执行透视扭曲时，如何避免图像部分被剪切？

Question

我试着改变图像的透视图，这样我得到的结果就是前视图的透视图。我正在使用cv2.0透视函数。但是，在执行扭曲时，图像的某些部分会被切断。我怎样才能避免这种情况？我认为的一个选择是找到图像特定部分的变换矩阵，然后将该矩阵应用于整个图像。然而，这种方法并没有产生令人满意的结果

我使用的代码是：

    import numpy as np
    import cv2
    from google.colab.patches import cv2_imshow
    img = cv2.imread("drive/My Drive/Images_for_Adarsh/DSC_0690.JPG")

    height,width = 1000,1500
    img = cv2.resize(img,(width,height))

    pts1 = np.float32([[ 250, 0],[1220, 300],[1300, 770],[ 250, 860]])
    pts2 = np.float32([[0,0],[width,0],[width,height],[0,height]])
    matrix = cv2.getPerspectiveTransform(pts1,pts2)


    print(matrix.shape)
    print(matrix)
    imgOutput = cv2.warpPerspective(img,matrix,(width,height))
    cv2_imshow(imgOutput)
    cv2.imwrite("drive/My Drive/PerspectiveWarp-Results1/0690_coarse/0690([[ 250, 0],[1220, 300],[1300, 770],[ 250, 860]]).JPG",imgOutput)

输入图像：

扭曲的图像：

Answer 1

下面是一种在Python/OpenCV中扭曲图像并添加额外空间的简单方法，该空间将包含更多的输入，但将输入之外的区域作为透明区域

输入：

import numpy as np
import cv2

# read input
img = cv2.imread("building.jpg")

# resize
height,width = 1000,1500
img = cv2.resize(img, (width,height))

# specify conjugate coordinates and shift output on left and top by 500
pts1 = np.float32([[ 250, 0],[1220, 300],[1300, 770],[ 250, 860]])
pts2 = np.float32([[+500,+500],[width+500,+500],[width+500,height+500],[+500,height+500]])

# compute perspective matrix
matrix = cv2.getPerspectiveTransform(pts1,pts2)

print(matrix.shape)
print(matrix)

# convert image to BGRA with opaque alpha
img = cv2.cvtColor(img, cv2.COLOR_BGR2BGRA)

# do perspective transformation setting area outside input to transparent
# extend output size so extended by 500 all around
imgOutput = cv2.warpPerspective(img, matrix, (width+1000,height+1000), cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT, borderValue=(0,0,0,0))

# resize output, since it is too large to post
imgOutput = cv2.resize(imgOutput, (width,height))
    
# save the warped output
cv2.imwrite("building_warped.png", imgOutput)

# show the result
cv2.imshow("result", imgOutput)
cv2.waitKey(0)
cv2.destroyAllWindows()

注意：应该可以使用矩阵将输入角点投影到输出域，并计算所需的输出大小以容纳所有扭曲的输入