cars.applications.sparse_matching.sparse_matching

this module contains the abstract matching application class.

Module Contents

Classes

SparseMatching

SparseMatching
class cars.applications.sparse_matching.sparse_matching.SparseMatching

Bases: cars.applications.application_template.ApplicationTemplate

SparseMatching

available_applications :Dict
default_application = sift
classmethod __init_subclass__(short_name, **kwargs)
abstract get_disparity_margin()

Get disparity margin corresponding to sparse matches

Returns

margin in percent

abstract get_disp_out_reject_percent()

Get disparity_outliers_rejection_percent corresponding to outliers to reject

Returns

margin disparity_outliers_rejection_percent percent

abstract get_margins()

Get margins to use in resampling

:return margins :rtype: xr.Dataset

abstract get_save_matches()

Get save_matches parameter

Returns

true is save_matches activated

Return type

bool

abstract run(epipolar_images_left, epipolar_images_right, disp_to_alt_ratio, orchestrator=None, pair_folder=None, pair_key='PAIR_0', mask1_ignored_by_sift: List[int] = None, mask2_ignored_by_sift: List[int] = None)

Run Matching application.

Create left and right CarsDataset filled with pandas.DataFrame , corresponding to epipolar 2D disparities, on the same geometry that epipolar_images_left and epipolar_images_right.

Parameters

  • epipolar_images_left (CarsDataset) – tiled left epipolar

  • epipolar_images_right (CarsDataset) – tiled right epipolar

  • disp_to_alt_ratio (float) – disp to alti ratio

  • orchestrator – orchestrator used

  • pair_folder (str) – folder used for current pair

  • pair_key (str) – pair key id

  • mask1_ignored_by_sift (list) – values used in left mask to ignore in correlation

  • mask2_ignored_by_sift (list) – values used in right mask to ignore in correlation

:return left matches, right matches :rtype: Tupple(CarsDataset, CarsDataset)