# 9.2. 姿态估计¶

## 9.2.1. 目标¶

-我们将学习如何利用calib3d模块在图像中创建一些3D效果。

## 9.2.2. 基础¶

>>> import cv2
>>> import numpy as np
>>> import glob
>>>
>>> # Load previously saved data
>>> with np.load('/tmp/x_B.npz') as X:
>>>     mtx, dist, _, _ = [X[i] for i in ('mtx','dist','rvecs','tvecs')]


>>> def draw(img, corners, imgpts):
>>>     corner = tuple(corners[0].ravel())
>>>     img = cv2.line(img, corner, tuple(imgpts[0].ravel()), (255,0,0), 5)
>>>     img = cv2.line(img, corner, tuple(imgpts[1].ravel()), (0,255,0), 5)
>>>     img = cv2.line(img, corner, tuple(imgpts[2].ravel()), (0,0,255), 5)
>>>     return img


>>> criteria = (cv2.TERM_CRITERIA_EPS + cv2.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)


>>> %matplotlib inline
>>> import matplotlib.pyplot as plt

>>> import os
>>> os.chdir('/cvdata/'        )

>>> cv = cv2

>>> for fname in glob.glob('left*.jpg'):
>>>     img = cv.imread(fname)
>>>     gray = cv.cvtColor(img,cv.COLOR_BGR2GRAY)
>>>     ret, corners = cv.findChessboardCorners(gray, (7,6),None)
>>>     if ret == True:
>>>         corners2 = cv.cornerSubPix(gray,corners,(11,11),(-1,-1),criteria)
>>>         # Find the rotation and translation vectors.
>>>         ret,rvecs, tvecs = cv.solvePnP(objp, corners2, mtx, dist)
>>>         # project 3D points to image plane
>>>         imgpts, jac = cv.projectPoints(axis, rvecs, tvecs, mtx, dist)
>>>         img = draw(img,corners2,imgpts)
>>>         plt.imshow(img)
>>> #         cv.imshow('img',img)
>>> #         k = cv.waitKey(0) & 0xFF
>>> #         if k == ord('s'):
>>> #             cv.imwrite(fname[:6]+'.png', img)
>>> # cv.destroyAllWindows()

>>>
>>> for fname in glob.glob('left*.jpg'):
>>>     img = cv2.imread(fname)
>>>     gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
>>>     ret, corners = cv2.findChessboardCorners(gray, (7,6),None)
>>>
>>>     if ret == True:
>>>         corners2 = cv2.cornerSubPix(gray,corners,(11,11),(-1,-1),criteria)
>>>
>>>         # Find the rotation and translation vectors.
>>>         rvecs, tvecs, inliers = cv2.solvePnPRansac(objp, corners2, mtx, dist)
>>>
>>>         # project 3D points to image plane
>>>         imgpts, jac = cv2.projectPoints(axis, rvecs, tvecs, mtx, dist)
>>>
>>>         img = draw(img,corners2,imgpts)
>>>         plt.show(img)
>>>
>>> #         cv2.imshow('img',img)
>>> #         k = cv2.waitKey(0) & 0xff
>>> #         if k == 's':
>>> #             cv2.imwrite(fname[:6]+'.png', img)
>>>
>>> # cv2.destroyAllWindows()

---------------------------------------------------------------------------

ValueError                                Traceback (most recent call last)

11
12         # Find the rotation and translation vectors.
---> 13         rvecs, tvecs, inliers = cv2.solvePnPRansac(objp, corners2, mtx, dist)
14
15         # project 3D points to image plane

ValueError: too many values to unpack (expected 3)


### 渲染立方体¶

>>> def draw(img, corners, imgpts):
>>>     imgpts = np.int32(imgpts).reshape(-1,2)
>>>
>>>     # draw ground floor in green
>>>     img = cv2.drawContours(img, [imgpts[:4]],-1,(0,255,0),-3)
>>>
>>>     # draw pillars in blue color
>>>     for i,j in zip(range(4),range(4,8)):
>>>         img = cv2.line(img, tuple(imgpts[i]), tuple(imgpts[j]),(255),3)
>>>
>>>     # draw top layer in red color
>>>     img = cv2.drawContours(img, [imgpts[4:]],-1,(0,0,255),3)
>>>
>>>     return img


>>> axis = np.float32([[0,0,0], [0,3,0], [3,3,0], [3,0,0],
>>>                    [0,0,-3],[0,3,-3],[3,3,-3],[3,0,-3] ])

>>> tt = draw(img,corners2, axis)

>>> plt.imshow(tt)

<matplotlib.image.AxesImage at 0x7fce704fe1d0>