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---
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
- text-to-image
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](https://www.kaggle.com/datasets/anshulmehtakaggl/themassiveindianfooddataset).
This card has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
English
## Dataset Structure
```json
{
"image": "Image(decode=True, id=None)",
"target": "ClassLabel(names=['biryani', 'cholebhature', 'dabeli', 'dal', 'dhokla', 'dosa', 'jalebi', 'kathiroll', 'kofta', 'naan', 'pakora', 'paneer', 'panipuri', 'pavbhaji', 'vadapav'], id=None)"
}
```
### Dataset Splits
This dataset is split into a train and test split. The split sizes are as follows:
| Split name | Num samples |
| ------------ | ------------------- |
| train | 3809 |
| test | 961 |
### 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.
### Dataset Curators
[Anshul Mehta](https://www.kaggle.com/anshulmehtakaggl)
### Licensing Information
[CC0: Public Domain](https://creativecommons.org/publicdomain/zero/1.0/)
### Citation Information
[The Massive Indian Foods Dataset](https://www.kaggle.com/datasets/anshulmehtakaggl/themassiveindianfooddataset) |