77 lines
2.0 KiB
Python
77 lines
2.0 KiB
Python
import glob
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import os
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import cv2
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import numpy as np
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# Defining the dimensions of checkerboard
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CHECKERBOARD = (6, 9)
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criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
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# Creating vector to store vectors of 3D points for each checkerboard image
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objpoints = []
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# Creating vector to store vectors of 2D points for each checkerboard image
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imgpoints = []
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# Defining the world coordinates for 3D points
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objp = np.zeros((CHECKERBOARD[0] * CHECKERBOARD[1], 3), np.float32)
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objp[:, :2] = np.mgrid[0 : CHECKERBOARD[0], 0 : CHECKERBOARD[1]].T.reshape(-1, 2)
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prev_img_shape = None
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# Extracting path of individual image stored in a given directory
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images = glob.glob("9/images/*.jpg")
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for fname in images:
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img = cv2.imread(fname)
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img = cv2.resize(img, (960, 720))
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gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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# Find the chess board corners
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ret, corners = cv2.findChessboardCorners(
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gray,
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CHECKERBOARD,
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cv2.CALIB_CB_ADAPTIVE_THRESH
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+ cv2.CALIB_CB_FAST_CHECK
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+ cv2.CALIB_CB_NORMALIZE_IMAGE,
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)
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"""
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If desired number of corner are detected,
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we refine the pixel coordinates and display
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them on the images of checker board
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"""
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if ret == True:
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objpoints.append(objp)
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# Refining pixel coordinates for given 2d points.
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corners2 = cv2.cornerSubPix(gray, corners, (11, 11), (-1, -1), criteria)
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imgpoints.append(corners2)
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# Draw and display the corners
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img = cv2.drawChessboardCorners(img, CHECKERBOARD, corners2, ret)
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cv2.imshow("img", img)
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cv2.waitKey(0)
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cv2.destroyAllWindows()
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h, w = img.shape[:2]
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"""
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Performing camera calibration by
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passing the value of known 3D points (objpoints)
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and corresponding pixel coordinates of the
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detected corners (imgpoints)
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"""
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ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(
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objpoints, imgpoints, gray.shape[::-1], None, None
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)
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print("Camera matrix : \n")
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print(mtx)
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print("dist : \n")
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print(dist)
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print("rvecs : \n")
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print(rvecs)
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print("tvecs : \n")
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print(tvecs)
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