Dataset Viewer
Auto-converted to Parquet Duplicate
image
imagewidth (px)
148
7.36k
label
stringclasses
43 values
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
jalebi
End of preview. Expand in Data Studio

Enhanced Indian Food Classification Dataset

A comprehensive dataset for Indian food classification with 15,404 images across 43 classes.

Dataset Structure

dataset/
├── train/           # Training images
├── validation/      # Validation images  
└── test/           # Test images

Usage

from datasets import load_dataset

# Load dataset
dataset = load_dataset("SohlHealth/enhanced-indian-food-classification")

# Access splits
train_data = dataset['train']
val_data = dataset['validation']
test_data = dataset['test']

# Example: get first image and label
image = train_data[0]['image']
label = train_data[0]['label']

Classes

The dataset includes 43 authentic Indian food categories covering curries, rice dishes, breads, snacks, sweets, and beverages.

License

CC-BY-4.0

Downloads last month
33