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Open Source Computer Vision Library
https://opencv.org/
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60 lines
1.9 KiB
60 lines
1.9 KiB
#/usr/bin/env python |
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import numpy as np |
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import cv2 |
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import os |
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from common import splitfn |
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USAGE = ''' |
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USAGE: calib.py [--save <filename>] [--debug <output path>] [--square_size] [<image mask>] |
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''' |
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if __name__ == '__main__': |
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import sys, getopt |
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from glob import glob |
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args, img_mask = getopt.getopt(sys.argv[1:], '', ['save=', 'debug=', 'square_size=']) |
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args = dict(args) |
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try: img_mask = img_mask[0] |
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except: img_mask = '../cpp/left*.jpg' |
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img_names = glob(img_mask) |
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debug_dir = args.get('--debug') |
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square_size = float(args.get('--square_size', 1.0)) |
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pattern_size = (9, 6) |
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pattern_points = np.zeros( (np.prod(pattern_size), 3), np.float32 ) |
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pattern_points[:,:2] = np.indices(pattern_size).T.reshape(-1, 2) |
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pattern_points *= square_size |
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obj_points = [] |
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img_points = [] |
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h, w = 0, 0 |
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for fn in img_names: |
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print 'processing %s...' % fn, |
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img = cv2.imread(fn, 0) |
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h, w = img.shape[:2] |
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found, corners = cv2.findChessboardCorners(img, pattern_size) |
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if found: |
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term = ( cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_COUNT, 30, 0.1 ) |
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cv2.cornerSubPix(img, corners, (5, 5), (-1, -1), term) |
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if debug_dir: |
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vis = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR) |
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cv2.drawChessboardCorners(vis, pattern_size, corners, found) |
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path, name, ext = splitfn(fn) |
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cv2.imwrite('%s/%s_chess.bmp' % (debug_dir, name), vis) |
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if not found: |
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print 'chessboard not found' |
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continue |
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img_points.append(corners.reshape(-1, 2)) |
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obj_points.append(pattern_points) |
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print 'ok' |
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rms, camera_matrix, dist_coefs, rvecs, tvecs = cv2.calibrateCamera(obj_points, img_points, (w, h)) |
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print "RMS:", rms |
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print "camera matrix:\n", camera_matrix |
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print "distortion coefficients: ", dist_coefs.ravel() |
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cv2.destroyAllWindows() |
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