geowatch.tasks.poly_from_point.predict module

class geowatch.tasks.poly_from_point.predict.HeatMapConfig(*args, **kwargs)

Bases: DataConfig

Valid options: []

Parameters:

• *args – positional arguments for this data config

• **kwargs – keyword arguments for this data config

default = {'filepath_output': <Value('output_region.geojson')>, 'filepath_to_images': <Value(None)>, 'filepath_to_points': <Value(None)>, 'filepath_to_region': <Value(None)>, 'filepath_to_sam': <Value(None)>, 'ignore_buffer': <Value(None)>, 'method': <Value('ellipse')>, 'region_id': <Value(None)>, 'size_prior': <Value('20.06063 x 20.0141229 @ 10mGSD')>, 'threshold': <Value(0.45)>, 'time_prior': <Value('1 year')>}

geowatch.tasks.poly_from_point.predict.convert_polygons_to_region_model(utm_polygons, main_region_header, points_gdf_utm, points_gdf_crs84, config)

Given polygons in a CRS, convert them to CRS84 polygon-based RegionModels.

geowatch.tasks.poly_from_point.predict.extract_polygons(im)

geowatch.tasks.poly_from_point.predict.image_predicted(im, geo_polygons_image, filename)

geowatch.tasks.poly_from_point.predict.show_mask(mask, ax, random_color=False)

geowatch.tasks.poly_from_point.predict.load_sam(filepath_to_sam)

geowatch.tasks.poly_from_point.predict.comput_average_boxes(dset)

geowatch.tasks.poly_from_point.predict.get_vidspace_info(video_obj)

Extract information about the videospace of a kwcoco video object

geowatch.tasks.poly_from_point.predict.load_point_annots(filepath_to_points, region_id)

geowatch.tasks.poly_from_point.predict.convert_points_to_poly_with_sam_method(dset, video_obj, points_gdf_utm, config)

geowatch.tasks.poly_from_point.predict.main()

IGNORE:

black /mnt/ssd2/data/test/geowatch/geowatch/tasks/poly_from_point/predict.py pyenv shell 3.10.5 source $(pyenv prefix)/envs/pyenv-geowatch/bin/activate python -m geowatch.tasks.poly_from_point.predict –method ‘box’ from geowatch.tasks.poly_from_point.predict import *