Metadata-Version: 2.2
Name: genitext
Version: 0.2.1
Summary: A CLI tool for generating high-quality image-text pairs for AI training
Home-page: https://github.com/CodeKnight314/GenIText
Author: Richard Tang
Author-email: richardgtang@gmail.com
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
License-File: LICENSE
Requires-Dist: torch
Requires-Dist: torchvision
Requires-Dist: Pillow
Requires-Dist: tqdm
Requires-Dist: matplotlib
Requires-Dist: pyyaml
Requires-Dist: bitsandbytes
Requires-Dist: accelerate
Requires-Dist: numpy
Requires-Dist: transformers
Requires-Dist: typing-extensions
Requires-Dist: ollama
Requires-Dist: click
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: requires-dist
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# GenIText: Generative Image-Text Automated package

<p align="center">
  <img src="resources/demo.gif" alt="Demonstration video of GenIText tool">
</p>

## Overview
This repository is independently developed as a felxible framework to generate high-quality Image-Text pairs for finetuning Image-Generation models, such as Stable Diffusion, DALL-E, and other generative models. By leveraging open-source captioning models, GenIText automates the process of generating diverse captions for corresponding images, ensuring that the text data is well-suited for downstream applications such as style-specific generations or domain adaptation. This framework is designed to complement contemporary repositories or modules in the field, offering an additional option for flexibility and automation to create customized datasets.

GenIText will become distributable as a CLI tool once package is ready for testing across systems. Please support in any way you see fit!

## Table of Contents
- [Installation](#installation)
- [Results](#results)
- [Usage](#usage)
  - [Inference](#inference)
  - [Training](#training)
  - [Dataset Preparation](#dataset-preparation)

## Installation
GenIText is available as a Python package and can be installed easily using `pip`. 

To install GenIText, simply run:
```bash
pip install genitext
```
After installation, you can verify that the CLI tool is accessible by running:
```bash 
genitext --help
```
To initiate the CLI tool, run: 
```bash
genitext
```
GenIText incorporates LLMs from Ollama to assist with prompt refinement which means ollama has to be available on the device when running `/refine` in the CLI tool. You can download the software for Mac or Windows OS from [here](https://ollama.com/download/). For Linux OS, you can install directly via the following: 
```bash
curl -fsSL https://ollama.com/install.sh | sh
```
After installing, pull the appropriate LLM you want to use in `/refine`. Currently, the default config is set to `deepseek-r1:7b` since it offers strong performance with it's reasoning capabilities while using relatively trivial memory. Options to switch the LLM in config will be made available soon.
