cars.applications.sparse_matching.sparse_matching
this module contains the abstract matching application class.
Module Contents
Classes
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: Tuple(CarsDataset, CarsDataset)