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")