pose_estimation.py

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 * 8, 3), np.float32)
objp[:, :2] = np.mgrid[0:8, 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('calib_images/checkerboard/*.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, (8, 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(corners2)

        # Draw and display the corners
        img = cv2.drawChessboardCorners(img, (8, 6), corners2, ret)

ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)


# Function to draw the axis
# Draw axis function can also be used.
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 * 8, 3), np.float32)
objp[:, :2] = np.mgrid[0:8, 0:6].T.reshape(-1, 2)

axis = np.float32([[3, 0, 0], [0, 3, 0], [0, 0, -3]]).reshape(-1, 3)

for fname in glob.glob('calib_images/checkerboard/scene_9.jpg'):
    img = cv2.imread(fname)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    ret, corners = cv2.findChessboardCorners(gray, (8, 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)
        cv2.imshow('img', img)
        k = cv2.waitKey(0) & 0xff

cv2.destroyAllWindows()