12.perspective transformation

Perspective transformation is also called projection transformation. The affine transformation we often call is a special case of perspective transformation. The purpose of perspective transformation is to convert an object that is a straight line in reality into a straight line through perspective transformation, which may appear as a diagonal line in the picture. Perspective transformation can map a rectangle to an arbitrary quadrilateral. This technology will be used later when our robot drives autonomously. Perspective transformation via function:

dst = cv2. warpPerspective(src, M, dsize[,flag, [,borderMode[,borderValue]]])

dst : The output image after perspective transformation, dsize determines the actual size of the output.

src：Source Image

M：3X3 transformation matrix

dsize: Output image size

flags：Interpolation method, the default is INTER_LINEAR (bilinear interpolation). When it is WARP_INVERSE_MAP, it means that M is an inverse transformation, which can realize the inverse transformation from the target dst to src.

borderMode：Edge type. Default is BORDER_CONSTANT. When the value is BORDER_TRANSPARENT, the values in the target image are not changed. These values correspond to the outliers in the original image.

borderValue：Boundary value, defaults to 0. Just like affine transformation, OpenCV will still provide a function cv2.getPerspectiveTransform() to provide the transformation matrix above.

The function is as follows:

matAffine = cv2.getPerspectiveTransform(matSrc, matDst)

matSrc：Enter the four vertex coordinates of the image.

matDst：Output the four vertex coordinates of the image.

Code path：/home/dofbot/Dofbot/4.opencv/2.Transform/07_perspectivity.ipynb

​x
import cv2
import   numpy as np
import   matplotlib.pyplot as plt
img = cv2.imread('yahboom.jpg',1)

imgInfo =   img.shape
height =   imgInfo[0]
width =   imgInfo[1]
#src   4->dst 4 upper left corner, lower left corner, upper right corner, lower right corner)
matSrc =   np.float32([[200,100],[200,400],[600,100],[width-1,height-1]])
matDst =   np.float32([[200,200],[200,300],[500,200],[500,400]])
#combination

matAffine =   cv2.getPerspectiveTransform(matSrc,matDst)# mat 1 src 2 dst
dst =   cv2.warpPerspective(img,matAffine,(width,height))
img_bgr2rgb   = cv2.cvtColor(dst, cv2.COLOR_BGR2RGB)
plt.imshow(img_bgr2rgb)
    plt.show()