Metadata-Version: 2.1
Name: cifar-utils
Version: 0.2
Author: Jyothsna Lakshminarayanan
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown

# CIFAR-100 Utils

This package provides simple utility functions to help you work with the CIFAR-100 dataset. 

## What is CIFAR-100?

CIFAR-100 is a popular dataset used in machine learning. It contains 100 different classes of images, each with 600 images. These classes range from animals like 'dog' and 'cat', to objects like 'car' and 'plane'. The dataset is divided into 20 superclasses, each of which contains several fine-grained classes.

### What does this package do?

This package gives you the following useful functions:

- **`get_classes()`**: This function returns a list of 100 fine-grained class names (e.g., 'apple', 'dog', 'airplane').
- **`get_super_classes()`**: This function returns a list of 20 broad superclasses (e.g., 'aquatic mammals', 'flowers', 'vehicles').
- **`image_data()`**: This function provides a concise summary of the CIFAR-100 dataset, including image format, matrix explanation, the number of superclasses, and the number of images in each superclass.

These functions are useful when you're working with the CIFAR-100 dataset and want easy access to the class names, superclasses, or need a quick overview of the dataset.

## Installation

You can easily install the package using pip:

```bash
pip install cifar-utils

## Usage

Once you've installed the package, you can use it in your Python code like this:

### 1. Get all class names:

The `get_classes()` function returns a list of 100 fine-grained class names from the CIFAR-100 dataset.

```python
from cifar_utils import get_classes

# Get all class names from CIFAR-100
class_names = get_classes()

# Print the first 10 class names
print(class_names[:10])  

### 2. Get all super class names:

from cifar_utils import get_super_classes

# Get all superclasses
super_classes = get_super_classes()

# Print the first 10 superclasses
print(super_classes[:10])

### 3. Get an overview about the image data:

from cifar_utils import image_data

# Get summary of CIFAR-100 dataset
image_data()

### **Disclaimer**:

I would like to clarify that I **did not copy** any of the content in this package. Any resemblance to other resources or code is purely **coincidental**.

For the **class names** used in this package, I referred to the **Hugging Face** website as a reference, and they were used as a foundation for the functionality in this package.
