This project is inspired by this excellent blogpost: https://www.sentiance.com/2018/05/03/venue-mapping/

Elaborate instructions are provided in the Readme file.

Alternatively, you can blindly use load.sh file after changing the path to the pbf file to create the file server. lat2tile.py has a quick utility function to generate all the tiles for the US-west region. You can generate a list of urls using the following. Once you have the following and download the tiles.

# download the us-west-latest.osm.pbf and change the path in load.sh
sh load.sh
python lat2tile.py > urls.txt

# start the server
docker run -p 80:80 -v openstreetmap-data:/var/lib/postgresql/10/main -d overv/openstreetmap-tile-server run
cat urls.txt | xargs -P 10 -n 1 wget -nH -nc -x

conda env create -f  environment.yml
conda activate loc2vec
git clone https://github.com/NVIDIA/apex
cd apex
pip install -v --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" .
cd ..
python loc2vec

• Siamese-Triplet Implementation - https://github.com/adambielski/siamese-triplet
• OpenstreetMap TileServer - https://github.com/Overv/openstreetmap-tile-server

First thanks! Below are a few things to implement. If you are a GIS expert, we can brainstorm a few ideas for collaboration. Open a issue and we can discuss there.

• Profile and remove CPU bottleneck
• Add a conda environment file to make it self contained
• Add ability to suspend and resume from training
• Ability to save checkpoint even mid-epoch based on number of hard triplets
• Add support for Fast.ai, esp Stocastic weight averaging & One cycle learning