我尝试使用反向扭曲变形两张人脸图像。我有两张图像的Delaunay三角形以及所有对应三角形对的所有变换矩阵。x1c 0d1x
我已经将矩阵应用于三角形内的每个像素，但我得到的图像都很混乱，有些像素也没有填充。

我怀疑顶点列表没有按顺序排列，这意味着三角形没有对应。或者可能只是我搞乱了行，列的顺序。
下面是我的代码：

from scipy.spatial import Delaunay
from skimage.draw import polygon
import numpy as np

def drawDelaunay(img, landmarks, color):
    tri = Delaunay(landmarks)
    vertices = []

    for t in landmarks[tri.simplices]:
        # t = [int(i) for i in t]
        pt1 = [t[0][0], t[0][1]]
        pt2 = [t[1][0], t[1][1]]
        pt3 = [t[2][0], t[2][1]]

        cv2.line(img, pt1, pt2, color, 1, cv2.LINE_AA, 0)
        cv2.line(img, pt2, pt3, color, 1, cv2.LINE_AA, 0)
        cv2.line(img, pt3, pt1, color, 1, cv2.LINE_AA, 0)    

        vertices.append([pt1, pt2, pt3])
    return img, vertices

def getAffineMat(triangle1, triangle2):
    x = np.transpose(np.matrix([*triangle1]))
    y = np.transpose(np.matrix([*triangle2]))

    # Add ones to bottom of x and y
    x = np.vstack((x, [1,1,1]))
    y = np.vstack((y, [1,1,1]))

    xInv = np.linalg.pinv(x)
    return np.dot(y, xInv)

srcImg = face2
srcRows, srcCols, srcDepth = face2.shape
destImg = np.zeros(face1.shape, dtype=np.uint8)

for triangle1, triangle2 in zip(vertices1, vertices2):
    transMat = getAffineMat(triangle1, triangle2)
    r, c = list(map(list, zip(*triangle2)))
    rr, cc = polygon(r, c)

    for row, col in zip(rr, cc):
        transformed = np.dot(transMat, [col, row, 1])
        srcX, srcY, *_ = np.array(transformed.T)

        # Check if pixel is within image boundaries   
        if isWithinBounds(srcCols, srcRows, col, row):
            # Interpolate the color of the pixel from the four nearest pixels
            color = bilinearInterpolation(srcImg, srcX, srcY)
            
            # Set the color of the current pixel in the destination image
            destImg[row, col] = color

我希望实现这没有getAffineTransform或warpAffine。任何帮助将不胜感激！
资料来源：

1. Transfer coordinates from one triangle to another triangle
2. https://devendrapratapyadav.github.io/FaceMorphing/