HeGeL: A Novel Dataset for Hebrew Geo-Location
Data
The data can be found here - https://github.com/OnlpLab/HeGeL/tree/main/data/human.
The data contains three json files corresponding to three split-sets: train (Tel Aviv), dev (Haifa), and test (Jerusalem).
Each sample contains the following:
- content - place description.
- geometry - the wkt shape of the geolocation of the place.
- goal_point - the centroid of the geometry.
Model
Dependencies
- Pytorch - Machine learning library for Python-related dependencies
- Anaconda - Anaconda includes all the other Python-related dependencies
- ArgParse - Command line parsing in Python
Installation
Below are installation instructions under Anaconda. IMPORTANT: We use python 3.8.15
- Setup a fresh Anaconda environment and install packages:
# create and switch to new anaconda env
$ conda create -n hegel python=3.8.15
$ source activate hegel
# install required packages
$ pip install -r requirements.txtInstructions
- Here are the instructions to use the code base:
Train and Test Model:
- To train the model with options, use the command line:
$ python train.py --options %(For the details of options)
$ python train.py [-h] [short_name_arg] %(For explanation on the commands)