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BRIA-2.3-ControlNet-ColorGrid

Image-to-Image
Diffusers
text-to-image
controlnet model
legal liability
commercial use
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metadata
license: other
license_name: bria-2.3
license_link: https://bria.ai/bria-huggingface-model-license-agreement/
pipeline_tag: image-to-image
inference: false
tags:
  - text-to-image
  - controlnet model
  - legal liability
  - commercial use
extra_gated_prompt: >-
  This model weights by BRIA AI can be obtained after a commercial license is
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  By submitting this form, I agree to BRIA’s Privacy policy and Terms & conditions, see links below: checkbox

BRIA 2.3 ControlNet ColorGrid Model Card

BRIA 2.3 ControlNet-ColorGrid, trained on the foundation of BRIA 2.3 Text-to-Image, enables the generation of high-quality images guided by a textual prompt and the extracted color grid from the input image. This allows for the creation of different scenes, all sharing the same color grid.

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.

ColorGrid Example

Model Description

  • Developed by: BRIA AI

  • Model type: ControlNet for Latent diffusion

  • License: bria-2.3

  • Model Description: ControlNet ColorGrid for BRIA 2.3 Text-to-Image model. The model generates images guided by a spatial grid of RGB colors.

  • Resources for more information: BRIA AI

Get Access

BRIA 2.3 ControlNet-ColorGrid requires access to BRIA 2.3 Text-to-Image. For more information, click here.

Code example using Diffusers 

pip install diffusers

from diffusers import ControlNetModel, StableDiffusionXLControlNetPipeline
import torch
from PIL import Image

controlnet = ControlNetModel.from_pretrained(
    "briaai/BRIA-2.3-ControlNet-ColorGrid",
    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"

# Create ColorGrid image
input_image = Image.open('pics/singer.png')
control_image = input_image.resize((16, 16)).resize((1024,1024), Image.NEAREST)

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