---
license: apache-2.0
language:
- en
library_name: diffusers
pipeline_tag: text-to-image
---

# InstantID Model Card

<div align="center">

[**Project Page**](https://instantid.github.io/) **|** [**Paper**](https://arxiv.org/abs/2401.07519) **|** [**Code**](https://github.com/InstantID/InstantID) **|** [🤗 **Gradio demo**](https://huggingface.co/spaces/InstantX/InstantID)


</div>

## Introduction

InstantID is a new state-of-the-art tuning-free method to achieve ID-Preserving generation with only single image.

<div  align="center">
![results](./examples/0.png)
</div>


## Usage

You can directly download the model in this repository.
You also can download the model in python script:

```python
from huggingface_hub import hf_hub_download
hf_hub_download(repo_id="InstantX/InstantID", local_dir="./checkpoints")
```


```python

import cv2
from insightface.app import FaceAnalysis
import torch

app = FaceAnalysis(name="buffalo_l", providers=['CUDAExecutionProvider', 'CPUExecutionProvider'])
app.prepare(ctx_id=0, det_size=(640, 640))

image = cv2.imread("person.jpg")
faces = app.get(image)

faceid_embeds = torch.from_numpy(faces[0].normed_embedding).unsqueeze(0)
```

For more details, please follow the instructions in our [GitHub repository](https://github.com/InstantID/InstantID). 


## Disclaimer

This project is released under Apache License and aims to positively impact the field of AI-driven image generation. Users are granted the freedom to create images using this tool, but they are obligated to comply with local laws and utilize it responsibly. The developers will not assume any responsibility for potential misuse by users.

## Citation
```bibtex
@article{wang2024instantid,
  title={InstantID: Zero-shot Identity-Preserving Generation in Seconds},
  author={Wang, Qixun and Bai, Xu and Wang, Haofan and Qin, Zekui and Chen, Anthony},
  journal={arXiv preprint arXiv:2401.07519},
  year={2024}
}
```