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ATROM

this repository provides Code for ijcai2023 paper: Open Anomalous Trajectory Recognition via Probabilistic Metric Learning

Datasets

The datasets used in our paper are collected by Kaggle and DiDi Chuxing. Please download from http://outreach.didichuxing.com/research/opendata and https://www.kaggle.com/c/pkdd-15-predict-taxi-service-trajectory-i/data respectively.

Usage

Run data_process.py to generate and load anomalous trajectories. Run model.py to train and test our model.

Requirements

  • python = 3.7
  • pytorch = 1.8
  • numpy
  • scikit-learn

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