gabrielilharco/snap-n-eat

Food detection and recommendation with deep learning

49
/ 100
Emerging

Combines ResNeXt-101 finetuned on Food-101 (achieving 71% accuracy) with nutritional recommendation via n-dimensional distance in nutrient space, then surfaces nearby restaurants serving suggested meals. Built on PyTorch/fastai for model training and Flask/Node.js for the web application, with microservices handling prediction, feature extraction, and meal ranking.

289 stars. No commits in the last 6 months.

Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 23 / 25

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Stars

289

Forks

74

Language

Jupyter Notebook

License

MIT

Last pushed

Mar 01, 2023

Commits (30d)

0

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