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calibration.py
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import numpy as np
import cv2
import glob
import matplotlib.pyplot as plt
#%matplotlib qt
def get_calibrating_points( calibrate_img_path = './camera_cal/calibration*.jpg'):
# prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
objp = np.zeros((6*9,3), np.float32)
objp[:,:2] = np.mgrid[0:9,0:6].T.reshape(-1,2)
# Arrays to store object points and image points from all the images.
objpoints = [] # 3d points in real world space
imgpoints = [] # 2d points in image plane.
# Make a list of calibration images
images = glob.glob(calibrate_img_path)
ret_images = []
# Step through the list and search for chessboard corners
for fname in images:
img = cv2.imread(fname)
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
# Find the chessboard corners
ret, corners = cv2.findChessboardCorners(gray, (9,6),None)
# If found, add object points, image points
if ret == True:
ret_images.append(fname)
objpoints.append(objp)
imgpoints.append(corners)
if is_print == True:
# Draw and display the corners
img = cv2.drawChessboardCorners(img, (9,6), corners, ret)
cv2.imshow('img',img)
cv2.waitKey(500)
cv2.destroyAllWindows()
return ret_images, objpoints, imgpoints
def calibrate(gray, row_n = 6, col_n = 9):
images, objpoints, imgpoints = get_calibrating_points()
ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(
objpoints, imgpoints, gray.shape[::-1], None, None)
return ret, mtx, dist, rvecs, tvecs
def undistort(img, mtx, dist):
dst = cv2.undistort(img, mtx, dist, None, mtx)
return dst
if __name__ == "__main__":
img = cv2.imread("camera_cal/calibration1.jpg")
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
ret, mtx, dist, rvecs, tvecs = calibrate(gray, 6, 9)
undistort_img = undistort(img, mtx, dist)
#print (ret, mtx, dist,rvecs,tvecs)
cv2.imwrite('examples/undistort_1.png',undistort_img)