---
title: Labelizer - AI Image Labeling Tool
emoji: 🖼️
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 6.0.2
app_file: app.py
pinned: false
license: mit
python_version: "3.12"
---

# 🖼️ Labelizer - AI Image Labeling Tool

An intelligent image labeling tool that uses Florence-2 vision-language model to automatically generate detailed descriptions for your images. Perfect for creating labeled datasets for machine learning projects.

## ✨ Features

- 🤖 **AI-Powered Labeling**: Uses advanced Florence-2 model for accurate image descriptions
- 📊 **Batch Processing**: Label multiple images at once with progress tracking
- ✏️ **Manual Editing**: Edit generated labels to fit your specific needs
- 📦 **Flexible Export**: Download datasets with organized folder structure or flat format
- 🎨 **User-Friendly Interface**: Clean, intuitive Gradio interface with emoji-enhanced navigation

## 🚀 How to Use

1. **Upload Images**: Click "📁 Upload images" to select multiple image files
2. **Generate Labels**:
   - Click "✨ Generate label" below individual images
   - Or click "🏷️ Labelize all images" for batch processing
3. **Review & Edit**: Modify any generated labels as needed
4. **Download**: Create and download your labeled dataset as a ZIP file

## 🛠️ Technical Details

- **Model**: Florence-2-large-hf for vision-language understanding
- **Framework**: Gradio with ZeroGPU support
- **Supported Formats**: JPG, PNG, GIF, BMP, TIFF, WebP
- **Export Options**: Organized folders (images/ + labels/) or flat structure

## 📋 Supported Tasks

The tool supports various captioning tasks:

- `<MORE_DETAILED_CAPTION>`: Comprehensive image descriptions
- `<DETAILED_CAPTION>`: Detailed but concise descriptions  
- `<CAPTION>`: Basic image captions

## 🎯 Use Cases

- **Machine Learning**: Create labeled datasets for computer vision tasks
- **Content Management**: Organize image collections with descriptions
- **Accessibility**: Generate alt-text for images
- **Research**: Prepare datasets for academic projects

## ⚡ Performance

- Optimized for GPU acceleration with ZeroGPU
- Efficient batch processing for large datasets
- Lazy loading to minimize resource usage

---

Built with ❤️ using [Gradio](https://gradio.app/) and [Florence-2](https://huggingface.co/microsoft/Florence-2-large)