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37 lines
1.4 KiB
Python
37 lines
1.4 KiB
Python
import numpy as np
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import cv2 as cv
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import glob
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# termination criteria
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criteria = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_MAX_ITER, 30, 0.001)
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# prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
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objp = np.zeros((6*7,3), np.float32)
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objp[:,:2] = np.mgrid[0:7,0:6].T.reshape(-1,2)
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# Arrays to store object points and image points from all the images.
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objpoints = [] # 3d point in real world space
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imgpoints = [] # 2d points in image plane.
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# images = glob.glob('detec/foscam/*.png')
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images = glob.glob('detec/foscam/*.jpg')
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for fname in images:
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img = cv.imread(fname)
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gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
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# Find the chess board corners
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ret, corners = cv.findChessboardCorners(gray, (7,6), None)
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# If found, add object points, image points (after refining them)
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if ret == True:
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objpoints.append(objp)
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corners2 = cv.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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cv.drawChessboardCorners(img, (7,6), corners2, ret)
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cv.imshow('img', img)
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cv.waitKey(500)
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cv.destroyAllWindows()
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ret, mtx, dist, rvecs, tvecs = cv.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)
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img = cv.imread('detec/foscam/1.jpg')
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h, w = img.shape[:2]
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newcameramtx, roi = cv.getOptimalNewCameraMatrix(mtx, dist, (w,h), 1, (w,h)) |