############### Input/Output ###############
# Input/output files.
# Set these if a matches file is not present. Images should be a filepath with a
# wildcard e.g., /home/my_username/my_images/*.jpg
--images=
--output_matches_file=

# If a matches file has already been created, set the filepath here. This avoids
# having to recompute all features and matches.
--matches_file=

# The calibration file indicates possibly known calibration e.g, from EXIF or
# explicit calibration. Theia attempts to extract EXIF focal lengths if calibration
# is not supplied for a given image.
--calibration_file=
--output_reconstruction=

############### Multithreading ###############
# Set to the number of threads you want to use.
--num_threads=16

############### Feature Extraction ###############
--descriptor=SIFT
--feature_density=NORMAL

############### Matching Options ###############
# Perform matching out-of-core. If set to true, the matching_working_directory
# must be set to a valid, writable directory (the directory will be created if
# it does not exits) Set to false to perform all-in-memory matching.
--match_out_of_core=true

# During feature matching, features are saved to disk so that out-of-core
# matching may be performed. This directory specifies which directory those
# features should be saved to.
--matching_working_directory=

# During feature matching we utilize an LRU cache for out-of-core matching. The size
# of that cache (in terms of number of images) is controlled by this parameter. The
# higher this number the more memory is required.
--matching_max_num_images_in_cache=128

--matching_strategy=CASCADE_HASHING
--lowes_ratio=0.75
--min_num_inliers_for_valid_match=30
# NOTE: This threshold is relative to an image with a width of 1024 pixels. It
# will be scaled appropriately based on the image resolutions. This allows a
# single threshold to be used for images with different resolutions.
--max_sampson_error_for_verified_match=6.0
--bundle_adjust_two_view_geometry=true
--keep_only_symmetric_matches=true

# Global descriptor extractor settings. The global image descriptors are used to
# speed up matching by selected the K most similar images for each image, and
# only performing feature matching with these images.
--num_nearest_neighbors_for_global_descriptor_matching=100
--num_gmm_clusters_for_fisher_vector=16
--max_num_features_for_fisher_vector_training=1000000

############### General SfM Options ###############
--reconstruction_estimator=GLOBAL
--min_track_length=2
--max_track_length=50
--reconstruct_largest_connected_component=false

# Set to true if all views were captured with the same camera. If true, then a
# single set of camera intrinsic parameters will be used for all views in the
# reconstruction.
--shared_calibration=false

# If set to true, only views with known calibration are reconstructed.
--only_calibrated_views=false

############### Global SfM Options ###############
--global_position_estimator=LEAST_UNSQUARED_DEVIATION
--global_rotation_estimator=ROBUST_L1L2
--post_rotation_filtering_degrees=15.0

# This refinement is very unstable for rotation-only motions so
# it is advised that this is set to false for these motions.
--refine_relative_translations_after_rotation_estimation=true

# If true, only cameras that are well-conditioned for position estimation will
# be used for global position estimation
--extract_maximal_rigid_subgraph=false

# Filter the relative translations with the 1DSfM filter to remove potential
# outliers in the relative pose measurements.
--filter_relative_translations_with_1dsfm=true

# Nonlinear position estimation options
--position_estimation_min_num_tracks_per_view=0
--position_estimation_robust_loss_width=0.1

# If true, perform a single iteration of bundle adjustment only on the camera
# positions and 3D points (rotation and camera intrinsics are held
# constant). This helps often to constrain inaccurate intrinsics.
--refine_camera_positions_and_points_after_position_estimation=true

# After estimating camera poses, we perform trianguation, then BA,
# then filter out bad points. This controls how many times we repeat
# this process.
--num_retriangulation_iterations=1

############### Incremental SfM Options ###############
# NOTE: This threshold is relative to an image with a width of 1024 pixels. It
# will be scaled appropriately based on the image resolutions. This allows a
# single threshold to be used for images with different resolutions.
--absolute_pose_reprojection_error_threshold=4
--partial_bundle_adjustment_num_views=20
--full_bundle_adjustment_growth_percent=5
--min_num_absolute_pose_inliers=30

############### Bundle Adjustment Options ###############
# Set this parameter to a value other than NONE if you want to utilize a robust
# cost function during bundle adjustment. This can increase robustness to outliers
# during the optimization.
--bundle_adjustment_robust_loss_function=HUBER

# Set this value to the determine the reprojection error in pixelst at which
# robustness begins (if a robust cost function is being used).
--bundle_adjustment_robust_loss_width=10.0

# Set this parameter to change which camera intrinsics should be
# optimized. Valid options are NONE, ALL, FOCAL_LENGTH, PRINCIPAL_POINTS,
# RADIAL_DISTORTION, ASPECT_RATIO, and SKEW. This parameter can be set using a
# bitmask (with no spaces) e.g., FOCAL_LENGTH|RADIAL_DISTORTION
--intrinsics_to_optimize=NONE

# After BA, remove any points that have a reprojection error greater
# than this.
--max_reprojection_error_pixels=4.0

############### Track Subsampling Options ###############

# If true, the estimated tracks are subsampled for bundle adjustment to increase
# the efficiency of BA. Tracks are chosen in a way which attempts to constraint
# BA as best as possible. This has been shown to provide a significant speedup
# without reducing the accuracy much (in fact, it increases the accuracy in some
# cases).
--subsample_tracks_for_bundle_adjustment=false

# Subsampled tracks are chosen with a probability related to their track
# length. We limit the effect of long tracks by capping the track length at this
# value for the purpose of selecting tracks.
--track_subset_selection_long_track_length_threshold=10

# Tracks are chosen in a way that ensures each view is spatially
# constraind. Tracks are first binned in an image grid and the top ranked track
# is chosen for optimization from each grid cell to ensure good spatial coverage
# of the image. The grid cells are set to be this size.
--track_selection_image_grid_cell_size_pixels=100

# Tracks are chosen such that each image observes at least this many tracks
#  which are being optimized. This ensures that each image is well-constrained.
--min_num_optimized_tracks_per_view=100

############### Triangulation Options ###############
--min_triangulation_angle_degrees=4.0
--triangulation_reprojection_error_pixels=15.0
--bundle_adjust_tracks=true

############### Logging Options ###############
# Logging verbosity.
--logtostderr
# Increase this number to get more verbose logging.
--v=1