OpenCV-Python - 使用校准函数时如何格式化 numpy 数组

Question

我正在尝试使用 OpenCV 3.0.0 python 绑定（使用非对称圆形网格）校准鱼眼相机，但我无法正确格式化对象和图像点数组。我当前的来源如下所示：

import cv2
import glob
import numpy as np


def main():
    circle_diameter = 4.5
    circle_radius = circle_diameter/2.0
    pattern_width = 4
    pattern_height = 11
    num_points = pattern_width*pattern_height

    images = glob.glob('*.bmp')
    criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)

    imgpoints = []
    objpoints = []
    obj = []

    for i in range(pattern_height):
        for j in range(pattern_width):
            obj.append((
                 float(2*j + i % 2)*circle_radius,
                 float(i*circle_radius),
                 0
            ))

    for name in images:
        image = cv2.imread(name)
        grayimage = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        retval, centers = cv2.findCirclesGrid(grayimage, (pattern_width, pattern_height), flags=(cv2.CALIB_CB_ASYMMETRIC_GRID + cv2.CALIB_CB_CLUSTERING))

        imgpoints_tmp = np.zeros((num_points, 2))
        if retval:
            for i in range(num_points):
                imgpoints_tmp[i, 0] = centers[i, 0, 0]
                imgpoints_tmp[i, 1] = centers[i, 0, 1]

            imgpoints.append(imgpoints_tmp)
            objpoints.append(obj)


    # Convertion to numpy array
    imgpoints = np.array(imgpoints, dtype=np.float32)
    objpoints = np.array(objpoints, dtype=np.float32)

    K, D = cv2.fisheye.calibrate(objpoints, imgpoints, image_size=(1280, 800), K=None, D=None)

if __name__ == '__main__':
    main()

错误信息是：

OpenCV Error: Assertion failed (objectPoints.type() == CV_32FC3 || objectPoints.type() == CV_64FC3) in cv::fisheye::calibrate

objpoints 的形状为 (31,44,3)。

所以objpoints 数组需要以不同的方式格式化，但我无法实现正确的布局。也许有人可以在这里提供帮助？

Answer 1

objpoints 的正确布局是一个带有 len(objpoints) = "number of pictures" 的 numpy 数组列表，每个条目都是一个 numpy 数组。

请查看the official help。 OpenCV 文档谈到了“向量”，它相当于一个列表或 numpy.array。在这种情况下，“向量的向量”可以解释为 numpy.arrays 的列表。

Answer 2

在 OpenCV (Camera Calibration) 的示例中，他们将 objp 设置为 objp2 = np.zeros((8*9,3), np.float32)

但是，在全向相机或鱼眼相机中，它应该是： objp = np.zeros((1,8*9,3), np.float32)

想法来自这里Calibrate fisheye lens using OpenCV — part 1

Answer 3

数据类型正确，但形状不正确。 objpoints 的预期形状应该是 (n_observations, 1, n_corners_per_observation, 3)。因此，您的案例中的代码应该是：

imgpoints = np.array(imgpoints, dtype=np.float32).reshape(
  -1, 
  1, 
  pattern_width * pattern_height, 
  3
)

或更笼统地说：

imgpoints = np.array(imgpoints, dtype=np.float32).reshape(
  n_observations, 
  1, 
  n_corners_per_observation, 
  3
)

错误信息有点误导。

Answer 4

在这里没有找到令人满意的答案，所以我搞砸了，最终让这个块工作：

calibration_flags = cv2.fisheye.CALIB_RECOMPUTE_EXTRINSIC + cv2.fisheye.CALIB_CHECK_COND + cv2.fisheye.CALIB_FIX_SKEW

# lists with each element a [1,n_points,_] array of type float32
obj_points = [np.random.rand(1,10,3).astype(np.float32)]
fisheye_points = [np.random.rand(1,10,2).astype(np.float32)]

# initialize empty variables of correct size and type, where total_num_points is summed across all arrays in each above list
rvecs = [np.zeros((1, 1, 3), dtype=np.float32) for i in range(total_num_points)]
tvecs = [np.zeros((1, 1, 3), dtype=np.float32) for i in range(total_num_points)]
D = np.zeros([4,1]).astype(np.float32)
K = np.zeros([3,3]).astype(np.float32)

outputs = cv2.fisheye.calibrate(gt_points,fisheye_points,(1920,1080),K,D,rvecs,tvecs)