def fitter_main(args, fitter):
world_points = gen_target.get_targets()
optlist, _ = getopt.getopt(args[1:], "i:o:")
in_file_name = None
out_file_name = None
for opt, param in optlist:
if opt == "-i":
in_file_name = param
if opt == "-o":
out_file_name = param
if not in_file_name:
raise Exception("Usage: %s -i <input image> [-o <output image>]" % args[0])
print "Loading image (black and white)"
image = cv.LoadImage(in_file_name, False)
print "Loading image (colour)"
color_image = cv.LoadImage(in_file_name, True)
print "Finding labelled circles"
image_features = find_circles.find_labelled_circles(image, annotate_image=color_image, find_ellipses=True)
print "Solving"
R, T, pixel_scale = fitter.solve(world_points, image_features, pixel_scale=2986.3, annotate_image=color_image)
print R, T, pixel_scale
err = calc_reprojection_error(R, T, pixel_scale, world_points, image_features)
print "Reprojection error: %f" % err
draw_reprojected(R, T, pixel_scale, world_points, color_image)
if out_file_name:
cv.SaveImage(out_file_name, color_image)
print "---"
print matrix([[px2 - px1, py2 - py1]])
J = make_barrel_distortion_jacobian(bd, sx, sy)
print (J * matrix([[dsx, dsy, dbd]]).T).T
class CalibrateParser(argparse.ArgumentParser):
def __init__(self):
super(CalibrateParser, self).__init__(description='Calibrate a camera')
self.add_argument('-i', '--input-images', nargs='+', help='Input image', required=True)
if __name__ == "__main__":
args = CalibrateParser().parse_args()
world_circles = gen_target.get_targets()
in_file_names = args.input_images
out_file_names = ["calibrated-%u.png" % i for i in range(len(in_file_names))]
print in_file_names
if not in_file_names:
raise Exception("Usage: %s -i <input image> [-o <output image>]" % sys.argv[0])
print "Loading images (black and white)"
images = [cv.LoadImage(in_file_name, False) for in_file_name in in_file_names]
print "Loading image (colour)"
color_images = [cv.LoadImage(in_file_name, True) for in_file_name in in_file_names]
print "Finding labelled circles"
image_circles = [find_circles.find_labelled_circles(image,
