def test_calibrate_compensate_distortion_realdata():
ds = datasets.calibration_ipv40CCD_distortion()
res = calibrate_distortion(ds, (7, 7))
ds_comp = compensate_distortion(ds, *res)
for img, comp in zip(ds, ds_comp):
assert_equal(comp.data.mean(), img.data.mean(), 0.01 * img.data.max())
def test_compensate_distortion_identity():
imgs = datasets.calibration_ipv40CCD_distortion(N=2)
mtx = np.identity(3)
dist = np.zeros((1, 5), dtype=np.float32)
roi = (0, 0, imgs.shape[0], imgs.shape[1])
imgs_comp = compensate_distortion(imgs, mtx, dist, mtx, roi)
assert (imgs_comp[0].data - imgs[0].data).sum() == 0
assert (imgs_comp[1].data - imgs[1].data).sum() == 0
def test_calibrate_distortion():
ds = datasets.calibration_ipv40CCD_distortion(N=3)
res = calibrate_distortion(ds, (7, 7))
assert len(res) == 4
assert res[0].shape == (3, 3)
assert res[1].shape == (1, 5)
assert res[2].shape == (3, 3)
assert len(res[3]) == 4
def test_calibration_object(tmp_path: Path):
ff_imgs, ex_list = _prepare_ff_data()
test_img = _prepare_ff_test_img()
dist_imgs = datasets.calibration_ipv40CCD_distortion(N=8)
# perform calibration
calib = Calibration()
calib.calibrate_flatfield(images=ff_imgs, targets=ex_list)
calib.calibrate_distortion(images=dist_imgs, checkerboard_size=(7, 7))
# save to disk
calib.save(tmp_path / "calib.pck")
# load from disk
calib_loaded = load_calibration(tmp_path / "calib.pck")
# perform compensation with both
comp = calib.process(test_img)
comp_loaded = calib_loaded.process(test_img)
# assert both result in the same image
assert_equal(comp.data, comp_loaded.data)