camera_calibration.py 文件源码

def camera_cal(self, image):

        # termination criteria
        criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)

        nx = 8
        ny = 6

        dst = np.copy(image) 

        # prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
        objp = np.zeros((ny * nx, 3), np.float32)
        objp[:,:2] = np.mgrid[0:nx, 0:ny].T.reshape(-1,2)

        # Arrays to store object points and image points from all the images.
        objpoints = [] # 3d points in real world space
        imgpoints = [] # 2d points in image plane.

        # Search for chessboard corners
        grey = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

        #ret_thresh,  mask = cv2.threshold(grey, 30, 255, cv2.THRESH_BINARY)

        ret, corners = cv2.findChessboardCorners(image, (nx, ny), None)  #flags=(cv2.cv.CV_CALIB_CB_ADAPTIVE_THRESH + cv2.cv.CV_CALIB_CB_FILTER_QUADS))        

        # If found, add object points, image points
        if ret == True:
            objpoints.append(objp)           
            cv2.cornerSubPix(grey,corners, (11,11), (-1,-1), criteria)
            imgpoints.append(corners)
            self.calibrated = True
            print ("FOUND!")

            #Draw and display the corners
            cv2.drawChessboardCorners(image, (nx, ny), corners, ret)  

            # Do camera calibration given object points and image points
            ret, self.mtx, self.dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, grey.shape[::-1], None, None)        

            # Save the camera calibration result for later use (we won't worry about rvecs / tvecs)
            dist_pickle = {}
            dist_pickle["mtx"] = self.mtx
            dist_pickle["dist"] = self.dist
            dist_pickle['objpoints'] = objpoints
            dist_pickle['imgpoints'] = imgpoints
            pickle.dump( dist_pickle, open( "/home/wil/ros/catkin_ws/src/av_sim/computer_vision/camera_calibration/data/camera_cal_pickle.p", "wb" ) )

         #else:
             #print("Searching...")

        return image