readme + req

README.md

@@ -1 +1,107 @@
-# AutoCaptioner
+# AutoCaptioner
+A tool to automatically 
+* generate detailed image captions to train higher-quality LoRA and 
+* optimize your prompts during inference.
+
+<div style="text-align: center;">
+  <img src="examples/caption_example.gif" alt="Captioning Example" width="600"/>
+</div>
+
+## What is AutoCaptioner?
+
+AutoCaptioner creates detailed, principled image captions for your LoRA dataset. These captions can be used to:
+- Train more expressive LoRAs on Flux or SDXL
+- Make inference easy via prompt optimization
+- Save time compared to manual captioning or ignoring captioning
+
+## Installation
+
+### Prerequisites
+- Python 3.11 or higher
+- [Together API](https://together.ai/) account and API key
+
+
+### Setup
+
+1. Create the virtual environment:
+   ```bash
+   python -m venv venv
+   source venv/bin/activate
+   python -m pip install -r requirements.txt
+   ```
+
+2. Set your Together API key: `TOGETHER_API_KEY`
+
+3. Run inference on one set of images:
+
+   ```bash
+   python main.py --input examples/ --output output/
+   ```
+
+   <details>
+   <summary>Arguments</summary>
+
+   - `--input` (str): Directory containing images to caption.
+   - `--output` (str): Directory to save images and captions (defaults to input directory).
+   - `--fix_outfit` (flag): Indicate if character has one outfit (for consistent descriptions).
+   - `--batch_images` (flag): Process images in batches by category.
+   </details>
+
+
+## Gradio Web Interface
+
+Launch a user-friendly web interface for captioning and prompt optimization:
+```bash
+python demo.py
+```
+
+### Features
+
+- High-accuracy image captioning with detailed contextual descriptions
+- Consistent character descriptions when using the outfit flag
+- Batch processing for large image collections
+- Optimized for AI model training datasets
+- Web interface for easy use
+
+## How It Works
+
+AutoCaptioner leverages the Llama-4-Maverick model through the Together AI platform to:
+1. Analyze the visual content of your images
+2. Generate detailed, structured captions
+3. Save the captions as text files alongside your images
+
+## Notes
+- Images are processed individually in standard mode
+- For large collections, batch processing by category is recommended
+- Each caption is saved as a .txt file with the same name as the image
+
+### Troubleshooting
+
+- **API errors**: Ensure your Together API key is set correctly
+- **Unsupported formats**: Only .png, .jpg, .jpeg, and .webp files are supported
+- **Memory issues**: For very large images, try processing in smaller batches
+
+### Examples
+
+<table>
+  <tr>
+    <th>Original Image</th>
+    <th>Generated Caption</th>
+  </tr>
+  <tr>
+    <td><img src="examples/landscape.jpg" alt="Landscape" width="300"/></td>
+    <td>"tr1gger photorealistic, mountain landscape, hiking gear and outdoor clothing, standing at viewpoint, awestruck, snow-capped peaks and valley, golden sunset light, wide-angle view"</td>
+  </tr>
+  <tr>
+    <td><img src="examples/city.jpg" alt="City" width="300"/></td>
+    <td>"tr1gger photorealistic, urban architecture, business suit with briefcase, walking on sidewalk, focused expression, downtown skyscrapers, evening city lights, street-level view"</td>
+  </tr>
+  <tr>
+    <td><img src="examples/food.jpg" alt="Food" width="300"/></td>
+    <td>"tr1gger photorealistic, culinary presentation, chef's uniform and hat, plating dish, concentrated, modern restaurant kitchen, soft studio lighting, overhead camera angle"</td>
+  </tr>
+</table>
+
+## License
+
+[MIT License](LICENSE)

requirements.txt

@@ -1,5 +1,3 @@
-gradio==4.44.1
-Pillow==10.0.0
-pydantic>=2.0.0
-together
-fastapi>=0.100.0
+gradio
+pillow
+together