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所以这是我第一次使用opencv。我把它安装在我的树莓派上。我正在使用我在教科书上找到的一个项目来测试它，我收到错误（-215）

OpenCV 错误： cvtColor 中的断言失败 ((scn == 3 || scn == 4) && (depth == CV_8U || depth == CV_32F))，文件 /build/opencv-ISmtkH/opencv-2.4.9.1+dfsg /modules/imgproc/src/color.cpp，第 3959 行 Traceback（最近一次调用最后）：文件“balltracking.py”，第 50 行，在 hsv = cv2.cvtColor(frame,cv2.COLOR_BGR2HSV) cv2.error: /build /opencv-ISmtkH/opencv-2.4.9.1+dfsg/modules/imgproc/src/color.cpp:3959: 错误：(-215) (scn == 3 || scn == 4) && (depth == CV_8U | | 函数 cvtColor 中的深度 == CV_32F)

我正在测试的代码如下：

    import cv2
import cv2.cv as cv
import numpy as np

kernel = np.ones((5,5),np.uint8)

# Take input from webcam
cap = cv2.VideoCapture(-1)

# Reduce the size of video to 320x240 so rpi can process faster
cap.set(3,320)
cap.set(4,240)

def nothing(x):
    pass
# Creating a windows for later use
cv2.namedWindow('HueComp')
cv2.namedWindow('SatComp')
cv2.namedWindow('ValComp')
cv2.namedWindow('closing')
cv2.namedWindow('tracking')


# Creating track bar for min and max for hue, saturation and value
# You can adjust the defaults as you like
cv2.createTrackbar('hmin', 'HueComp',12,179,nothing)
cv2.createTrackbar('hmax', 'HueComp',37,179,nothing)

cv2.createTrackbar('smin', 'SatComp',96,255,nothing)
cv2.createTrackbar('smax', 'SatComp',255,255,nothing)

cv2.createTrackbar('vmin', 'ValComp',186,255,nothing)
cv2.createTrackbar('vmax', 'ValComp',255,255,nothing)

# My experimental values
# hmn = 12
# hmx = 37
# smn = 145
# smx = 255
# vmn = 186
# vmx = 255


while(1):

    buzz = 0
    _, frame = cap.read()

    #converting to HSV
    hsv = cv2.cvtColor(frame,cv2.COLOR_BGR2HSV)
    hue,sat,val = cv2.split(hsv)

    # get info from track bar and appy to result
    hmn = cv2.getTrackbarPos('hmin','HueComp')
    hmx = cv2.getTrackbarPos('hmax','HueComp')


    smn = cv2.getTrackbarPos('smin','SatComp')
    smx = cv2.getTrackbarPos('smax','SatComp')


    vmn = cv2.getTrackbarPos('vmin','ValComp')
    vmx = cv2.getTrackbarPos('vmax','ValComp')

    # Apply thresholding
    hthresh = cv2.inRange(np.array(hue),np.array(hmn),np.array(hmx))
    sthresh = cv2.inRange(np.array(sat),np.array(smn),np.array(smx))
    vthresh = cv2.inRange(np.array(val),np.array(vmn),np.array(vmx))

    # AND h s and v
    tracking = cv2.bitwise_and(hthresh,cv2.bitwise_and(sthresh,vthresh))

    # Some morpholigical filtering
    dilation = cv2.dilate(tracking,kernel,iterations = 1)
    closing = cv2.morphologyEx(dilation, cv2.MORPH_CLOSE, kernel)
    closing = cv2.GaussianBlur(closing,(5,5),0)

    # Detect circles using HoughCircles
    circles = cv2.HoughCircles(closing,cv.CV_HOUGH_GRADIENT,2,120,param1=120,param2=50,minRadius=10,maxRadius=0)
    # circles = np.uint16(np.around(circles))

    #Draw Circles
    if circles is not None:
            for i in circles[0,:]:
                # If the ball is far, draw it in green
                if int(round(i[2])) < 30:
                    cv2.circle(frame,(int(round(i[0])),int(round(i[1]))),int(round(i[2])),(0,255,0),5)
                    cv2.circle(frame,(int(round(i[0])),int(round(i[1]))),2,(0,255,0),10)
                # else draw it in red
                elif int(round(i[2])) > 35:
                    cv2.circle(frame,(int(round(i[0])),int(round(i[1]))),int(round(i[2])),(0,0,255),5)
                    cv2.circle(frame,(int(round(i[0])),int(round(i[1]))),2,(0,0,255),10)
                    buzz = 1

    #you can use the 'buzz' variable as a trigger to switch some GPIO lines on Rpi :)
    # print buzz                    
    # if buzz:
        # put your GPIO line here


    #Show the result in frames
    cv2.imshow('HueComp',hthresh)
    cv2.imshow('SatComp',sthresh)
    cv2.imshow('ValComp',vthresh)
    cv2.imshow('closing',closing)
    cv2.imshow('tracking',frame)

    k = cv2.waitKey(5) & 0xFF
    if k == 27:
        break

cap.release()

cv2.destroyAllWindows()
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1 回答 1

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您可以检查 numpy 数组的数据类型，hsv.dtype它应该是错误消息 CV_8U 或 CV_32F 中列出的类型之一。opencv 告诉你的是它需要 uint8 或 float32 的 dtype。要转换您的数组，您可以使用hsv.astype(np.uint8)它将您的数组转换为 uint8。

在检查数据类型时，我还想检查数组使用的形状：hsv.shape如果您有彩色图像，这应该输出类似 (rows,cols, 3) 的内容。

于 2017-04-04T23:22:05.150 回答