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Remove correspondences from translation averaging outliers downstream #755

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merged 4 commits into from
Jan 23, 2024
Merged

Remove correspondences from translation averaging outliers downstream #755

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c59bd49
return inlier idx from ta
akshay-krishnan Dec 5, 2023
cc9c312
Merge branch 'master' of github.com:borglab/gtsfm into ta-outlier-remove
akshay-krishnan Jan 23, 2024
78ea96a
improve doc
akshay-krishnan Jan 23, 2024
962235e
fix tests
akshay-krishnan Jan 23, 2024
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4 changes: 2 additions & 2 deletions gtsfm/averaging/translation/averaging_1dsfm.py
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Original file line number Diff line number Diff line change
Expand Up @@ -491,7 +491,7 @@ def run_translation_averaging(
i2Ti1_priors: Dict[Tuple[int, int], PosePrior] = {},
scale_factor: float = 1.0,
gt_wTi_list: List[Optional[Pose3]] = [],
) -> Tuple[List[Optional[Pose3]], Optional[GtsfmMetricsGroup]]:
) -> Tuple[List[Optional[Pose3]], Optional[GtsfmMetricsGroup], Optional[List[Tuple[int, int]]]]:
"""Run the translation averaging.

Args:
Expand Down Expand Up @@ -565,7 +565,7 @@ def run_translation_averaging(
ta_metrics.add_metric(GtsfmMetric("outlier_rejection_duration_sec", inlier_computation_time))
ta_metrics.add_metric(GtsfmMetric("optimization_duration_sec", averaging_time))

return wTi_list, ta_metrics
return wTi_list, ta_metrics, list(w_i2Ui1_dict_inliers.keys())


def compute_metrics(
Expand Down
6 changes: 3 additions & 3 deletions gtsfm/averaging/translation/translation_averaging_base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -58,7 +58,7 @@ def run_translation_averaging(
i2Ti1_priors: Dict[Tuple[int, int], PosePrior] = {},
scale_factor: float = 1.0,
gt_wTi_list: List[Optional[Pose3]] = [],
) -> Tuple[List[Optional[Pose3]], Optional[GtsfmMetricsGroup]]:
) -> Tuple[List[Optional[Pose3]], Optional[GtsfmMetricsGroup], Optional[List[Tuple[int, int]]]]:
"""Run the translation averaging, and combine the estimated global translations with global rotations.

Args:
Expand Down Expand Up @@ -89,7 +89,7 @@ def create_computation_graph(
i2Ti1_priors: Dict[Tuple[int, int], PosePrior] = {},
scale_factor: float = 1.0,
gt_wTi_list: List[Optional[Pose3]] = [],
) -> Tuple[Delayed, Delayed]:
) -> Tuple[Delayed, Delayed, Delayed]:
"""Create the computation graph for performing translation averaging.

Args:
Expand All @@ -107,7 +107,7 @@ def create_computation_graph(
Global poses wrapped as Delayed.
A GtsfmMetricsGroup with translation averaging metrics wrapped as Delayed.
"""
return dask.delayed(self.run_translation_averaging, nout=2)(
return dask.delayed(self.run_translation_averaging, nout=3)(
num_images=num_images,
i2Ui1_dict=i2Ui1_graph,
wRi_list=wRi_graph,
Expand Down
20 changes: 18 additions & 2 deletions gtsfm/multi_view_optimizer.py
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Expand Up @@ -128,7 +128,7 @@ def create_computation_graph(
)
tracks2d_graph = dask.delayed(get_2d_tracks)(viewgraph_v_corr_idxs_graph, keypoints_list)

wTi_graph, ta_metrics = self.trans_avg_module.create_computation_graph(
wTi_graph, ta_metrics, ta_inlier_idx_i1_i2 = self.trans_avg_module.create_computation_graph(
num_images,
pruned_i2Ui1_graph,
delayed_wRi,
Expand All @@ -138,13 +138,16 @@ def create_computation_graph(
relative_pose_priors,
gt_wTi_list=gt_wTi_list,
)
ta_v_corr_idxs_graph = dask.delayed(filter_corr_by_idx)(viewgraph_v_corr_idxs_graph, ta_inlier_idx_i1_i2)
ta_inlier_tracks_2d_graph = dask.delayed(get_2d_tracks)(ta_v_corr_idxs_graph, keypoints_list)
# TODO(akshay-krishnan): update pose priors also with the same inlier indices.

init_cameras_graph = dask.delayed(init_cameras)(wTi_graph, all_intrinsics)

ba_input_graph, data_assoc_metrics_graph = self.data_association_module.create_computation_graph(
num_images,
init_cameras_graph,
tracks2d_graph,
ta_inlier_tracks_2d_graph,
cameras_gt,
relative_pose_priors,
images,
Expand Down Expand Up @@ -196,3 +199,16 @@ def get_2d_tracks(
) -> List[SfmTrack2d]:
tracks_estimator = CppDsfTracksEstimator()
return tracks_estimator.run(corr_idxs_dict, keypoints_list)


def filter_corr_by_idx(correspondences, idxs):
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nit: missing type annotations

"""Filter correspondences by indices.

Args:
correspondences: Correspondences as a dictionary.
idxs: Indices to filter by.

Returns:
Filtered correspondences.
"""
return {k: v for k, v in correspondences.items() if k in idxs}