cars.applications.triangulation.triangulation_tools
Preprocessing module: contains functions used for triangulation
Module Contents
Functions
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This function will perform triangulation from a disparity map |
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This function will perform triangulation from sift matches |
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Compute points cloud |
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Compute the point cloud height offset from geoid. |
- cars.applications.triangulation.triangulation_tools.triangulate(loader_to_use, configuration, disp_ref: xarray.Dataset, disp_sec: xarray.Dataset = None, im_ref_msk_ds: xarray.Dataset = None, im_sec_msk_ds: xarray.Dataset = None, snap_to_img1: bool = False) Dict[str, xarray.Dataset]
This function will perform triangulation from a disparity map
- Parameters
loader_to_use (str) – geometry loader to use
configuration (StereoConfiguration) – StereoConfiguration
disp_ref – left to right disparity map dataset
disp_sec – if available, the right to left disparity map dataset
im_ref_msk_ds – reference image dataset (image and mask (if indicated by the user) in epipolar geometry)
im_sec_msk_ds – secondary image dataset (image and mask (if indicated by the user) in epipolar geometry)
snap_to_img1 – If True, Lines of Sight of img2 are moved so as to cross those of img1
snap_to_img1 – bool
- Returns
point_cloud as a dictionary of dataset containing:
Array with shape (roi_size_x,roi_size_y,3), with last dimension corresponding to longitude, latitude and elevation
Array with shape (roi_size_x,roi_size_y) with output mask
Array for color (optional): only if color1 is not None
The dictionary keys are :
‘ref’ to retrieve the dataset built from the left to right disparity map
‘sec’ to retrieve the dataset built from the right to left disparity map (if provided in input)
- cars.applications.triangulation.triangulation_tools.triangulate_matches(loader_to_use, configuration, matches, snap_to_img1=False)
This function will perform triangulation from sift matches
- Parameters
loader_to_use (str) – geometry loader to use
configuration (StereoConfiguration) – StereoConfiguration
matches – numpy.array of matches of shape (nb_matches, 4)
snap_to_img1 – If this is True, Lines of Sight of img2 are moved so as to cross those of img1
snap_to_img1 – bool
- Returns
point_cloud as a dataset containing:
Array with shape (nb_matches,1,3), with last dimension corresponding to longitude, latitude and elevation
Array with shape (nb_matches,1) with output mask
- Return type
xarray.Dataset
- cars.applications.triangulation.triangulation_tools.compute_points_cloud(loader_to_use: str, data: xarray.Dataset, cars_conf, grid1: str, grid2: str, roi_key: str, dataset_msk: xarray.Dataset = None) xarray.Dataset
Compute points cloud
- Parameters
loader_to_use (str:param loader_to_use: geometru loader to use) – geometru loader to use
data – The reference to disparity map dataset
cars_conf – cars input configuration dictionary
grid1 – path to the reference image grid file
grid2 – path to the secondary image grid file
roi_key – roi of the disparity map key (‘roi’ if cropped while calling create_disp_dataset, otherwise ‘roi_with_margins’)
dataset_msk – dataset with mask information to use
- Returns
the points cloud dataset
- cars.applications.triangulation.triangulation_tools.geoid_offset(points, geoid)
Compute the point cloud height offset from geoid.
- Parameters
points (xarray.Dataset) – point cloud data in lat/lon/alt WGS84 (EPSG 4326) coordinates.
geoid (xarray.Dataset) – geoid elevation data.
- Returns
the same point cloud but using geoid as altimetric reference.
- Return type
xarray.Dataset