From 4ea570e2ab403ad8a5779dd432df56e44ef85da2 Mon Sep 17 00:00:00 2001 From: Jens Ahrensfeld Date: Mon, 24 Nov 2025 12:30:41 +0100 Subject: [PATCH] refactored --- cam_calib.py | 18 +++++++++++------- cam_pose.py | 36 ++++++++++++++++++++---------------- 2 files changed, 31 insertions(+), 23 deletions(-) diff --git a/cam_calib.py b/cam_calib.py index 4bfe6bd..bc6e92e 100644 --- a/cam_calib.py +++ b/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 diff --git a/cam_pose.py b/cam_pose.py index 21f13f8..4caabcc 100644 --- a/cam_pose.py +++ b/cam_pose.py @@ -2,6 +2,9 @@ import numpy as np import cv2 as cv import glob +PAT_NX = 7 +PAT_NY = 6 + def draw_gizmo(img, corners, imgpts): corner = tuple(corners[0].ravel().astype("int32")) imgpts = imgpts.astype("int32") @@ -26,6 +29,14 @@ def draw_cube(img, corners, imgpts): return img +def init_data(): + criteria = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_MAX_ITER, 30, 0.001) + objp = np.zeros((PAT_NX * PAT_NY, 3), np.float32) + objp[:, :2] = np.mgrid[0:PAT_NX, 0:PAT_NY].T.reshape(-1, 2) + + axis = np.float32([[3, 0, 0], [0, 3, 0], [0, 0, -3]]).reshape(-1, 3) + + return criteria, objp, axis def main(): process_video() @@ -34,11 +45,8 @@ def process_video(): with np.load('results/cam.npz') as X: mtx, dist, _, _ = [X[i] for i in ('mtx', 'dist', 'rvecs', 'tvecs')] - criteria = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_MAX_ITER, 30, 0.001) - objp = np.zeros((6 * 7, 3), np.float32) - objp[:, :2] = np.mgrid[0:7, 0:6].T.reshape(-1, 2) - - axis = np.float32([[3, 0, 0], [0, 3, 0], [0, 0, -3]]).reshape(-1, 3) + # Init + criteria, objp, axis = init_data() # Open camera video = cv.VideoCapture(0) @@ -51,7 +59,7 @@ def process_video(): ok, img = video.read() if not ok: return - process_img(img, criteria, objp, axis, mtx, dist) + process(img, mtx, dist, criteria, objp, axis) k = cv.waitKey(1) & 0xFF if k == ord('q'): break @@ -60,25 +68,21 @@ def process_still(): with np.load('results/cam.npz') as X: mtx, dist, _, _ = [X[i] for i in ('mtx', 'dist', 'rvecs', 'tvecs')] - criteria = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_MAX_ITER, 30, 0.001) - objp = np.zeros((6 * 7, 3), np.float32) - objp[:, :2] = np.mgrid[0:7, 0:6].T.reshape(-1, 2) - - axis = np.float32([[3, 0, 0], [0, 3, 0], [0, 0, -3]]).reshape(-1, 3) + # Init + criteria, objp, axis = init_data() for fname in glob.glob('check*.jpg'): img = cv.imread(fname) - process_img(img, criteria, objp, axis, mtx, dist) + process(img, mtx, dist, criteria, objp, axis) k = cv.waitKey(1) & 0xFF if k == ord('q'): break -def process_img(img, criteria, objp, axis, mtx, dist): # Load previously saved data - pattern_size = (7, 6) +def process(img, mtx, dist, criteria, objp, axis): # Load previously saved data gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY) - ret, corners = cv.findChessboardCorners(gray, pattern_size, corners=None, flags=cv.CALIB_CB_ADAPTIVE_THRESH+cv.CALIB_CB_NORMALIZE_IMAGE+cv.CALIB_CB_FAST_CHECK) - cv.drawChessboardCorners(img, corners=corners, patternSize=pattern_size, patternWasFound=ret) + ret, corners = cv.findChessboardCorners(gray, (PAT_NX, PAT_NY), corners=None, flags=cv.CALIB_CB_ADAPTIVE_THRESH+cv.CALIB_CB_NORMALIZE_IMAGE+cv.CALIB_CB_FAST_CHECK) + cv.drawChessboardCorners(img, corners=corners, patternSize=(PAT_NX, PAT_NY), patternWasFound=ret) if ret: corners2 = cv.cornerSubPix(gray, corners, (11, 11), (-1, -1), criteria)