shalev396/calorie-lens

image-classification model by shalev396

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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. Python Space API (free): the Space exposes /predict (photo + optional total grams in, [result, seconds, device] out). Inference Endpoint: deploy this repo from its page (Deploy -> Inference Endpoints). handler.py takes an image (Content-Type: image/jpeg, or JSON {"inputs": "", "parameters":…

shalev396/calorie-lens on Hugging Face A short preview, not the full document.

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Inside the original model card — Document outline
  1. Calorie Lens
  2. Model
  3. Usage
  4. Training
  5. Experiments
  6. Evaluation
  7. Limitations

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Model overview

shalev396/calorie-lens is a image-classification model repository published by shalev396 on Hugging Face. A library was not reported.

This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.

Model facts

Task
image-classification
Library
Not reported
Recent downloads (30 days)
104,074
Cumulative likes
2
Hugging Face trending score
1
Reported safetensors parameters
94,637,834
Architecture
Not reported
License
mit
Access
Not gated by Hugging Face
Created
2026-10-10T22:12:41.000Z
Last modified
2026-10-13T04:54:39.000Z

Compatibility and lineage

Language coverage was not reported.

Base-model lineage was not included.

Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.

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Model card and usage instructions

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Source: Hugging Face Hub. Metadata observed 2026-11-01T06:54:32.747Z. Daily imports are snapshots, not real-time monitoring.

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