[np.argmin(diff)]
myPointsNew[2] = myPoints[np.argmax(diff)]
#print("NewPoints",myPointsNew)
return myPointsNew
def getWarp(img,biggest):
biggest = reorder(biggest)
pts1 = np.float32(biggest)
pts2 = np.float32([[0, 0], [widthImg, 0], [0, heightImg], [widthImg, heightImg]])
matrix = cv2.getPerspectiveTransform(pts1, pts2)
imgOutput = cv2.warpPerspective(img, matrix, (widthImg, heightImg))
imgCropped = imgOutput[20:imgOutput.shape[0]-20,20:imgOutput.shape[1]-20]
imgCropped = cv2.resize(imgCropped,(widthImg,heightImg))
return imgCropped
def stackImages(scale,imgArray):
rows = len(imgArray)
cols = len(imgArray[0])
rowsAvailable = isinstance(imgArray[0], list)
width = imgArray[0][0].shape[1]
height = imgArray[0][0].shape[0]
if rowsAvailable:
for x in range ( 0, rows):
for y in range(0, cols):
if imgArray[x][y].shape[:2] == imgArray[0][0].shape [:2]:
imgArray[x][y] = cv2.resize(imgArray[x][y], (0, 0), None, scale, scale)
else:
imgArray[x][y] = cv2.resize(imgArray[x][y], (imgArray[0][0].shape[1], imgArray[0][0].shape[0]), None, scale, scale)
if len(imgArray[x][y].shape) == 2: imgArray[x][y]= cv2.cvtColor( imgArray[x][y], cv2.COLOR_GRAY2BGR)
imageBlank = np.zeros((height, width, 3), np.uint8)
hor = [imageBlank]*rows
hor_con = [imageBlank]*rows
for x in range(0, rows):
hor[x] = np.hstack(imgArray[x])
ver = np.vstack(hor)
else:
for x in range(0, rows):
if imgArray[x].shape[:2] == imgArray[0].shape[:2]:
imgArray[x] = cv2.resize(imgArray[x], (0, 0), None, scale, scale)
else:
imgArray[x] = cv2.resize(imgArray[x], (imgArray[0].shape[1], imgArray[0].shape[0]), None,scale, scale)
if len(imgArray[x].shape) == 2: imgArray[x] = cv2.cvtColor(imgArray[x], cv2.COLOR_GRAY2BGR)
hor= np.hstack(imgArray)
ver = hor
return ver
while True:
success, img = cap.read()
img = cv2.resize(img,(widthImg,heightImg))
imgContour = img.copy()
imgThres = preProcessing(img)
biggest = getContours(imgThres)
if biggest.size !=0:
imgWarped=getWarp(img,biggest)
# imageArray = ([img,imgThres],
# [imgContour,imgWarped])
imageArray = ([imgContour, imgWarped])
cv2.imshow("ImageWarped", imgWarped)
else:
# imageArray = ([img, imgThres],
# [img, img])
imageArray = ([imgContour, img])
stackedImages = stackImages(0.6,imageArray)
cv2.imshow("WorkFlow", stackedImages)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
例子3：车牌识别
import cv2
#############################################
frameWidth = 640
frameHeight = 480
nPlateCascade = cv2.CascadeClassifier("Resources/haarcascade_russian_plate_number.xml")
minArea = 200
color = (255,0,255)
###############################################
cap = cv2.VideoCapture("Resources/video12.mp4")
cap.set(3, frameWidth)
cap.set(4, frameHeight)
cap.set(10,150)
count = 0
while True:
success, img = cap.read()
imgGray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
numberPlates = nPlateCascade.detectMultiScale(imgGray, 1.1, 10)
for (x, y, w, h) in numberPlates:
area = w*h
if area >minArea:
cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 255), 2)
cv2.putText(img,"Number Plate",(x,y-5),
cv2.FONT_HERSHEY_COMPLEX_SMALL,1,color,2)
imgRoi = img[y:y+h,x:x+w]
cv2.imshow("ROI", imgRoi)
cv2.imshow("Result", img)
if cv2.waitKey(1) & 0xFF == ord('s'):
cv2.imwrite("Resources/Scanned/NoPlate_"+str(count)+".jpg",imgRoi)
cv2.rectangle(img,(0,200),(640,300),(0,255,0),cv2.FILLED)
cv2.putText(img,"Scan Saved",(150,265),cv2.FONT_HERSHEY_DUPLEX,
2,(0,0,255),2)
cv2.imshow("Result",img)
cv2.waitKey(500)
count +=1
