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single_calibrate.py
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single_calibrate.py
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# -*- coding: utf-8 -*-
"""
Created on Mon May 28 21:35:55 2018
@author: Autumn
"""
import numpy as np
import cv2
import glob
import os
import argparse
ap = argparse.ArgumentParser()
ap.add_argument('-f', '--filepath', required=True, help='path to input images')
ap.add_argument('-s', '--savepath', help='save modified images (True or False)')
args = vars(ap.parse_args())
# termination criteria
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
# 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 point in real world space
imgpoints = [] # 2d points in image plane
images = glob.glob(args['filepath'] + '/*.jpg')
for fname in images:
img = cv2.imread(fname)
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
# Find the chess board corners
ret, corners = cv2.findChessboardCorners(gray, (9,6), None)
# If found, add object points, image points (after refining them)
if ret == True:
objpoints.append(objp)
corners2 = cv2.cornerSubPix(gray, corners, (11,11), (-1,-1), criteria)
imgpoints.append(corners2)
# Draw and display the corners
img = cv2.drawChessboardCorners(img, (9,6), corners2, ret)
cv2.imshow('img',img)
cv2.waitKey(500)
cv2.destroyAllWindows()
ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)
if args['savepath']:
if not os.path.isdir('./undistorted_images'):
os.mkdir('./undistorted_images')
for fname in images:
img = cv2.imread(fname)
img_name = fname.split(os.sep)[-1].split('.')[0]
h, w = img.shape[:2]
newcameramtx, roi=cv2.getOptimalNewCameraMatrix(mtx,dist,(w,h),1,(w,h))
# undistort
dst = cv2.undistort(img, mtx, dist, None, newcameramtx)
# crop the image
x,y,w,h = roi
dst = dst[y:y+h, x:x+w]
cv2.imwrite('./undistorted_images/undistorted_{}.jpg'.format(img_name), dst)
cv2.destroyAllWindows()
#calculate re-projection error
tot_error = 0
for i in range(len(objpoints)):
imgpoints2, _ = cv2.projectPoints(objpoints[i], rvecs[i], tvecs[i], mtx, dist)
error = cv2.norm(imgpoints[i],imgpoints2, cv2.NORM_L2)/len(imgpoints2)
tot_error += error
print("average re-projection error: ", tot_error/len(objpoints))