OpenCV立体摄像机校准错误：断言失败

Question

我知道这个问题曾被问过几次，但答案并没有解决我的问题。

我想校准一对相机用作立体声输入。但是当我运行代码时，我收到错误消息：

OpenCV(3.4.1) Error: Assertion failed (nimages > 0 && nimages == (int)imagePoints1.total() && (!imgPtMat2 || nimages == (int)imagePoints2.total())) in collectCalibrationData, file /tmp/opencv-20180529-49540-yj8rbk/opencv-3.4.1/modules/calib3d/src/calibration.cpp, line 3133
Traceback (most recent call last):
  File "/Users/MyName/Pycharm/Project/calibration.py", line 342, in <module>
    TERMINATION_CRITERIA )
cv2.error: OpenCV(3.4.1) /tmp/opencv-20180529-49540-yj8rbk/opencv-3.4.1/modules/calib3d/src/calibration.cpp:3133: error: (-215) nimages > 0 && nimages == (int)imagePoints1.total() && (!imgPtMat2 || nimages == (int)imagePoints2.total()) in function collectCalibrationData

我的代码是：

def distortion_matrix(path, objpoints, imgpoints):

  for item in os.listdir(path):
    if item.endswith(".jpg"):
        cap = cv2.VideoCapture(path+item, cv2.CAP_IMAGES)

        ret, img = cap.read()  # Capture frame-by-frame

        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

        keypoints = blobDetector.detect(gray)  # Detect blobs.

                    im_with_keypoints = cv2.drawKeypoints(img, keypoints, np.array([]), (0, 255, 0),
                                              cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
        im_with_keypoints_gray = cv2.cvtColor(im_with_keypoints, cv2.COLOR_BGR2GRAY)
        ret, corners = cv2.findCirclesGrid(im_with_keypoints, (4, 11), None,
                                           flags=cv2.CALIB_CB_ASYMMETRIC_GRID)  

        if ret == True:
            objpoints.append(objp)  

            corners2 = cv2.cornerSubPix(im_with_keypoints_gray, corners, (11, 11), (-1, -1),
                                        criteria)  
            imgpoints.append(corners2)


  cap.release()

_, leftCameraMatrix, leftDistortionCoefficients, _, _ , objpoints0, imgpoints0 = distortion_matrix("./calibration/left/", objpoints0, imgpoints0)
_, rightCameraMatrix, rightDistortionCoefficients, _, _, objpoints1, imgpoints1 = distortion_matrix("./calibration/right/", objpoints1, imgpoints1)



(_, _, _, _, _, rotationMatrix, translationVector, _, _) = cv2.stereoCalibrate( objp, imgpoints0, imgpoints1, 
                                                                            leftCameraMatrix, leftDistortionCoefficients, 
                                                                            rightCameraMatrix, rightDistortionCoefficients, 
                                                                            imageSize, None, None, None, None,
                                                                            cv2.CALIB_FIX_INTRINSIC, TERMINATION_CRITERIA )

大多数情况下，抛出它时，似乎Message引用的数组（imgpoint和objpoint）为空或未均匀填充。但最后两个都得到了长度20（我扫描了20个图像所以这看起来是正确的）并且阵列的每个单元格都存储了44个阵列（我使用的圆形网格有44个点，所以这似乎也是正确的）。

**编辑：**我的objp，imgpoint和objpoint定义如下：

objp = np.zeros((np.prod(pattern_size), 3), np.float32)
objp[0]  = (0, 0, 0)
objp[1]  = (0, 2, 0)
objp[2]  = (0, 4, 0)
objp[3]  = (0, 6, 0)
...


objpoints0 = []
objpoints1 = []

imgpoints0 = []
imgpoints1 = []

**编辑2：**

如果NUM_IMAGES代表图像数量，那我现在就知道了。但只有在我调用distortion_matrix()之后添加新轴时。然后代码就能完成了。我需要测试结果，但至少这个问题似乎可以解决。

非常感谢你

Answer 1

你说你正在进行立体声校准，是否有任何情况下你的网格上的某些点从其他相机看不到？当您的某个视图无法检测到校准图案上的所有点时，可能会出现此错误。需要考虑的三点是 1-确保您的对象点是3d 2-确保左点，右点和对象点具有相同的大小（视图数）。 3-确保左侧点，右侧点和对象点在每个列表索引处具有相同的点数。

编辑：你的对象点objp必须包含3d点的列表/向量，目前它的形状类似于（44,3），它必须是（NUM_IMAGES，44,3）。你可以用objp = np.repeat(objp[np.newaxis, :, :], NUM_IMAGES, axis=0)实现这一目标