---
title: CIFAR-100 ResNet18 Demo
emoji: 🖼️
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 4.44.0
app_file: app.py
pinned: false
license: mit
models:
  - ivantv/cifar100-resnet18
---

# CIFAR-100 Image Classification Demo

This is a demo Space for the ResNet-18 model trained on CIFAR-100 dataset.

**Model:** [ivantv/cifar100-resnet18](https://huggingface.co/ivantv/cifar100-resnet18)

## Features

- 🎯 **100 Categories** - Classify images into animals, vehicles, objects, plants, and more
- 🚀 **75.84% Accuracy** - High-performance ResNet-18 model
- 📸 **Easy to Use** - Just upload an image and get instant predictions
- 🔝 **Top-5 Predictions** - See the most likely classes with confidence scores

## Model Details

- **Architecture:** ResNet-18
- **Parameters:** 11,220,132
- **Training:** 50 epochs on CIFAR-100
- **Test Accuracy:** 75.84%

## Usage

1. Upload an image using the interface
2. View the top-5 predictions with confidence scores
3. Try different types of images!

## Categories

The model can recognize 100 different categories including:

**Animals:** bear, tiger, elephant, dolphin, fox, lion, wolf, butterfly, etc.  
**Vehicles:** bicycle, bus, train, motorcycle, pickup_truck, etc.  
**Objects:** chair, table, lamp, clock, keyboard, telephone, etc.  
**Plants:** maple_tree, oak_tree, palm_tree, rose, tulip, orchid, etc.  
**Structures:** house, castle, bridge, skyscraper, etc.

## Files

This Space uses:
- `app.py` - Gradio interface
- `requirements.txt` - Dependencies
- Model downloaded from: [ivantv/cifar100-resnet18](https://huggingface.co/ivantv/cifar100-resnet18)

## License

MIT License