---
license: other
license_name: bria-2.3
license_link: https://bria.ai/bria-huggingface-model-license-agreement/
inference: false
tags:
- text-to-image
- controlnet model
- legal liability
- commercial use
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  agreed upon. Fill in the form below and we reach out to you.
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---

# BRIA 2.3 ControlNet Pose Model Card


BRIA 2.3 ControlNet-Pose, trained on the foundation of [BRIA 2.3 Text-to-Image](https://huggingface.co/briaai/BRIA-2.3), enables the generation of high-quality images guided by a textual prompt and the human pose estimation of the input image. This allows for the creation of different variations of an image, all sharing the same human pose. 


[BRIA 2.3](https://huggingface.co/briaai/BRIA-2.3) was trained from scratch exclusively on licensed data from our esteemed data partners. Therefore, they are safe for commercial use and provide full legal liability coverage for copyright and privacy infringement, as well as harmful content mitigation. That is, our dataset does not contain copyrighted materials, such as fictional characters, logos, trademarks, public figures, harmful content, or privacy-infringing content.

Join our [Discord community](https://discord.gg/Nxe9YW9zHS) for more information, tutorials, tools, and to connect with other users!

![controlnet_pose_showoff.png](https://huggingface.co/briaai/BRIA-2.3-ControlNet-Pose/resolve/main/controlnet_pose_showoff.png)


### Model Description
- **Developed by:** BRIA AI
- **Model type:** [ControlNet](https://huggingface.co/docs/diffusers/using-diffusers/controlnet) for Latent diffusion
- **License:** [bria-2.3](https://bria.ai/bria-huggingface-model-license-agreement/)

- **Model Description:** ControlNet Pose for BRIA 2.3  Text-to-Image model. The model generates images guided by text and the grayscale image of the conditioned image.
- **Resources for more information:** [BRIA AI](https://bria.ai/)


### Get Access
BRIA 2.3 ControlNet-Pose requires access to BRIA 2.3 Text-to-Image. For more information, [click here](https://huggingface.co/briaai/BRIA-2.3).






### Code example using Diffusers 
1. Install https://github.com/patrickvonplaten/controlnet_aux

```sh
$ pip install controlnet_aux
```

2. Let's install `diffusers` and related packages:

```
$ pip install diffusers transformers accelerate
```


```py
from diffusers import ControlNetModel, StableDiffusionXLControlNetPipeline
from controlnet_aux import OpenposeDetector
import torch
from diffusers.utils import load_image

controlnet = ControlNetModel.from_pretrained(
    "briaai/BRIA-2.3-ControlNet-Pose",
    torch_dtype=torch.float16
)

pipe = StableDiffusionXLControlNetPipeline.from_pretrained(
    "briaai/BRIA-2.3",
    controlnet=controlnet,
    torch_dtype=torch.float16,
)
pipe.to("cuda")

prompt = "A portrait of a Beautiful and playful ethereal singer, golden designs, highly detailed, blurry background"
negative_prompt = "Logo,Watermark,Text,Ugly,Morbid,Extra fingers,Poorly drawn hands,Mutation,Blurry,Extra limbs,Gross proportions,Missing arms,Mutated hands,Long neck,Duplicate,Mutilated,Mutilated hands,Poorly drawn face,Deformed,Bad anatomy,Cloned face,Malformed limbs,Missing legs,Too many fingers"

# Calculate Pose image
openpose = OpenposeDetector.from_pretrained('lllyasviel/ControlNet')

image = load_image("https://huggingface.co/briaai/BRIA-2.3-ControlNet-Pose/resolve/main/image1.png")

pose_image = openpose(image)

image = pipe(prompt=prompt, negative_prompt=negative_prompt, image=pose_image, controlnet_conditioning_scale=1.0, height=1024, width=1024).images[0]
```