Question

我用opencv编写了一个python代码来检测一个矩形（显示高度和宽度）也确定了从相机到对象的距离但是当我运行代码时我得到了这个错误（可以在下面找到）我不要＆＃ 39;不知道我做错了什么，如果有人能帮助我，我会很感激，我已经尝试了所有可能的解决方案，但我仍然无法摆脱错误。

错误

yuv_red = cv2.cvtColor（frame，cv2.COLOR_BGR2YUV）错误：C：\ builds \ master_PackSlaveAddon-win32-vc12-static \ opencv \ modules \ imgproc \ src \ color.cpp：8059：错误：（-215）scn == 3 ||函数cv :: cvtColor中的scn == 4

  import sys
sys.path.append('C:\Python27\Lib\site-packages')
import cv2
import numpy as np
import argparse
import math

############################# Capturing Video Through Camera ########################
cap = cv2.VideoCapture(0)

############# Distance to Camera initial value set to zero ##########################
Distance_to_Camera=0

while(True):

#################################  Capture frame-by-frame ###########################
    ret, frame = cap.read()

############################ Converting frame(img i.e BGR to YUV) ###################
    yuv_red = cv2.cvtColor(frame, cv2.COLOR_BGR2YUV)

    red_color = np.uint8([[[0,0,255]]])
    yuv_color = cv2.cvtColor(red_color,cv2.COLOR_BGR2YUV)
    print yuv_color

############################### Processing of Image  ##############################

#####################   Defining the Range of Red Colour  ###########################
    red_lower = np.array([136,87,111],np.uint8)
    red_upper = np.array([180,255,255],np.uint8)

##################### Finding the Range of Red Colour in the image ###################
    mask = cv2.inRange(yuv_red, red_lower,red_upper)

####################### Morphological Transformation, Dilation #######################   

    res = cv2.bitwise_and(frame, frame, mask = mask)

##################################################################################### 
    gray = cv2.cvtColor(res,cv2.COLOR_BGR2GRAY)      #Converting the BGR res to Gray
    blurred = cv2.GaussianBlur(gray, (5,5), 5)       #Blur Image to remove noise  
    blur = cv2.bilateralFilter(blurred, 5,50,50)     #Smooth the image
    median = cv2.medianBlur(blur,5)                  #Reduce noise from image 
    thresh = cv2.threshold(median, 3, 255, cv2.THRESH_BINARY)[1] #To achieve a better output of white and black

    frame2, contour, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)

#####################  Splitting and Merging Image channels ###########################
    b,g,r = cv2.split(res)
    ttl = res.size/3
    Ra = float(np.sum(r))/ ttl
    print Ra

    if Ra > 1:
        c = contours[0]
        M = cv2.moments(c)
        x = int(M['m10']/M['m00'])
        y = int(M['m01']/M['m00'])

        x,y,w,h = cv2.boundingRect(c)
        epsilon = 0.01*cv2.arcLength(c, True)
        approx = cv2.approxPolyDP(c, epsilon, True)
        perimeter = cv2.approxLength(c,True)
        area = cv2.contourArea(c)
        ah = h/40
        aw = w/40



        Distance_to_Camera = round(math.sqrt(315/area),4)
        print Distance_to_Camera

        approx = cv2.approxPolyDP(c, epsilon, True)
        print   len(approx)
        shape = len(approx)

        if shape == 4:
            print " 4 Sides"
            rect = cv2.minAreaRect(c)
            box = cv2.boxPoints(rect)
            box = np.int0(box)
            cv2.drawContours(frame,ArithmeticError[box],0,(0,0,255),0)
            print box

        if ah == aw:
################################  Displaying Text on the Image ################################
            print "Unknown"
            cv2.putTextputText(frame,"Unknown",(x+150,y+150),cv2.FONT_HERSHEY_SIMPLEX,2,(255,255,255),4)
        else:

 ################################  Displaying Text on the Image ################################           

            print "Rectangle"
            cv2.putTextputText(frame,"Rectangle",(x+150,y+150),cv2.FONT_HERSHEY_SIMPLEX,2,(255,255,255),4)

            output = ("Distance="+str((round((distance+0.0004)*1000))) + "cm" + "X=" + str(aw)+"cm" +"Y="+str(ah)+"cm"+"Perimeter=" +str(round(perimeter/40))+"cm"+"Area="+str(round((area/1.64)/1000))+"cm^2")
            cv2.imshow('gray',frame)

    else:
        cv2.imshow('gray',frame)

##########################################  Output ##########################################
        cv2.imshow('gray',frame)
        cv2.imshow('grayscaled',thresh)

    if cv2.waitKey(20) & 0xFF == 27:
        break

##if k == 27:         # wait for ESC key to exit
##    cv2.destroyAllWindows()

# When everything done, release the capture
    cv2.destroyAllWindows()
    cap.release()



















  [1]: https://i.stack.imgur.com/qB2rx.png

Answer 1

在实现双边过滤器的行中，您有一个错误的括号：

blur = cv2.bilateralFilter(blurred, (5,50,50)

查看docs for cv2.bilateralFilter()以查看正确的用法。

使用Opencv python2.7检测矩形

1 个答案: