OpenCV 3.0 行迭代器 [英] OpenCV 3.0 LineIterator

问题描述

我想使用 LineIterator在使用 Python 的 OpenCV 3.0 中，它是否仍可用于为 Python 构建的 OpenCV 3.0?看来网上的答案都指向cv.InitLineIterator，它是cv 模块的一部分.我试过导入这个模块，但它似乎没有包含在当前版本中.是否已重命名或严格删除?

I want to use the LineIterator in OpenCV 3.0 using Python, is it still available with OpenCV 3.0 built for Python? It seems that the answers on the internet are all pointing to cv.InitLineIterator which is part of the cv module. I've tried importing this module but it seems like it is not included with the current build. Has it been renamed or strictly just removed?

推荐答案

我已经解决了我自己的问题.行迭代器似乎在 cv2 库中不可用.因此，我制作了自己的行迭代器.没有使用循环，所以它应该很快.如果有人需要，这里是代码:

I've solved my own problem. Line iterator seems to be unavailable in the cv2 library. Therefore, I made my own line iterator. No loops are used, so it should be pretty fast. Here is the code if anybody needs it:

def createLineIterator(P1, P2, img):
    """
    Produces and array that consists of the coordinates and intensities of each pixel in a line between two points

    Parameters:
        -P1: a numpy array that consists of the coordinate of the first point (x,y)
        -P2: a numpy array that consists of the coordinate of the second point (x,y)
        -img: the image being processed

    Returns:
        -it: a numpy array that consists of the coordinates and intensities of each pixel in the radii (shape: [numPixels, 3], row = [x,y,intensity])     
    """
   #define local variables for readability
   imageH = img.shape[0]
   imageW = img.shape[1]
   P1X = P1[0]
   P1Y = P1[1]
   P2X = P2[0]
   P2Y = P2[1]

   #difference and absolute difference between points
   #used to calculate slope and relative location between points
   dX = P2X - P1X
   dY = P2Y - P1Y
   dXa = np.abs(dX)
   dYa = np.abs(dY)

   #predefine numpy array for output based on distance between points
   itbuffer = np.empty(shape=(np.maximum(dYa,dXa),3),dtype=np.float32)
   itbuffer.fill(np.nan)

   #Obtain coordinates along the line using a form of Bresenham's algorithm
   negY = P1Y > P2Y
   negX = P1X > P2X
   if P1X == P2X: #vertical line segment
       itbuffer[:,0] = P1X
       if negY:
           itbuffer[:,1] = np.arange(P1Y - 1,P1Y - dYa - 1,-1)
       else:
           itbuffer[:,1] = np.arange(P1Y+1,P1Y+dYa+1)              
   elif P1Y == P2Y: #horizontal line segment
       itbuffer[:,1] = P1Y
       if negX:
           itbuffer[:,0] = np.arange(P1X-1,P1X-dXa-1,-1)
       else:
           itbuffer[:,0] = np.arange(P1X+1,P1X+dXa+1)
   else: #diagonal line segment
       steepSlope = dYa > dXa
       if steepSlope:
           slope = dX.astype(np.float32)/dY.astype(np.float32)
           if negY:
               itbuffer[:,1] = np.arange(P1Y-1,P1Y-dYa-1,-1)
           else:
               itbuffer[:,1] = np.arange(P1Y+1,P1Y+dYa+1)
           itbuffer[:,0] = (slope*(itbuffer[:,1]-P1Y)).astype(np.int) + P1X
       else:
           slope = dY.astype(np.float32)/dX.astype(np.float32)
           if negX:
               itbuffer[:,0] = np.arange(P1X-1,P1X-dXa-1,-1)
           else:
               itbuffer[:,0] = np.arange(P1X+1,P1X+dXa+1)
           itbuffer[:,1] = (slope*(itbuffer[:,0]-P1X)).astype(np.int) + P1Y

   #Remove points outside of image
   colX = itbuffer[:,0]
   colY = itbuffer[:,1]
   itbuffer = itbuffer[(colX >= 0) & (colY >=0) & (colX<imageW) & (colY<imageH)]

   #Get intensities from img ndarray
   itbuffer[:,2] = img[itbuffer[:,1].astype(np.uint),itbuffer[:,0].astype(np.uint)]

   return itbuffer

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