Fix 4.3 python style
parent
12f919dc55
commit
2f2d6546d1
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@ -4,14 +4,15 @@ Authors: John Lambert
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"""
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import unittest
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from typing import Dict, List, Tuple
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from typing import Dict, Tuple
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import numpy as np
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from gtsam.gtsfm import Keypoints
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from gtsam.utils.test_case import GtsamTestCase
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import gtsam
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from gtsam import IndexPair, Point2, SfmTrack2d
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from gtsam import (IndexPair, KeypointsVector, MatchIndicesMap, Point2,
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SfmMeasurementVector, SfmTrack2d)
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class TestDsfTrackGenerator(GtsamTestCase):
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@ -22,20 +23,21 @@ class TestDsfTrackGenerator(GtsamTestCase):
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) -> None:
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"""Tests DSF for non-transitive matches.
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Test will result in no tracks since nontransitive tracks are naively discarded by DSF.
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Test will result in no tracks since nontransitive tracks are naively
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discarded by DSF.
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"""
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keypoints_list = get_dummy_keypoints_list()
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nontransitive_matches_dict = get_nontransitive_matches() # contains one non-transitive track
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keypoints = get_dummy_keypoints_list()
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nontransitive_matches = get_nontransitive_matches()
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# For each image pair (i1,i2), we provide a (K,2) matrix
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# of corresponding keypoint indices (k1,k2).
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matches_dict = {}
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for (i1,i2), corr_idxs in nontransitive_matches_dict.items():
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matches_dict[IndexPair(i1, i2)] = corr_idxs
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matches = MatchIndicesMap()
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for (i1, i2), correspondences in nontransitive_matches.items():
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matches[IndexPair(i1, i2)] = correspondences
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tracks = gtsam.gtsfm.tracksFromPairwiseMatches(
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matches_dict,
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keypoints_list,
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matches,
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keypoints,
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verbose=True,
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)
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self.assertEqual(len(tracks), 0, "Tracks not filtered correctly")
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@ -47,20 +49,20 @@ class TestDsfTrackGenerator(GtsamTestCase):
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kps_i1 = Keypoints(np.array([[50.0, 60], [70, 80], [90, 100]]))
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kps_i2 = Keypoints(np.array([[110.0, 120], [130, 140]]))
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keypoints_list = []
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keypoints_list.append(kps_i0)
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keypoints_list.append(kps_i1)
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keypoints_list.append(kps_i2)
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keypoints = KeypointsVector()
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keypoints.append(kps_i0)
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keypoints.append(kps_i1)
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keypoints.append(kps_i2)
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# For each image pair (i1,i2), we provide a (K,2) matrix
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# of corresponding keypoint indices (k1,k2).
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matches_dict = {}
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matches_dict[IndexPair(0, 1)] = np.array([[0, 0], [1, 1]])
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matches_dict[IndexPair(1, 2)] = np.array([[2, 0], [1, 1]])
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# of corresponding image indices (k1,k2).
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matches = MatchIndicesMap()
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matches[IndexPair(0, 1)] = np.array([[0, 0], [1, 1]])
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matches[IndexPair(1, 2)] = np.array([[2, 0], [1, 1]])
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tracks = gtsam.gtsfm.tracksFromPairwiseMatches(
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matches_dict,
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keypoints_list,
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matches,
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keypoints,
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verbose=False,
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)
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assert len(tracks) == 3
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@ -110,17 +112,16 @@ class TestSfmTrack2d(GtsamTestCase):
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def test_sfm_track_2d_constructor(self) -> None:
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"""Test construction of 2D SfM track."""
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measurements = []
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measurements = SfmMeasurementVector()
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measurements.append((0, Point2(10, 20)))
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track = SfmTrack2d(measurements=measurements)
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track.measurement(0)
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assert track.numberMeasurements() == 1
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def get_dummy_keypoints_list() -> List[Keypoints]:
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""" """
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def get_dummy_keypoints_list() -> KeypointsVector:
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"""Generate a list of dummy keypoints for testing."""
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img1_kp_coords = np.array([[1, 1], [2, 2], [3, 3.]])
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img1_kp_scale = np.array([6.0, 9.0, 8.5])
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img2_kp_coords = np.array(
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[
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[1, 1.],
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@ -156,33 +157,32 @@ def get_dummy_keypoints_list() -> List[Keypoints]:
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[5, 5],
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]
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)
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keypoints_list = [
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Keypoints(coordinates=img1_kp_coords),
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Keypoints(coordinates=img2_kp_coords),
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Keypoints(coordinates=img3_kp_coords),
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Keypoints(coordinates=img4_kp_coords),
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]
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return keypoints_list
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keypoints = KeypointsVector()
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keypoints.append(Keypoints(coordinates=img1_kp_coords))
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keypoints.append(Keypoints(coordinates=img2_kp_coords))
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keypoints.append(Keypoints(coordinates=img3_kp_coords))
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keypoints.append(Keypoints(coordinates=img4_kp_coords))
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return keypoints
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def get_nontransitive_matches() -> Dict[Tuple[int, int], np.ndarray]:
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"""Set up correspondences for each (i1,i2) pair that violates transitivity.
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(i=0, k=0) (i=0, k=1)
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| \\ |
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| \\ |
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(i=1, k=2)--(i=2,k=3)--(i=3, k=4)
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Transitivity is violated due to the match between frames 0 and 3.
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Transitivity is violated due to the match between frames 0 and 3.
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"""
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nontransitive_matches_dict = {
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nontransitive_matches = {
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(0, 1): np.array([[0, 2]]),
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(1, 2): np.array([[2, 3]]),
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(0, 2): np.array([[0, 3]]),
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(0, 3): np.array([[1, 4]]),
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(2, 3): np.array([[3, 4]]),
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}
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return nontransitive_matches_dict
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return nontransitive_matches
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if __name__ == "__main__":
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