python - 来自solvePnP的输出与projectPoints不匹配

我从solvePnP获取了奇怪的数据，所以我尝试使用projectPoints进行检查:

retval, rvec, tvec=cv2.solvePnP(opts, ipts, mtx, dist, flags=cv2.SOLVEPNP_ITERATIVE)
print(retval,rvec,tvec)
proj, jac = cv2.projectPoints(opts, rvec, tvec, mtx, dist)
print(proj,ipts)

在此图片上检测到的是z = 0的3d点:



ipts取自此图片(此处仅图片的一部分):



我已经检查了点本身(通过SIFT检测到，可以正确检测到点并以正确的方式配对)。

现在，我想测试由SolvePnP找到的rvec和tvec是否正确，因此我调用cv2.projectPoint来测试3d点是否投影到图像点。这是我所拥有的:



因此，我看到投影点位于图像之外，且y
(从solvePnP检索为true)

这是失真矩阵dist:

1.6324642475694839e+02 -2.1480843988631259e+04 -3.4969507980045117e-01 7.9693609309756430e-01 -4.0684056606034986e+01

这是mtx:

6.4154558230601404e+04 0. 1.2973531562160772e+03
0. 9.8908265814965678e+04 9.5760834379036123e+02
0. 0. 1.

这是选择:

[[ 1708.74987793  1138.92041016     0.        ]
 [ 1708.74987793  1138.92041016     0.        ]
 [ 1708.74987793  1138.92041016     0.        ]
 [ 1708.74987793  1138.92041016     0.        ]
 [ 1708.74987793  1138.92041016     0.        ]
 [ 1708.74987793  1138.92041016     0.        ]
 [ 1708.74987793  1138.92041016     0.        ]
 [ 1984.09973145  1069.31677246     0.        ]
 [ 1984.09973145  1069.31677246     0.        ]
 [ 1908.19396973  1200.05529785     0.        ]
 [ 1994.56677246  1286.16516113     0.        ]
 [ 1994.56677246  1286.16516113     0.        ]
 [ 1806.82177734  1058.06872559     0.        ]
 [ 1925.55639648  1077.33703613     0.        ]
 [ 1998.30627441  1115.51647949     0.        ]
 [ 1998.30627441  1115.51647949     0.        ]
 [ 1998.30627441  1115.51647949     0.        ]
 [ 2013.79003906  1168.08728027     0.        ]
 [ 1972.93457031  1234.92614746     0.        ]
 [ 2029.11364746  1220.234375       0.        ]]

这是ipts:

[[  71.6125946    11.61344719]
 [ 116.60684967   71.6068573 ]
 [ 116.60684967   71.6068573 ]
 [ 101.60684967   86.60684967]
 [ 101.60684967   86.60684967]
 [ 116.60684967  101.6068573 ]
 [ 116.60684967  101.6068573 ]
 [ 112.37421417   53.40462112]
 [ 112.37421417   53.40462112]
 [  83.76233673   84.36077118]
 [  98.45358276  112.38414764]
 [  98.45358276  112.38414764]
 [  67.2594223    38.04878998]
 [  96.85155487   51.85028076]
 [ 112.26165009   67.25630188]
 [ 112.26165009   67.25630188]
 [ 112.26165009   67.25630188]
 [ 112.24694061   82.24401855]
 [  96.82528687   97.66513824]
 [ 112.2511673    97.25905609]]

rvec = [[-0.21890167] [-0.86241377] [ 0.96051463]]
tvec = [[  239.04461181] [-2165.99539286] [-1700.61539107]]

我也尝试遵循其中一个注释，并将opt中的每个y乘以-1，但这给了我更疯狂的坐标，例如10 ^ 13。

最佳答案

相机矩阵(mts)不正确。 Fx和Fy非常不同(Fx = 6.4154558230601404e + 04 Fy = 9.8908265814965678e + 04)并且很大。根据OpenCV calibrateCamera()函数中的注释，通常会出现此问题，因为您可能在findChessboardCorners中使用了patternSize = cvSize(rows，cols)而不是使用patternSize = cvSize(cols，rows)。

关于python - 来自solvePnP的输出与projectPoints不匹配，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/47723638/