Metadata-Version: 2.4
Name: feedback_image_trainer
Version: 0.1.0
Summary: Fine-tune Stable Diffusion with feedback-driven Optuna hyperparameter search
Author: Your Name
Author-email: your.email@example.com
License: MIT
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: torch>=2.0.0
Requires-Dist: diffusers>=0.20.0
Requires-Dist: transformers>=4.30.0
Requires-Dist: accelerate>=0.20.0
Requires-Dist: optuna>=2.0.0
Requires-Dist: torchvision>=0.15.0
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: license
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

#### overview
```markdown
# Feedback Image Trainer

A Python package to fine-tune Stable Diffusion models using feedback-driven hyperparameter search with Optuna.

## Installation

```bash
pip install feedback_image_trainer
```

## Usage

```python
from feedback_image_trainer import run_study

run_study(
    feedback_file="image_feedback.json",
    model_path="runwayml/stable-diffusion-v1-5",
    output_dir="fine_tuned_model",
    trials=5
)
```

## Input Data Format

The `image_feedback.json` file should contain a list of dictionaries with the following structure:

```json
[
    {
        "image_path": "path/to/image.png",
        "prompt": "A description of the image",
        "feedback": 1
    },
    ...
]
```

## Requirements

- Python 3.8+
- torch>=2.0.0
- diffusers>=0.20.0
- transformers>=4.30.0
- accelerate>=0.20.0
- optuna>=2.0.0
- torchvision>=0.15.0

