OpenCV小例程——摄像机标定

心已赠人 2021-12-10 04:07 259阅读 0赞

获取到的标定板图像为：  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3hpYW9fbHhs_size_16_color_FFFFFF_t_70]  
Python3下opencv摄像机标定

import numpy as np
    import cv2
    import glob
    # 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*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 = cv2.imread(fname)
        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        # Find the chess board corners
        ret, corners = cv2.findChessboardCorners(gray, (7,6), 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(corners)
            #ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)
            # Draw and display the corners
            cv2.drawChessboardCorners(img, (7,6), corners2, ret)
            cv2.imshow('img', img)
            cv2.waitKey(500)
    cv2.destroyAllWindows()

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3hpYW9fbHhs_size_16_color_FFFFFF_t_70 1]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3hpYW9fbHhs_size_16_color_FFFFFF_t_70 2]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3hpYW9fbHhs_size_16_color_FFFFFF_t_70 3]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3hpYW9fbHhs_size_16_color_FFFFFF_t_70 4]

ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)
    img = cv2.imread('left12.jpg')
    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('calibresult.png', dst)
    
    
    # undistort
    mapx, mapy = cv2.initUndistortRectifyMap(mtx, dist, None, newcameramtx, (w,h), 5)
    dst = cv2.remap(img, mapx, mapy, cv2.INTER_LINEAR)
    # crop the image
    x, y, w, h = roi
    dst = dst[y:y+h, x:x+w]
    cv2.imwrite('calibresult.png', dst)

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3hpYW9fbHhs_size_16_color_FFFFFF_t_70 5]  
统计误差

mean_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)
        mean_error += error
    print( "total error: {}".format(mean_error/len(objpoints)) )

total error: 0.023686000375385676

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