A very interesting food dish dataset, if you're building a health app/model: 100 k carefully curated food samples spanning home-cooked meals, restaurant dishes, raw ingredients and packaged products.
How it was built is just as valuable
• 50 k real users on Binance captured their own plates and pre-annotated by professional human annotators.
• Machine-generated labels were then spot-checked and refined by Biance users to guarantee quality.
• A slice of the dataset made available on Hugging Face under an OpenRail license.
Sounds like a new approach for crowdsourcing data collection.
Link below:
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