EXPERIMENTAL: UNDER DEVELOPMENT
Guarding OpenStreetMap from invalid or suspicious edits, Gabbar is an alpha package of a pre-trained binary problematic/not problematic classifier that was trained on manually labelled changesets from OpenStreetMap.
https://en.wikipedia.org/wiki/Gabbar_Singh_(character)
pip install gabbar# Setup a virtual environment with Python 3.
mkvirtualenv --python=$(which python3) gabbar_py3
# Install in locally editable (``-e``) mode.
pip install -e .[test]
# Install node dependencies.
npm install
# A prediction of "-1" represents that this feature is an anomaly (outlier).
gabbar 49172351
[
{
"attributes": {
"action_create": 0,
"action_delete": 0,
"action_modify": 1,
"area_of_feature_bbox": 109591.9146,
"feature_name_touched": 0,
"feature_version": 17,
"highway_tag_created": 41,
"highway_tag_deleted": 0,
"highway_value_difference": 0,
"length_of_longest_segment": 0.1577,
"primary_tags_difference": 1
},
"changeset_id": "49172351",
"feature_id": "124863896",
"feature_type": "way",
"prediction": -1,
"score": -0.1493,
"timestamp": "2017-07-10 10:33:02.925012",
"version": "0.6.2"
}
]npm test