gabbar

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)

Installation

pip install gabbar

Setup

# 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

Prediction

# 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"
    }
]