---
language:
- tr
- en
license: mit
task_categories:
- image-classification
- feature-extraction
- zero-shot-image-classification
tags:
- food
- nutrition
- vision
- calorie-tracking
- turkey
size_categories:
- 10K<n<100K
---

# Turkish Food & Nutrition Vision Dataset (Food v2)

High-resolution, human-POV Turkish food and packaged snack dataset with canonical nutrition macros and portion sizes.

## 📊 Dataset Summary
- **Repository**: `ozertuu/foodv2`
- **Canonical Foods**: 29,840
- **Images Total**: 89,520
- **Average Images / Food**: ~3.0
- **Image Sources**: Yemeksepeti / DeliveryHero, GetirYemek, Migros Sanalmarket, Getir, Nefis Yemek Tarifleri, OpenFoodFacts.

## 🍽️ Features & Schema
- `image`: PIL Image / Raw JPEG bytes
- `food_id`: Unique canonical food UUID
- `name_tr`: Turkish food name
- `name_en`: English translation
- `category`: Macro food category (`proteins`, `sweets`, `vegetables`, `fruits`, `grains`, etc.)
- `calories_100g`, `protein_100g`, `carbs_100g`, `fat_100g`: Canonical macro nutrition per 100g
- `default_serving`, `default_serving_grams`: Standard reference portion
- `source_url`, `source_domain`: Source origin
- `sha256`, `phash`: Deduplication hashes

## 💻 Quickstart in Kaggle / Python

```python
from datasets import load_dataset

# Load entire dataset or stream
dataset = load_dataset("ozertuu/foodv2", split="train")

# Inspect first item
item = dataset[0]
print(item["name_tr"], item["calories_100g"], "kcal")
item["image"].show()
```