使激光探测器在我的代码中有错误

本文介绍了使激光探测器在我的代码中有错误的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！

问题描述

我正在使用opencv库制作一个检测激光，圆和数字的程序.这是我第一次使用ros indigo，我真的不知道我在做什么，但是在运行程序时，我遇到了迅速重复出现的错误.这是我得到的错误:

I am making a program that detects lasers and circles and numbers then with the opencv library. This is my first time using ros indigo and I don't really know what I am doing but I am getting an error that is repeating at a rapid rate when I run my program. this is the error I am getting:

[错误] [WallTime:1565273888.861720]错误的回调:追溯(最近一次通话): _invoke_callback中的第720行的文件"/opt/ros/indigo/lib/python2.7/dist-packages/rospy/topics.py" cb(味精) 在回调中的文件"lazer3.py"，第89行 cv_image2 = self.convert_image(cv_image)NameError:未定义全局名称"self"

[ERROR] [WallTime: 1565273888.861720] bad callback:Traceback (most recent call last): File "/opt/ros/indigo/lib/python2.7/dist-packages/rospy/topics.py", line 720, in _invoke_callback cb(msg) File "lazer3.py", line 89, in callback cv_image2 = self.convert_image(cv_image)NameError: global name 'self' is not defined

该错误出现在显示cv_image2 = self.convert_image(cv_image)的行中，这是因为如果我删除了self，则使用self会得到另一个错误:

the error is in the line that says cv_image2 = self.convert_image(cv_image) and it is because I use the self if I delete self I get a different error:

[错误] [WallTime:1565274017.459066]错误的回调:追溯(最近一次通话): _invoke_callback中的第720行的文件"/opt/ros/indigo/lib/python2.7/dist-packages/rospy/topics.py" cb(味精) 在回调中的文件"lazer3.py"，第89行 cv_image2 = convert_image(cv_image) 在convert_image中的文件"lazer3.py"，第29行标签= measure.label(阈值，邻居= 8，背景= 0)AttributeError:模块"对象没有属性标签"

[ERROR] [WallTime: 1565274017.459066] bad callback:Traceback (most recent call last): File "/opt/ros/indigo/lib/python2.7/dist-packages/rospy/topics.py", line 720, in _invoke_callback cb(msg) File "lazer3.py", line 89, in callback cv_image2 = convert_image(cv_image) File "lazer3.py", line 29, in convert_image labels = measure.label(thresh, neighbors=8, background=0)AttributeError: 'module' object has no attribute 'label'

这是我的代码:

from __future__ import print_function
import cv2
import numpy as np
import imutils
from imutils import contours
from skimage import measure

'''
def getPoint(cameraTip,dotXY,normalPoint):
    slope= (cameraTip[2]-dotXY[2])/(cameraTip[1]-dotXY[1])
    b=cameraTip[2]-(slope*cameraTip[1])
    z=slope*normalPoint[1]+b
    return [normalPoint[0],normalPoint[1],z]
'''
# Image Processing functions
def convert_image(image): # Image of kind bgr8
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    blurred = cv2.GaussianBlur(gray, (11, 11), 0)
        #threshold the image to reveal light regions in the
        # blurred image
    thresh = cv2.threshold(blurred, 30, 255, cv2.THRESH_BINARY)[1]
        # perform a series of erosions and dilations to remove
        # any small blobs of noise from the thresholded image
    thresh = cv2.erode(thresh, None, iterations=2)
    thresh = cv2.dilate(thresh, None, iterations=4)
        # perform a connected component analysis on the thresholded
        # image, then initialize a mask to store only the "large"
        # components
    labels = measure.label(thresh, neighbors=8, background=0)
    mask = np.zeros(thresh.shape, dtype="uint8")

        # loop over the unique components
    for label in np.unique(labels):
            # if this is the background label, ignore it
        if label == 0:
            continue

            # otherwise, construct the label mask and count the
                # number of pixels
        labelMask = np.zeros(thresh.shape, dtype="uint8")
        labelMask[labels == label] = 255
        numPixels = cv2.countNonZero(labelMask)

                # if the number of pixels in the component is sufficiently
                # large, then add it to our mask of "large blobs"
        if numPixels > 300:
            mask = cv2.add(mask, labelMask)
    # find the contours in the mask, then sort them from left to
    # right
    cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
        cv2.CHAIN_APPROX_SIMPLE)
    cnts = imutils.grab_contours(cnts)
    cnts = contours.sort_contours(cnts)[0]

        # loop over the contours
    for (i, c) in enumerate(cnts):
            # draw the bright spot on the image
        (x, y, w, h) = cv2.boundingRect(c)
        ((cX, cY), radius) = cv2.minEnclosingCircle(c)
        #x and y center are cX and cY
        cv2.circle(image, (int(cX), int(cY)), int(radius),
            (0, 0, 255), 3)
        cv2.putText(image, "#{}".format(i + 1), (x, y - 15),
            cv2.FONT_HERSHEY_SIMPLEX, 0.45, (0, 0, 255), 2)

        # show the output image
    cv2.imshow("Image", image)
    cv2.waitKey(1)
        #camera.release()
    return image

# ROS Interface
if __name__ == "__main__":
    import rospy
    from cv_bridge import CvBridge, CvBridgeError
    from sensor_msgs.msg import Image
    bridge = CvBridge()
    def show_img(cv_image):
        (rows,cols,channels) = cv_image.shape
        if cols > 60 and rows > 60 :
            cv2.circle(cv_image, (50,50), 10, 255)
        cv2.imshow("Image window", cv_image)
        cv2.waitKey(3)
    image_pub = rospy.Publisher("image_topic_2", Image)
    def callback(data):
        try:
            cv_image = bridge.imgmsg_to_cv2(data, "bgr8")
            show_img(cv_image)
            cv_image2 = self.convert_image(cv_image)
            image_pub.publish(bridge.cv2_to_imgmsg(cv_image2, "bgr8"))
        except CvBridgeError as e:
            print(e)
    image_sub = rospy.Subscriber("CM_040GE/image_raw", Image, callback)
    rospy.init_node('image_converter', anonymous=True)
    rospy.spin()
    print("image_converter: Shutting down")
    cv2.destroyAllWindows()

我还想澄清一点，就是因为代码相似，所以这不是我最后一个问题的重复，因为我遇到了另一个错误，而且我在问一个完全独立的问题

also I want to make it clear that just because the code is the similar this is not a repeat of my last question because I was getting a different error and I was asking about a completely separate issue

rospy

使激光探测器在我的代码中有错误

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