Initial commit

cam_calib.py

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+import numpy as np
+import cv2 as cv
+import glob
+
+def main():
+	# termination criteria
+	criteria = (cv.TERM_CRITERIA_EPS + cv.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 * 7, 3), np.float32)
+	objp[:, :2] = np.mgrid[0:7, 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('*.jpg')
+
+	for fname in images:
+		img = cv.imread(fname)
+		gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
+
+		# Find the chess board corners
+		ret, corners = cv.findChessboardCorners(gray, (7, 6), None)
+
+		# If found, add object points, image points (after refining them)
+		if ret:
+			objpoints.append(objp)
+
+			corners2 = cv.cornerSubPix(gray, corners, (11, 11), (-1, -1), criteria)
+			imgpoints.append(corners2)
+
+			# Draw and display the corners
+			cv.drawChessboardCorners(img, (7, 6), corners2, ret)
+			cv.imshow('img', img)
+			cv.waitKey(500)
+
+		#  Calibration
+		ret, mtx, dist, rvecs, tvecs = cv.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)
+
+		# write to file
+		np.savez("results/cam.npz", mtx=mtx, dist=dist, rvecs=rvecs, tvecs=tvecs)
+
+		#  Undistortion
+		img = cv.imread('checker_cam.jpg')
+		h, w = img.shape[:2]
+		newcameramtx, roi = cv.getOptimalNewCameraMatrix(mtx, dist, (w, h), 1, (w, h))
+
+		#  1. Using cv.undistort()
+		dst = cv.undistort(img, mtx, dist, None, newcameramtx)
+
+		# crop the image
+		x, y, w, h = roi
+		dst = dst[y:y + h, x:x + w]
+		cv.imwrite('results/calibresult_1.png', dst)
+
+		# 2. Undistort using remapping
+		mapx, mapy = cv.initUndistortRectifyMap(mtx, dist, None, newcameramtx, (w, h), 5)
+		dst = cv.remap(img, mapx, mapy, cv.INTER_LINEAR)
+
+		# crop the image
+		x, y, w, h = roi
+		dst = dst[y:y + h, x:x + w]
+		cv.imwrite('results/calibresult_2.png', dst)
+
+		#  Re-projection Error
+		mean_error = 0
+		for i in range(len(objpoints)):
+			imgpoints2, _ = cv.projectPoints(objpoints[i], rvecs[i], tvecs[i], mtx, dist)
+			error = cv.norm(imgpoints[i], imgpoints2, cv.NORM_L2) / len(imgpoints2)
+			mean_error += error
+
+		print("total error: {}".format(mean_error / len(objpoints)))
+	cv.destroyAllWindows()
+
+if __name__ == '__main__':
+	main()