我尝试为warpPerspective（）函数指定一个与基本（0,0）不同的原点，以便独立于支持图像大小应用变换。我在原始代码中添加了一个CvPoint参数，但是我找不到使用这些坐标的位置。我试图在X0，Y0和W0的计算中使用它们，但它不起作用，这只是在生成的图像中移动变换后的图像。有什么想法吗？
这里是代码：
void warpPerspective( const Mat& src, Mat& dst, const Mat& M0, Size dsize,
int flags, int borderType, const Scalar& borderValue, CvPoint origin )
{
dst.create( dsize, src.type() );
const int BLOCK_SZ = 32;
short XY[BLOCK_SZ*BLOCK_SZ*2], A[BLOCK_SZ*BLOCK_SZ];
double M[9];
Mat _M(3, 3, CV_64F, M);
int interpolation = flags & INTER_MAX;
if( interpolation == INTER_AREA )
interpolation = INTER_LINEAR;
CV_Assert( (M0.type() == CV_32F || M0.type() == CV_64F) && M0.rows == 3 && M0.cols == 3 );
M0.convertTo(_M, _M.type());
if( !(flags & WARP_INVERSE_MAP) )
invert(_M, _M);
int x, y, x1, y1, width = dst.cols, height = dst.rows;
int bh0 = std::min(BLOCK_SZ/2, height);
int bw0 = std::min(BLOCK_SZ*BLOCK_SZ/bh0, width);
bh0 = std::min(BLOCK_SZ*BLOCK_SZ/bw0, height);
for( y = 0; y < height; y += bh0 )
{
for( x = 0; x < width; x += bw0 )
{
int bw = std::min( bw0, width - x);
int bh = std::min( bh0, height - y);
Mat _XY(bh, bw, CV_16SC2, XY), _A;
Mat dpart(dst, Rect(x, y, bw, bh));
for( y1 = 0; y1 < bh; y1++ )
{
short* xy = XY + y1*bw*2;
double X0 = M[0]*x + M[1]*(y + y1) + M[2];
double Y0 = M[3]*x + M[4]*(y + y1) + M[5];
double W0 = M[6]*x + M[7]*(y + y1) + M[8];
if( interpolation == INTER_NEAREST )
for( x1 = 0; x1 < bw; x1++ )
{
double W = W0 + M[6]*x1;
W = W ? 1./W : 0;
int X = saturate_cast<int>((X0 + M[0]*x1)*W);
int Y = saturate_cast<int>((Y0 + M[3]*x1)*W);
xy[x1*2] = (short)X;
xy[x1*2+1] = (short)Y;
}
else
{
short* alpha = A + y1*bw;
for( x1 = 0; x1 < bw; x1++ )
{
double W = W0 + M[6]*x1;
W = W ? INTER_TAB_SIZE/W : 0;
int X = saturate_cast<int>((X0 + M[0]*x1)*W);
int Y = saturate_cast<int>((Y0 + M[3]*x1)*W);
xy[x1*2] = (short)(X >> INTER_BITS);
xy[x1*2+1] = (short)(Y >> INTER_BITS);
alpha[x1] = (short)((Y & (INTER_TAB_SIZE-1))*INTER_TAB_SIZE +
(X & (INTER_TAB_SIZE-1)));
}
}
}
if( interpolation == INTER_NEAREST )
remap( src, dpart, _XY, Mat(), interpolation, borderType, borderValue );
else
{
Mat _A(bh, bw, CV_16U, A);
remap( src, dpart, _XY, _A, interpolation, borderType, borderValue );
}
}
}
}
答案 0 :(得分：5)
好的，我自己找到了！你有两件事要做：
以下是如此转换的代码：
void warpPerspective( const Mat& src, Mat& dst, const Mat& M0, Size dsize,
int flags, int borderType, const Scalar& borderValue, CvPoint origin )
{
dst.create( dsize, src.type() );
const int BLOCK_SZ = 32;
short XY[BLOCK_SZ*BLOCK_SZ*2], A[BLOCK_SZ*BLOCK_SZ];
double M[9];
Mat _M(3, 3, CV_64F, M);
int interpolation = flags & INTER_MAX;
if( interpolation == INTER_AREA )
interpolation = INTER_LINEAR;
CV_Assert( (M0.type() == CV_32F || M0.type() == CV_64F) && M0.rows == 3 && M0.cols == 3 );
M0.convertTo(_M, _M.type());
if( !(flags & WARP_INVERSE_MAP) )
invert(_M, _M);
int x, xDest, y, yDest, x1, y1, width = dst.cols, height = dst.rows;
int bh0 = std::min(BLOCK_SZ/2, height);
int bw0 = std::min(BLOCK_SZ*BLOCK_SZ/bh0, width);
bh0 = std::min(BLOCK_SZ*BLOCK_SZ/bw0, height);
for( y = -origin.y, yDest = 0; y < height; y += bh0, yDest += bh0 )
{
for( x = -origin.x, xDest = 0; x < width; x += bw0, xDest += bw0 )
{
int bw = std::min( bw0, width - x);
int bh = std::min( bh0, height - y);
// to avoid dimensions errors
if (bw <= 0 || bh <= 0)
break;
Mat _XY(bh, bw, CV_16SC2, XY), _A;
Mat dpart(dst, Rect(xDest, yDest, bw, bh));
for( y1 = 0; y1 < bh; y1++ )
{
short* xy = XY + y1*bw*2;
double X0 = M[0]*x + M[1]*(y + y1) + M[2];
double Y0 = M[3]*x + M[4]*(y + y1) + M[5];
double W0 = M[6]*x + M[7]*(y + y1) + M[8];
if( interpolation == INTER_NEAREST )
for( x1 = 0; x1 < bw; x1++ )
{
double W = W0 + M[6]*x1;
W = W ? 1./W : 0;
int X = saturate_cast<int>((X0 + M[0]*x1)*W);
int Y = saturate_cast<int>((Y0 + M[3]*x1)*W);
xy[x1*2] = (short)X;
xy[x1*2+1] = (short)Y;
}
else
{
short* alpha = A + y1*bw;
for( x1 = 0; x1 < bw; x1++ )
{
double W = W0 + M[6]*x1;
W = W ? INTER_TAB_SIZE/W : 0;
int X = saturate_cast<int>((X0 + M[0]*x1)*W);
int Y = saturate_cast<int>((Y0 + M[3]*x1)*W);
xy[x1*2] = (short)(X >> INTER_BITS) + origin.x;
xy[x1*2+1] = (short)(Y >> INTER_BITS) + origin.y;
alpha[x1] = (short)((Y & (INTER_TAB_SIZE-1))*INTER_TAB_SIZE +
(X & (INTER_TAB_SIZE-1)));
}
}
}
if( interpolation == INTER_NEAREST )
remap( src, dpart, _XY, Mat(), interpolation, borderType, borderValue );
else
{
Mat _A(bh, bw, CV_16U, A);
remap( src, dpart, _XY, _A, interpolation, borderType, borderValue );
}
}
}
}
使用此功能：
CvPoint transformPoint(const CvPoint pointToTransform, const CvMat* matrix) {
double coordinates[3] = {pointToTransform.x, pointToTransform.y, 1};
CvMat originVector = cvMat(3, 1, CV_64F, coordinates);
CvMat transformedVector = cvMat(3, 1, CV_64F, coordinates);
cvMatMul(matrix, &originVector, &transformedVector);
CvPoint outputPoint = cvPoint((int)(cvmGet(&transformedVector, 0, 0) / cvmGet(&transformedVector, 2, 0)), (int)(cvmGet(&transformedVector, 1, 0) / cvmGet(&transformedVector, 2, 0)));
return outputPoint;
}
答案 1 :(得分：2)
更简单，更简洁的解决方案是修改透视转换。您可以进行平移，将原点移动到所需位置，然后进行透视变换，最后进行反向平移。
这是python中的一个小示例程序，它围绕点（100,100）旋转图像45度：
import cv2
import numpy as np
def translation_mat(dx, dy):
return np.array([1, 0, dx, 0, 1, dy, 0, 0, 1]).reshape((3,3))
def main():
img = cv2.imread(r"pigeon.png", cv2.IMREAD_GRAYSCALE)
# a simple rotation by 45 degrees
rot = np.array([np.sin(np.pi/4), -np.cos(np.pi/4), 0, np.cos(np.pi/4), np.sin(np.pi/4), 0, 0, 0, 1]).reshape((3,3))
t1 = translation_mat(-100, -100)
t2 = translation_mat(100, 100)
rot_shifted = t2.dot(rot.dot(t1))
size = (img.shape[1], img.shape[0])
img1 = cv2.warpPerspective(img, rot, size)
img2 = cv2.warpPerspective(img, rot_shifted, size)
cv2.imshow("Original image", img)
cv2.imshow("Rotated around (0,0)", img1)
cv2.imshow("Rotated around(100, 100)", img2)
cv2.waitKey(0)
if __name__ == '__main__':
main()
并非您从右到左阅读转换顺序。
rot_shifted = t2.dot(rot.dot(t1))
首先应用t1，然后是rot，然后是t2。
答案 2 :(得分：0)
对于那些在Python中寻找这篇文章的人来说，这是一个开始。我不是百分之百确定它的工作原理，因为我已经从中删除了一些优化。也有线路空间插值的问题，我根本就没有使用它，但如果你这样做，你可能想仔细看看。
import cv2
import numpy as np
def warp_perspective(src, M, (width, height), (origin_x, origin_y),
flags=cv2.INTER_NEAREST, borderMode=cv2.BORDER_CONSTANT,
borderValue=0, dst=None):
"""
Implementation in Python using base code from
http://stackoverflow.com/questions/4279008/specify-an-origin-to-warpperspective-function-in-opencv-2-x
Note there is an issue with linear interpolation.
"""
B_SIZE = 32
if dst == None:
dst = np.zeros((height, width, 3), dtype=src.dtype)
# Set interpolation mode.
interpolation = flags & cv2.INTER_MAX
if interpolation == cv2.INTER_AREA:
raise Exception('Area interpolation is not supported!')
# Prepare matrix.
M = M.astype(np.float64)
if not(flags & cv2.WARP_INVERSE_MAP):
M = cv2.invert(M)[1]
M = M.flatten()
x_dst = y_dst = 0
for y in xrange(-origin_y, height, B_SIZE):
for x in xrange(-origin_x, width, B_SIZE):
print (x, y)
# Block dimensions.
bw = min(B_SIZE, width - x_dst)
bh = min(B_SIZE, height - y_dst)
# To avoid dimension errors.
if bw <= 0 or bh <= 0:
break
# View of the destination array.
dpart = dst[y_dst:y_dst+bh, x_dst:x_dst+bw]
# Original code used view of array here, but we're using numpy array's.
XY = np.zeros((bh, bw, 2), dtype=np.int16)
A = np.zeros((bh, bw), dtype=np.uint16)
for y1 in xrange(bh):
X0 = M[0]*x + M[1]*(y + y1) + M[2]
Y0 = M[3]*x + M[4]*(y + y1) + M[5]
W0 = M[6]*x + M[7]*(y + y1) + M[8]
if interpolation == cv2.INTER_NEAREST:
for x1 in xrange(bw):
W = np.float64(W0 + M[6]*x1);
if W != 0:
W = np.float64(1.0)/W
X = np.int32((X0 + M[0]*x1)*W)
Y = np.int32((Y0 + M[3]*x1)*W)
XY[y1, x1][0] = np.int16(X)
XY[y1, x1][1] = np.int16(Y)
else:
for x1 in xrange(bw):
W = np.float64(W0 + M[6]*x1);
if W != 0:
W = cv2.INTER_TAB_SIZE/W
X = np.int32((X0 + M[0]*x1)*W)
Y = np.int32((Y0 + M[3]*x1)*W)
XY[y1, x1][0] = np.int16((X >> cv2.INTER_BITS) + origin_x)
XY[y1, x1][1] = np.int16((Y >> cv2.INTER_BITS) + origin_y)
A[y1, x1] = np.int16(((Y & (cv2.INTER_TAB_SIZE-1))*cv2.INTER_TAB_SIZE + (X & (cv2.INTER_TAB_SIZE-1))))
if interpolation == cv2.INTER_NEAREST:
cv2.remap(src, XY, None, interpolation, dst=dpart,
borderMode=borderMode, borderValue=borderValue)
else:
cv2.remap(src, XY, A, interpolation, dst=dpart,
borderMode=borderMode, borderValue=borderValue)
x_dst += B_SIZE
x_dst = 0
y_dst += B_SIZE
return dst