Austin Schuh | 085eab9 | 2020-11-26 13:54:51 -0800 | [diff] [blame] | 1 | #!/usr/bin/python3 |
Alex Perry | 84077a5 | 2019-03-06 20:46:42 -0800 | [diff] [blame] | 2 | |
| 3 | import cv2 |
| 4 | import glob |
| 5 | import math |
| 6 | import numpy as np |
| 7 | import sys |
| 8 | """ |
| 9 | Usage: |
| 10 | undistort.py [display] |
| 11 | |
| 12 | Finds files in /tmp/*.yuyv to compute distortion constants for. |
| 13 | """ |
| 14 | |
| 15 | |
| 16 | def undist(orig, mtx, dist, newcameramtx, its=1): |
| 17 | """ |
| 18 | This function runs a manual undistort over the entire image to compare to the |
| 19 | golden as proof that the algorithm works and the generated constants are correct. |
| 20 | """ |
| 21 | output = np.full(orig.shape, 255, dtype=np.uint8) |
| 22 | for i in range(480): |
| 23 | for j in range(640): |
| 24 | x0 = (i - mtx[1, 2]) / mtx[1, 1] |
| 25 | y0 = (j - mtx[0, 2]) / mtx[0, 0] |
| 26 | x = x0 |
| 27 | y = y0 |
| 28 | for k in range(its): |
| 29 | r2 = x * x + y * y |
| 30 | coeff = (1 + dist[0, 0] * r2 + dist[0, 1] * math.pow(r2, 2) + |
| 31 | dist[0, 4] * math.pow(r2, 3)) |
| 32 | x = x0 / coeff |
| 33 | y = y0 / coeff |
| 34 | ip = x * newcameramtx[1, 1] + newcameramtx[1, 2] |
| 35 | jp = y * newcameramtx[0, 0] + newcameramtx[0, 2] |
| 36 | if ip < 0 or jp < 0 or ip >= 480 or jp >= 640: |
| 37 | continue |
| 38 | output[int(ip), int(jp)] = orig[i, j] |
| 39 | return output |
| 40 | |
| 41 | |
| 42 | def main(argv): |
| 43 | # prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0) |
| 44 | objp = np.zeros((6 * 9, 3), np.float32) |
| 45 | objp[:, :2] = np.mgrid[0:9, 0:6].T.reshape(-1, 2) |
| 46 | |
| 47 | # Arrays to store object points and image points from all the images. |
| 48 | objpoints = [] # 3d point in real world space |
| 49 | imgpoints = [] # 2d points in image plane. |
| 50 | |
| 51 | images = glob.glob('/tmp/*.yuyv') |
| 52 | |
| 53 | cols = 640 |
| 54 | rows = 480 |
| 55 | |
| 56 | # Iterate through all the available images |
| 57 | for fname in images: |
| 58 | fd = open(fname, 'rb') |
| 59 | f = np.fromfile(fd, np.uint8, cols * rows * 2) |
| 60 | # Convert yuyv color space to single channel grey. |
| 61 | grey = f[::2] |
| 62 | grey = np.reshape(grey, (rows, cols)) |
| 63 | |
| 64 | ret, corners = cv2.findChessboardCorners(grey, (9, 6), None) |
| 65 | if ret: |
| 66 | objpoints.append(objp) |
| 67 | imgpoints.append(corners) |
| 68 | # Draw the chessboard with corners marked. |
| 69 | if len(argv) > 1 and argv[1] == 'display': |
| 70 | rgb = cv2.cvtColor(grey, cv2.COLOR_GRAY2RGB) |
| 71 | cv2.drawChessboardCorners(rgb, (9, 6), corners, ret) |
| 72 | cv2.imshow('', rgb) |
| 73 | cv2.waitKey(0) |
| 74 | cv2.destroyAllWindows() |
| 75 | fd.close() |
| 76 | |
Ravago Jones | 5127ccc | 2022-07-31 16:32:45 -0700 | [diff] [blame^] | 77 | ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, |
| 78 | grey.shape[::-1], None, |
| 79 | None) |
Alex Perry | 84077a5 | 2019-03-06 20:46:42 -0800 | [diff] [blame] | 80 | newcameramtx, roi = cv2.getOptimalNewCameraMatrix(mtx, dist, (rows, cols), |
| 81 | 1, (rows, cols)) |
| 82 | |
| 83 | dist[0, 2] = 0 |
| 84 | dist[0, 3] = 0 |
| 85 | print("Formatted for Game Config:") |
| 86 | print("""distortion { |
| 87 | f_x: %f |
| 88 | c_x: %f |
| 89 | f_y: %f |
| 90 | c_y :%f |
| 91 | f_x_prime: %f |
| 92 | c_x_prime: %f |
| 93 | f_y_prime: %f |
| 94 | c_y_prime: %f |
| 95 | k_1: %f |
| 96 | k_2: %f |
| 97 | k_3: %f |
| 98 | distortion_iterations: 7 |
| 99 | }""" % ( |
| 100 | # f_x c_x |
| 101 | mtx[0][0], |
| 102 | mtx[0][2], |
| 103 | # f_y c_y |
| 104 | mtx[1][1], |
| 105 | mtx[1][2], |
| 106 | # f_x c_x prime |
| 107 | newcameramtx[0][0], |
| 108 | newcameramtx[0][2], |
| 109 | # f_y c_y prime |
| 110 | newcameramtx[1][1], |
| 111 | newcameramtx[1][2], |
| 112 | # k_1, k_2, k_3 |
| 113 | dist[0, 0], |
| 114 | dist[0, 1], |
| 115 | dist[0, 4])) |
| 116 | |
| 117 | # Draw the original image, open-cv undistort, and our undistort in separate |
| 118 | # windows for each available image. |
| 119 | if len(argv) > 1 and argv[1] == 'display': |
| 120 | for fname in images: |
| 121 | fd = open(fname, 'rb') |
| 122 | f = np.fromfile(fd, np.uint8, cols * rows * 2) |
| 123 | grey_t = f[::2] |
| 124 | grey_t = np.reshape(grey_t, (rows, cols)) |
| 125 | dst_expected = cv2.undistort(grey_t, mtx, dist, None, newcameramtx) |
| 126 | dst_actual = undist(grey_t, mtx, dist, newcameramtx, 5) |
| 127 | cv2.imshow('orig', grey_t) |
| 128 | cv2.imshow('opencv undistort', dst_expected) |
| 129 | cv2.imshow('our undistort', dst_actual) |
| 130 | cv2.waitKey(0) |
| 131 | cv2.destroyAllWindows() |
| 132 | fd.close() |
| 133 | |
| 134 | |
| 135 | if __name__ == '__main__': |
| 136 | main(sys.argv) |