title: Attribute Error in python problems
body: <p>import numpy as np
  import cv2
  import imutils
  import argparse</p>
  
  <p>class Stitcher:
      def <strong>init</strong>(self):
          # determine if we are using OpenCV v3.X
          self.isv3 = imutils.is_cv3()</p>
  
  <pre><code>def stitch(self, images, ratio=0.75, reprojThresh=4.0,
      showMatches=False):
      (imageB, imageA) = images
      (kpsA, featuresA) = self.detectAndDescribe(imageA)
      (kpsB, featuresB) = self.detectAndDescribe(imageB)
  
      # match features between the two images
      M = self.matchKeypoints(kpsA, kpsB,
          featuresA, featuresB, ratio, reprojThresh)
  
      if M is None:
          return None
  
      # apply a perspective warp to stitch the images
      (matches, H, status) = M
      result = cv2.warpPerspective(imageA, H,
          (imageA.shape[1] + imageB.shape[1], imageA.shape[0]))
      result[0:imageB.shape[0], 0:imageB.shape[1]] = imageB
  
      # check to see if the keypoint matches should be visualized
      if showMatches:
          vis = self.drawMatches(imageA, imageB, kpsA, kpsB, matches,
              status)
  
          # return a tuple of the stitched image and the
          # visualization
          return (result, vis)
  
      # return the stitched image
      return result
  
  def detectAndDescribe(self, image):
  
      gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
  
  
      if self.isv3:
          orb = cv2.ORB_create()
  
          (kps, features) = orb.detectAndCompute(image, None)
  
      # If we are using OpenCV 2.4.X
      else:
          # detect keypoints in the image
          detector = cv2.FeatureDetector_create("ORB")
          kps = detector.detect(gray)
  
          # extract features from the image
          extractor = cv2.DescriptorExtractor_create("ORB")
          (kps, features) = extractor.compute(gray, kps)
  
      # convert the keypoints to NumPy arrays
      kps = np.float32([kp.pt for kp in kps])
  
      # return a tuple of keypoints and features
      return (kps, features)
  
  def matchKeypoints(self, kpsA, kpsB, featuresA, featuresB,
      ratio, reprojThresh):
      # compute the raw matches and initialize the list of actual matches
      matcher = cv2.DescriptorMatcher_create("BruteForce")
      rawMatches = matcher.knnMatch(featuresA, featuresB, 2)
      matches = []
  
      # loop over the raw matches
      for m in rawMatches:
          # ensure the distance is within a certain ratio of each
          # other (i.e. Lowe's ratio test)
          if len(m) == 2 and m[0].distance &lt; m[1].distance * ratio:
              matches.append((m[0].trainIdx, m[0].queryIdx))
  
      # computing a homography requires at least 4 matches
      if len(matches) &gt; 4:
          # construct the two sets of points
          ptsA = np.float32([kpsA[i] for (_, i) in matches])
          ptsB = np.float32([kpsB[i] for (i, _) in matches])
  
          # homography between the two sets of points
          (H, status) = cv2.findHomography(ptsA, ptsB, cv2.RANSAC,
              reprojThresh)
  
          # return the matches along with the homograpy matrix
          # and status of each matched point
          return (matches, H, status)
  
      return None
  
  def drawMatches(self, imageA, imageB, kpsA, kpsB, matches, status):
      # initialize the output visualization image
      (hA, wA) = imageA.shape[:2]
      (hB, wB) = imageB.shape[:2]
      vis = np.zeros((max(hA, hB), wA + wB, 3), dtype="uint8")
      vis[0:hA, 0:wA] = imageA
      vis[0:hB, wA:] = imageB
  
      # loop over the matches
      for ((trainIdx, queryIdx), s) in zip(matches, status):
          # matching if the keypoint is matched
          if s == 1:
              # draw the match
              ptA = (int(kpsA[queryIdx][0]), int(kpsA[queryIdx][1]))
              ptB = (int(kpsB[trainIdx][0]) + wA, int(kpsB[trainIdx][1]))
              cv2.line(vis, ptA, ptB, (240, 255, 100), 1)
  
      # return the visualization
      return vis
  
  
  
  Output:: Attribute Error: 'module' object has no attribute 'is_cv3
  </code></pre>
  
  <p>Please check the code and resend the edited code to solve the problem.</p>