Welcome to NUWA-HP60C Depth Camera repository

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: 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, the default is 0. 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: input the four vertex coordinates of the image.

matDst: output the four vertex coordinates of the image.

• Start Docker

After entering the Raspberry Pi 5 desktop, open a terminal and run the following command to start the container corresponding to Dofbot:

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./Docker_Ros.sh

Access Jupyter Lab within Docker:

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IP:9999 // Example: 192.168.1.11:9999

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

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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()