Affine transformation

Affine Transformation (Affine Transformation or Affine Map) is a linear transformation from two-dimensional coordinates (x, y) to two-dimensional coordinates (u, v).

Its mathematical expression is as follows.

The corresponding homogeneous coordinate matrix representation is:

Affine transformation maintains the "straightness" (a straight line remains a straight line after affine transformation) and "parallelism" of a two-dimensional figure (the relative position relationship between straight lines remains unchanged, parallel lines remain parallel lines after affine transformation, and the position order of points on the straight lines does not change). Three pairs of non-collinear corresponding points determine a unique affine transformation. The rotation and stretching of an image is the image affine transformation. Affine transformation also requires an M matrix, but because affine transformation is relatively complex, it is generally difficult to find this matrix directly. OpenCV provides a method to automatically solve M based on the correspondence between the three points before and after the transformation. This function is:

M=cv2.getAffineTransform(pos1,pos2)

The two positions are the corresponding position relationship before and after the transformation.

The output is the affine matrix M.

Then use the function cv2.warpAffine().

Code path:

x
~/dofbot_pro/dofbot_opencv/scripts/2.Transform/05_Radiation.ipynb

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import cv2
import   numpy as np
import   matplotlib.pyplot as plt
 
img =   cv2.imread('yahboom.jpg',1)
img_bgr2rgb   = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
plt.imshow(img_bgr2rgb)
plt.show()
#   cv2.waitKey(0)

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imgInfo =   img.shape
height =   imgInfo[0]
width =   imgInfo[1]
#src   3->dst 3 (Upper left corner,Lower left corner,Upper right corner)
matSrc =   np.float32([[0,0], [0,height-1], [width-1,0]])
matDst =   np.float32([[50,50], [300,height-200], [width-300,100]])
#combination
matAffine =   cv2.getAffineTransform(matSrc,matDst)# mat 1 src 2 dst
dst =   cv2.warpAffine(img,matAffine,(width,height))
img_bgr2rgb   = cv2.cvtColor(dst, cv2.COLOR_BGR2RGB)
plt.imshow(img_bgr2rgb)