refactored

cam_calib.py

@@ -2,13 +2,17 @@ import numpy as np
 import cv2 as cv
 import glob
 
+PAT_NX = 7
+PAT_NY = 6
+
 def main():
+
 	# termination criteria
-	criteria = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_MAX_ITER, 30, 0.001)
+	criteria = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_MAX_ITER, 30, 0.01)
 
 	# 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)
+	objp = np.zeros((PAT_NX * PAT_NY, 3), np.float32)
+	objp[:, :2] = np.mgrid[0:PAT_NX, 0:PAT_NY].T.reshape(-1, 2)
 
 	# Arrays to store object points and image points from all the images.
 	objpoints = []  # 3d point in real world space
@@ -21,7 +25,7 @@ def main():
 		gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
 
 		# Find the chess board corners
-		ret, corners = cv.findChessboardCorners(gray, (7, 6), None)
+		ret, corners = cv.findChessboardCorners(gray, (PAT_NX, PAT_NY), None)
 
 		# If found, add object points, image points (after refining them)
 		if ret:
@@ -31,9 +35,9 @@ def main():
 			imgpoints.append(corners2)
 
 			# Draw and display the corners
-			cv.drawChessboardCorners(img, (7, 6), corners2, ret)
+			cv.drawChessboardCorners(img, (PAT_NX, PAT_NY), corners2, ret)
 			cv.imshow('img', img)
-			cv.waitKey(500)
+			cv.waitKey(-1)
 
 		#  Calibration
 		ret, mtx, dist, rvecs, tvecs = cv.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)
@@ -46,7 +50,7 @@ def main():
 		h, w = img.shape[:2]
 		newcameramtx, roi = cv.getOptimalNewCameraMatrix(mtx, dist, (w, h), 1, (w, h))
 
-		#  1. Using cv.undistort()
+		#  1. Undistort using cv.undistort()
 		dst = cv.undistort(img, mtx, dist, None, newcameramtx)
 
 		# crop the image