Opencv 学习笔记（二）——三小时精通Opencv（Project）

参考：2020最新-3h精通Opencv

代码

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1.颜色识别

cv2.imread()和cv2.cvtColor() 的使用

cv2.imread()和cv2.cvtColor() 的使用

1、cv2.imread()接口读图像，读进来直接是BGR 格式数据格式在 0~255
需要特别注意的是图片读出来的格式是BGR，不是我们最常见的RGB格式，颜色肯定有区别。
2、cv2.cvtColor(p1,p2) 是颜色空间转换函数，p1是需要转换的图片，p2是转换成何种格式。
cv2.COLOR_BGR2RGB 将BGR格式转换成RGB格式
cv2.COLOR_BGR2GRAY 将BGR格式转换成灰度图片

cv2.circle()

cv2.circle(img, center, radius, color[, thickness[, lineType[, shift]]])
作用
根据给定的圆心和半径等画圆
参数说明
img：输入的图片data
center：圆心位置
radius：圆的半径
color：圆的颜色
thickness：圆形轮廓的粗细（如果为正）。负厚度表示要绘制实心圆。
lineType： 圆边界的类型。
shift：中心坐标和半径值中的小数位数。

完整代码：

import cv2
import numpy as np

frameWidth = 640
frameHeight = 480
cap = cv2.VideoCapture(0)
#cap = cv2.VideoCapture(0, cv2.CAP_DSHOW)
cap.set(3, frameWidth)
cap.set(4, frameHeight)
cap.set(10,150)

#添加可以识别的颜色
myColors = [[5,107,0,19,255,255],
            [133,56,0,159,156,255],
            [57,76,0,100,255,255]]
myColorValues = [[51,153,255],
                 [255,0,255],
                 [0,255,0]]


def findColor(img,myColors,myColorValues):
    imgHSV = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
    count = 0
    for color in myColors:

        lower = np.array(color[0:3])  #返回集合中，下标0至3的集合
        upper = np.array(color[3:6])
        mask = cv2.inRange(imgHSV, lower, upper)

        x,y = getContours(mask)

        cv2.circle(imgResult,(x,y),10,myColorValues[count],cv2.FILLED)
        count += 1
        #cv2.imshow(str(color[0]),mask)


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)
        print(area)
        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


while True:
    success, img = cap.read()
    imgResult = img.copy()

    findColor(img, myColors, myColorValues)
    cv2.imshow("Result", imgResult)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

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2.识别+提取 图片内容

完整代码：

import cv2
import numpy as np


###################################
widthImg=540
heightImg =640
#####################################

cap = cv2.VideoCapture(0)

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)    #边缘检测

    # 给边缘加粗
    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)     #计算边数
            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)    # 获取最大轮廓
    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()
    #使用摄像头
    #img = cv2.resize(img,(widthImg,heightImg))

    #使用图片
    img = cv2.imread("Resources/paper.jpg")
    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