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---
license: other
language:
- en
base_model:
- black-forest-labs/FLUX.1-dev
pipeline_tag: text-to-image
tags:
- diffusers
- controlnet
- Flux
- image-generation
---
# Description
This repository provides a Diffusers version of FLUX.1-dev Depth ControlNet checkpoint by Xlabs AI, [original repo](https://huggingface.co/XLabs-AI/flux-controlnet-depth-v3).
# How to use
This model can be used directly with the diffusers library
```
import torch
from diffusers.utils import load_image
from diffusers import FluxControlNetModel
from diffusers.pipelines import FluxControlNetPipeline
from PIL import Image
import numpy as np
generator = torch.Generator(device="cuda").manual_seed(87544357)
controlnet = FluxControlNetModel.from_pretrained(
"Xlabs-AI/flux-controlnet-depth-diffusers",
torch_dtype=torch.bfloat16,
use_safetensors=True,
)
pipe = FluxControlNetPipeline.from_pretrained(
"black-forest-labs/FLUX.1-dev",
controlnet=controlnet,
torch_dtype=torch.bfloat16
)
pipe.to("cuda")
control_image = load_image("https://huggingface.co/Xlabs-AI/flux-controlnet-depth-diffusers/resolve/main/depth_example.png")
prompt = "photo of fashion woman in the street"
image = pipe(
prompt,
control_image=control_image,
controlnet_conditioning_scale=0.7,
num_inference_steps=25,
guidance_scale=3.5,
height=768,
width=1024,
generator=generator,
num_images_per_prompt=1,
).images[0]
image.save("output_test_controlnet.png")
```
## License
Our weights fall under the [FLUX.1 [dev]](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md) Non-Commercial License<br/> |