avnishs17/food_not_food

Food vs Not Food Dataset (from Hugging Face ImageNet-1K)

This dataset is a binary classification subset derived from the Hugging Face `imagenet-1k` dataset. It is curated to support the task of distinguishing food images from non-food images.

📦 Dataset Overview

• —Source: `imagenet-1k` on Hugging Face Datasets
• —Classes:
• —food: 40 selected ImageNet classes representing food items (e.g., pizza, banana, hotdog)
• —not_food: 40 selected classes not related to food (e.g., car, clock, dog)
• —Images per class: 100
• —Total images: 8,000 (4,000 food + 4,000 not_food)

ImageNet Food Classification Data Pipeline - Download, Filter & Preprocess

Automated ImageNet-1K dataset preprocessing for binary food classification Code: download_and_preprocess.py

💡 Tip: Use Jupyter notebook to interactively explore WordNet filtering and understand the manual class ID corrections needed for accurate food/non-food separation.