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calorie-lens

shalev396

A photo of a meal goes in; out come **the ingredients on the plate, how many grams of each, and the nutrition of every ingredient and of the whole plate** (kcal, protein, fat, carbs, fiber, sugars, saturated fat, sodium). It is two models fused into one network, trained on the Nutrition5k dishes, whose every ingredient was weighed on a scale, on plates weighed at a Finnish lunch line (FlavoriaFoodWeight1700) and on USDA FoodData Central. `config.json` records `pretrained: false`; `model.load()` rebuilds every network from `config.json` and loads `model.safetensors`, so inference never downloads a base model. The weights load with `transformers` versions before and after 5.18, which renamed DINOv2's attention layers. **Space API (free):** the Space exposes `/predict` (photo + optional total grams in, `[result, seconds, device]` out).

Image classification

Input Image→ Output Not verified

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Monthly input tokens 10 MMonthly output tokens 2 M1 M = 1 million tokens · USD
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calorie-lens

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