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altosaar / Food2vec

Licence: mit
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food2vec

Food vectors. Live demo at https://altosaar.github.io/food2vec/, blog post with more information and plots here: https://jaan.io/food2vec-augmented-cooking-machine-intelligence/

Usage

Train a model on the recipes dataset, replicate the results from the blog post:

conda env create -f environment.yml
conda activate food2vec
git clone [email protected]:altosaar/food2vec.git
echo "[submodule \"src/sentence_word2vec\"]
        path = src/sentence_word2vec
        url = https://github.com/altosaar/sentence_word2vec.git
git submodule update --init
cd food2vec/src
./run_fasttext.sh

Visualization & embedding exploration tools

# run t-sne and make the plots for the ingredient embeddings
jupyter notebook ./src/plot_ingredients_recipes.ipynb

Embedding plot.ly plots to host them yourself

https://gist.github.com/altosaar/67d8456ad28acd1abb497f1950d8de8a

Contributing

Pull requests and all feedback welcome! Please file an issue if you run into problems replicating the results.

Ideas on next steps

  • get more data
  • convert jupyter notebook for plotting into one python script
  • write scripts to figure out the right vocabulary
  • fit a better model (e.g. multi-class regression in pytorch) -- if you manage to get better results than the live demo at https://altosaar.github.io/food2vec/ just submit a pull request with the new assets/data/wordVecs.js and I'll happily update it :)
  • compare the above model embeddings to the current embeddings
  • make the UI of the website more user-friendly and mobile-friendly

Acknowledgments

Thanks to Anthony for open-sourcing a javascript embedding browser -- the one here is heavily based on it.

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