metadata
license: cc0-1.0
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': biryani
'1': cholebhature
'2': dabeli
'3': dal
'4': dhokla
'5': dosa
'6': jalebi
'7': kathiroll
'8': kofta
'9': naan
'10': pakora
'11': paneer
'12': panipuri
'13': pavbhaji
'14': vadapav
splits:
- name: train
num_bytes: 611741947.222
num_examples: 3809
- name: test
num_bytes: 153961285
num_examples: 961
download_size: 688922167
dataset_size: 765703232.222
task_categories:
- image-classification
language:
- en
pretty_name: indian-foods
size_categories:
- 1K<n<10K
Dataset Card for Indian Foods Dataset
Dataset Description
- Homepage: https://www.kaggle.com/datasets/anshulmehtakaggl/themassiveindianfooddataset
- Repository: https://www.kaggle.com/datasets/anshulmehtakaggl/themassiveindianfooddataset
- Paper:
- Leaderboard:
- Point of Contact: https://www.kaggle.com/anshulmehtakaggl
Dataset Summary
This is a multi-category(multi-class classification) related Indian food dataset showcasing The-massive-Indian-Food-Dataset. This card has been generated using this raw template.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
English
Dataset Structure
{
"image": <PIL image of the food item>
"label": class
}
where the categories are one of biryani, cholebhature, jalebi, kofta, naan, paneer, panipuri, pavbhaji, dabeli, dhokla, dosa, kathiroll, pakora, vadapav
Data Instances
Each instance is a picture of the Indian food item,along with the category it belongs to.
Initial Data Collection and Normalization
Collection by Scraping data from Google Images + Leveraging some JS Functions. All the images are resized to (300,300) to maintain size uniformity.