AI-ServicesBB/food-waste-dataset

Food Waste Dataset

This dataset contains detailed information about food waste, including images and nutritional information.

Dataset Description

The dataset combines image data with detailed nutritional information for each meal and its ingredients.

Features

For each entry:

• bonid: Unique identifier for each meal
• image: Image of the meal
• Lists per meal (multiple ingredients):
  • Artikelnummer: Article numbers
  • Artikel: Ingredient names
  • Stückartikel: Piece article information
  • Anzahl_Kellen: Number of portions
  • Gewicht_Kelle: Weight per portion
  • Gewicht_Teller: Weight per plate
  • kcal_Teller, kj_Teller: Caloric information
  • Fett_Teller, ges_Fettsäuren_Teller: Fat content
  • Kohlenhydrate_Teller, Zucker_Teller: Carbohydrate content
  • Eiweiß_Teller: Protein content
  • Salz_Teller: Salt content
  • Menge_Rückläufer, Prozent_Rückläufer: Return quantities

Per image measurements:

• Before consumption:
  • Gewicht_vorher: Initial weight
  • kcal_vorher, kj_vorher: Initial calories
  • Fett_vorher, ges_Fettsäuren_vorher: Initial fat content
  • Kohlenhydrate_vorher, Zucker_vorher: Initial carbohydrates
  • Eiweiß_vorher: Initial protein
  • Salz_vorher: Initial salt
• After consumption:
  • Gewicht_nachher: Remaining weight
  • kcal_nachher, kj_nachher: Remaining calories
  • Fett_nachher, ges_fettsäuren_nachher: Remaining fat
  • Kohlenhydrate_nachher, Zucker_nachher: Remaining carbohydrates
  • Eiweiß_nachher: Remaining protein
  • Salz_nachher: Remaining salt

Usage

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("AI-ServicesBB/food-waste-dataset")

# Access an example
example = dataset['train'][0]

# Get image and nutritional data
image = example['image']
ingredients = example['Artikel']
weights = example['Gewicht_Teller']
calories = example['kcal_Teller']

# Get before/after measurements
weight_before = example['Gewicht_vorher']
weight_after = example['Gewicht_nachher']

Dataset Creation

The dataset combines two main sources:

1. Ingredient-specific measurements for each meal
2. Before/after measurements with images for complete meals

All numeric values are standardized to use decimal points (converted from German number format).

Additional Information

• Total number of entries: {len(dataset)}
• Image format: JPEG
• Measurements are in grams, calories, and standard nutritional units