Loading autocnet/cg/cg.py +5 −1 Original line number Diff line number Diff line Loading @@ -459,6 +459,7 @@ def distribute_points_in_geom(geom, method="classic", nspts_func=lambda x: ceil(round(x,1)*10), ewpts_func=lambda x: ceil(round(x,1)*5), Session=None, ratio_size=0.1, **kwargs): """ Given a geometry, attempt a basic classification of the shape. Loading Loading @@ -486,6 +487,9 @@ def distribute_points_in_geom(geom, method="classic", ewpts_func : obj Function taking a Number and returning an int ratio_size : float A number that represent the minimum size the ratio is set at to be considered a sliver. Returns ------- Loading Loading @@ -532,7 +536,7 @@ def distribute_points_in_geom(geom, method="classic", ew = True # Decision Tree if ratio < 0.1 and geom.area < 0.01: if ratio < ratio_size and geom.area < 0.01: # Class: Slivers - ignore. return np.array([]) elif geom.area <= 0.004 and ratio >= 0.25: Loading autocnet/spatial/overlap.py +8 −6 Original line number Diff line number Diff line Loading @@ -11,7 +11,6 @@ import shapely import sqlalchemy from plio.io.io_gdal import GeoDataset from math import floor from autocnet.cg import cg as compgeom from autocnet.graph.node import NetworkNode Loading Loading @@ -76,6 +75,7 @@ def place_points_in_overlap(overlap, point_type=2, ncg=None, use_cache=False, ratio_size=0.1, **kwargs): """ Place points into an overlap geometry by back-projecting using sensor models. Loading Loading @@ -114,6 +114,10 @@ def place_points_in_overlap(overlap, messages to the point_insert (defined in ncg.config) redis queue for asynchronous (higher performance) inserts. ratio_size : float Used in calling the function distribute_points_in_geom to determine the minimum size the ratio can be to be considered a sliver and ignored. Returns ------- points : list of Points Loading Loading @@ -146,7 +150,7 @@ def place_points_in_overlap(overlap, ta = time.time() # Determine the point distribution in the overlap geom geom = overlap.geom valid = compgeom.distribute_points_in_geom(geom, **distribute_points_kwargs, **kwargs) valid = compgeom.distribute_points_in_geom(geom, ratio_size=ratio_size, **distribute_points_kwargs, **kwargs) if not valid.any(): warnings.warn(f'Failed to distribute points in overlap {overlap.id}') return [] Loading Loading @@ -218,8 +222,7 @@ def place_points_in_overlap(overlap, # kps are in the image space with upper left origin and the roi # could be the requested size or smaller if near an image boundary. # So use the roi upper left_x and top_y for the actual origin. left_x = floor(image_roi.x) - image_roi.size_x top_y = floor(image_roi.y) - image_roi.size_y left_x, _, top_y, _ = image_roi.image_extent newsample = left_x + interesting.x newline = top_y + interesting.y Loading Loading @@ -449,8 +452,7 @@ def place_points_in_image(image, # kps are in the image space with upper left origin and the roi # could be the requested size or smaller if near an image boundary. # So use the roi upper left_x and top_y for the actual origin. left_x = floor(image_roi.x) - image_roi.size_x top_y = floor(image_roi.y) - image_roi.size_y left_x, _, top_y, _ = image_roi.image_extent newsample = left_x + interesting.x newline = top_y + interesting.y Loading Loading
autocnet/cg/cg.py +5 −1 Original line number Diff line number Diff line Loading @@ -459,6 +459,7 @@ def distribute_points_in_geom(geom, method="classic", nspts_func=lambda x: ceil(round(x,1)*10), ewpts_func=lambda x: ceil(round(x,1)*5), Session=None, ratio_size=0.1, **kwargs): """ Given a geometry, attempt a basic classification of the shape. Loading Loading @@ -486,6 +487,9 @@ def distribute_points_in_geom(geom, method="classic", ewpts_func : obj Function taking a Number and returning an int ratio_size : float A number that represent the minimum size the ratio is set at to be considered a sliver. Returns ------- Loading Loading @@ -532,7 +536,7 @@ def distribute_points_in_geom(geom, method="classic", ew = True # Decision Tree if ratio < 0.1 and geom.area < 0.01: if ratio < ratio_size and geom.area < 0.01: # Class: Slivers - ignore. return np.array([]) elif geom.area <= 0.004 and ratio >= 0.25: Loading
autocnet/spatial/overlap.py +8 −6 Original line number Diff line number Diff line Loading @@ -11,7 +11,6 @@ import shapely import sqlalchemy from plio.io.io_gdal import GeoDataset from math import floor from autocnet.cg import cg as compgeom from autocnet.graph.node import NetworkNode Loading Loading @@ -76,6 +75,7 @@ def place_points_in_overlap(overlap, point_type=2, ncg=None, use_cache=False, ratio_size=0.1, **kwargs): """ Place points into an overlap geometry by back-projecting using sensor models. Loading Loading @@ -114,6 +114,10 @@ def place_points_in_overlap(overlap, messages to the point_insert (defined in ncg.config) redis queue for asynchronous (higher performance) inserts. ratio_size : float Used in calling the function distribute_points_in_geom to determine the minimum size the ratio can be to be considered a sliver and ignored. Returns ------- points : list of Points Loading Loading @@ -146,7 +150,7 @@ def place_points_in_overlap(overlap, ta = time.time() # Determine the point distribution in the overlap geom geom = overlap.geom valid = compgeom.distribute_points_in_geom(geom, **distribute_points_kwargs, **kwargs) valid = compgeom.distribute_points_in_geom(geom, ratio_size=ratio_size, **distribute_points_kwargs, **kwargs) if not valid.any(): warnings.warn(f'Failed to distribute points in overlap {overlap.id}') return [] Loading Loading @@ -218,8 +222,7 @@ def place_points_in_overlap(overlap, # kps are in the image space with upper left origin and the roi # could be the requested size or smaller if near an image boundary. # So use the roi upper left_x and top_y for the actual origin. left_x = floor(image_roi.x) - image_roi.size_x top_y = floor(image_roi.y) - image_roi.size_y left_x, _, top_y, _ = image_roi.image_extent newsample = left_x + interesting.x newline = top_y + interesting.y Loading Loading @@ -449,8 +452,7 @@ def place_points_in_image(image, # kps are in the image space with upper left origin and the roi # could be the requested size or smaller if near an image boundary. # So use the roi upper left_x and top_y for the actual origin. left_x = floor(image_roi.x) - image_roi.size_x top_y = floor(image_roi.y) - image_roi.size_y left_x, _, top_y, _ = image_roi.image_extent newsample = left_x + interesting.x newline = top_y + interesting.y Loading
