---
license: apache-2.0
pipeline_tag: image-to-image
tags:
- image-editing
- multi-modal
---

# Text-Vision Co-Instructed Image Editing (TV-Edit)

This repository contains the weights for **TV-Edit**, a Textual-Visual instruction unified Editing framework. TV-Edit jointly models textual instructions as semantic intent and sparse visual instructions (such as points or drags) as spatial guidance to achieve precise and intent-faithful image manipulation.

[**Project Page**](https://xiechenxi99.github.io/TVEdit/) | [**Paper**](https://huggingface.co/papers/2606.16767) | [**GitHub**](https://github.com/PolyU-VCLab/TVEdit)

## Introduction
TV-Edit is designed to unify the strengths of textual instructions and visual prompts. By integrating semantic intent and spatial constraints, TV-Edit leads to more precise spatial control, less instruction ambiguity, and stronger structural consistency than text-only or drag-based alternatives.

## Installation

To set up the environment, run the following commands:

```shell
## git clone the repository
git clone https://github.com/PolyU-VCLab/TVEdit.git
cd TVEdit

# create an environment
conda create -n TVEdit python=3.10
conda activate TVEdit

pip install --upgrade pip
pip install torch==2.5.0+cu121 torchvision==0.20.0+cu121 --index-url https://download.pytorch.org/whl/cu121
pip install transformers==4.52.4 pytorch-lightning==2.4.0 diffusers==0.35.1
```

## Usage

You can run the interactive Gradio demo to test the model:

1. Download the base model checkpoint: [Qwen-Image-Edit](https://huggingface.co/Qwen/Qwen-Image-Edit).
2. Download the trained TV-Edit weights from this repository.
3. [Optional] TV-Edit supports existing trained acceleration LoRA for 4-step editing: [Qwen-Image-Edit-4step](https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Edit-Lightning-4steps-V1.0-bf16.safetensors).
4. Launch the Gradio demo:

```shell
python gradio_demo.py
```

After launching the demo, you can upload an image, draw point trajectories for spatial control, and enter textual instructions for semantic changes.

## Citation

If you find this work helpful, please cite:

```bibtex
@article{xie2026text-vision,
  title={Text-Vision Co-Instructed Image Editing},
  author={Xie, Chenxi and Wu, Yuhui and Yi, Qiaosi and Zhang, Lei},
  journal={arXiv preprint arXiv:2606.16767},
  year={2026},
}
```