cv2：去扭曲后不需要的裁剪 (initUndistortRectifyMap)

如何解决cv2：去扭曲后不需要的裁剪 (initUndistortRectifyMap)

我想校准我的相机。目标是消除失真并且不裁剪图像（如最后一张照片）。我是这样做的：

1)加载图片，找到棋盘的角

import cv2
import numpy as np
import os
import glob
import  sys

CHECKERBOARD = (7,7)
subpix_criteria = (cv2.TERM_CRITERIA_EPS+cv2.TERM_CRITERIA_MAX_ITER,30,0.1)
calibration_flags = cv2.fisheye.CALIB_RECOMPUTE_EXTRINSIC+cv2.fisheye.CALIB_CHECK_COND+cv2.fisheye.CALIB_FIX_SKEW
objp = np.zeros((1,CHECKERBOARD[0]*CHECKERBOARD[1],3),np.float32)
objp[0,:,:2] = np.mgrid[0:CHECKERBOARD[0],0:CHECKERBOARD[1]].T.reshape(-1,2)
_img_shape = None
objpoints = [] # 3d point in real world space
imgpoints = [] # 2d points in image plane.
images = os.listdir("./calib_snapshots")
gray = None
for fname in images:
    fname = os.path.join("./calib_snapshots",fname)
    if not os.path.isfile(fname):
        continue
    img = cv2.imread(fname)
    if _img_shape == None:
        _img_shape = img.shape[:2]
    else:
        assert _img_shape == img.shape[:2],"All images must share the same size."
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    # Find the chess board corners
    ret,corners = cv2.findChessboardCorners(gray,CHECKERBOARD,cv2.CALIB_CB_ADAPTIVE_THRESH+cv2.CALIB_CB_FAST_CHECK)
    # If found,add object points,image points (after refining them)
    if ret == True:
        objpoints.append(objp)
        cv2.cornerSubPix(gray,corners,(3,(-1,-1),subpix_criteria)
        imgpoints.append(corners)

2)然后计算相机矩阵和畸变系数：

DIM =_img_shape[::-1]
K = np.zeros((3,3))
D = np.zeros((4,1))
rvecs = [np.zeros((1,1,dtype=np.float64) for i in range(N_OK)]
tvecs = [np.zeros((1,dtype=np.float64) for i in range(N_OK)]
rms,_,_ = \
    cv2.fisheye.calibrate(
        objpoints,imgpoints,gray.shape[::-1],K,D,rvecs,tvecs,calibration_flags,(cv2.TERM_CRITERIA_EPS+cv2.TERM_CRITERIA_MAX_ITER,1e-6)
    )

3. 然后计算地图：

map1,map2 = cv2.fisheye.initUndistortRectifyMap(K,np.eye(3),DIM,cv2.CV_16SC2)

我的输入图像：

4）当我重新映射我的图像时 - 我在结果中得到这样的裁剪图像：

img = cv2.imread("goingcrazy.jpg")
undistorted_img = cv2.remap(img,map1,map2,interpolation=cv2.INTER_LINEAR)

我得到了什么：

想要的图片：

我怎样才能得到这样的未裁剪图像？

PS 我在 c++ 中有工作解决方案，并尝试了这样的事情：我从校准（）结果中打印了相机矩阵和失真系数，从 c++ 终端复制它，并传递给 python 中的 initUndistortRectifyMap（与与 c++ 中的参数相同），但我得到了不同的 map1 和 map2，并且图像仍然被裁剪...