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MLPproject/.venv/lib/python3.12/site-packages/skimage/feature/tests/test_sift.py
2025-10-23 15:44:32 +02:00

180 lines
5.6 KiB
Python

import numpy as np
import pytest
from numpy.testing import assert_almost_equal, assert_equal
from skimage import data
from skimage._shared.testing import run_in_parallel
from skimage.feature import SIFT
from skimage.util.dtype import _convert
img = data.coins()
@run_in_parallel()
@pytest.mark.parametrize('dtype', ['float32', 'float64', 'uint8', 'uint16', 'int64'])
def test_keypoints_sift(dtype):
_img = _convert(img, dtype)
detector_extractor = SIFT()
detector_extractor.detect_and_extract(_img)
exp_keypoint_rows = np.array([18, 18, 19, 22, 26, 26, 30, 31, 31, 32])
exp_keypoint_cols = np.array([331, 331, 325, 330, 310, 330, 205, 323, 149, 338])
exp_octaves = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
exp_position_rows = np.array(
[
17.81909936,
17.81909936,
19.05454661,
21.85933727,
25.54800708,
26.25710504,
29.90826307,
30.78713806,
30.87953572,
31.72557969,
]
)
exp_position_cols = np.array(
[
331.49693187,
331.49693187,
325.24476016,
330.44616424,
310.33932904,
330.46155224,
204.74535177,
322.84100812,
149.43192282,
337.89643013,
]
)
exp_orientations = np.array(
[
0.26391655,
0.26391655,
0.39134262,
1.77063053,
0.98637565,
1.37997279,
0.4919992,
1.48615988,
0.33753212,
1.64859617,
]
)
exp_scales = np.array([2, 2, 1, 3, 3, 1, 2, 1, 1, 1])
exp_sigmas = np.array(
[
1.35160379,
1.35160379,
0.94551567,
1.52377498,
1.55173233,
0.93973722,
1.37594124,
1.06663786,
1.04827034,
1.0378916,
]
)
exp_scalespace_sigmas = np.array(
[
[0.8, 1.00793684, 1.26992084, 1.6, 2.01587368, 2.53984168],
[1.6, 2.01587368, 2.53984168, 3.2, 4.03174736, 5.07968337],
[3.2, 4.03174736, 5.07968337, 6.4, 8.06349472, 10.15936673],
[6.4, 8.06349472, 10.15936673, 12.8, 16.12698944, 20.31873347],
[12.8, 16.12698944, 20.31873347, 25.6, 32.25397888, 40.63746693],
[25.6, 32.25397888, 40.63746693, 51.2, 64.50795775, 81.27493386],
]
)
assert_almost_equal(exp_keypoint_rows, detector_extractor.keypoints[:10, 0])
assert_almost_equal(exp_keypoint_cols, detector_extractor.keypoints[:10, 1])
assert_almost_equal(exp_octaves, detector_extractor.octaves[:10])
assert_almost_equal(
exp_position_rows, detector_extractor.positions[:10, 0], decimal=4
)
assert_almost_equal(
exp_position_cols, detector_extractor.positions[:10, 1], decimal=4
)
assert_almost_equal(
exp_orientations, detector_extractor.orientations[:10], decimal=4
)
assert_almost_equal(exp_scales, detector_extractor.scales[:10])
assert_almost_equal(exp_sigmas, detector_extractor.sigmas[:10], decimal=4)
assert_almost_equal(
exp_scalespace_sigmas, detector_extractor.scalespace_sigmas, decimal=4
)
detector_extractor2 = SIFT()
detector_extractor2.detect(img)
detector_extractor2.extract(img)
assert_almost_equal(
detector_extractor.keypoints[:10, 0], detector_extractor2.keypoints[:10, 0]
)
assert_almost_equal(
detector_extractor.keypoints[:10, 0], detector_extractor2.keypoints[:10, 0]
)
def test_descriptor_sift():
detector_extractor = SIFT(n_hist=2, n_ori=4)
exp_descriptors = np.array(
[
[173, 30, 55, 32, 173, 16, 45, 82, 173, 154, 170, 173, 173, 169, 65, 110],
[173, 30, 55, 32, 173, 16, 45, 82, 173, 154, 170, 173, 173, 169, 65, 110],
[189, 52, 18, 18, 189, 11, 21, 55, 189, 75, 173, 91, 189, 65, 189, 162],
[172, 156, 185, 66, 92, 76, 78, 185, 185, 87, 88, 82, 98, 56, 96, 185],
[216, 19, 40, 9, 196, 7, 57, 36, 216, 56, 158, 29, 216, 42, 144, 154],
[169, 120, 169, 91, 129, 108, 169, 67, 169, 142, 111, 95, 169, 120, 69, 41],
[199, 10, 138, 44, 178, 11, 161, 34, 199, 113, 73, 64, 199, 82, 31, 178],
[154, 56, 154, 49, 144, 154, 154, 78, 154, 51, 154, 83, 154, 154, 154, 72],
[230, 46, 47, 21, 230, 15, 65, 95, 230, 52, 72, 51, 230, 19, 59, 130],
[
155,
117,
154,
102,
155,
155,
90,
110,
145,
127,
155,
50,
57,
155,
155,
70,
],
],
dtype=np.uint8,
)
detector_extractor.detect_and_extract(img)
assert_equal(exp_descriptors, detector_extractor.descriptors[:10])
keypoints_count = detector_extractor.keypoints.shape[0]
assert keypoints_count == detector_extractor.descriptors.shape[0]
assert keypoints_count == detector_extractor.orientations.shape[0]
assert keypoints_count == detector_extractor.octaves.shape[0]
assert keypoints_count == detector_extractor.positions.shape[0]
assert keypoints_count == detector_extractor.scales.shape[0]
assert keypoints_count == detector_extractor.scales.shape[0]
def test_no_descriptors_extracted_sift():
img = np.ones((128, 128))
detector_extractor = SIFT()
with pytest.raises(RuntimeError):
detector_extractor.detect_and_extract(img)