diffusers_example.py

import torch

from diffusers import FluxControlNetModel, FluxControlNetPipeline
from diffusers.utils import load_image

base_model = "black-forest-labs/FLUX.1-dev"
controlnet_model_union = "Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro-2.0"

controlnet = FluxControlNetModel.from_pretrained(
    controlnet_model_union, torch_dtype=torch.bfloat16
)
pipe = FluxControlNetPipeline.from_pretrained(
    base_model, controlnet=controlnet, torch_dtype=torch.bfloat16
)
pipe.to("cuda")

# replace with other conds
control_image = load_image("./conds/canny.png")
width, height = control_image.size

prompt = (
    "A young girl stands gracefully at the edge of a serene beach, "
    "her long, flowing hair gently tousled by the sea breeze. "
    "She wears a soft, pastel-colored dress that complements the "
    "tranquil blues and greens of the coastal scenery. The golden hues "
    "of the setting sun cast a warm glow on her face, highlighting her "
    "serene expression. The background features a vast, azure ocean with "
    "gentle waves lapping at the shore, surrounded by distant cliffs and a "
    "clear, cloudless sky. The composition emphasizes the girl's serene "
    "presence amidst the natural beauty, with a balanced blend of warm "
    "and cool tones."
)

image = pipe(
    prompt,
    control_image=control_image,
    width=width,
    height=height,
    controlnet_conditioning_scale=0.7,
    control_guidance_end=0.8,
    num_inference_steps=30,
    guidance_scale=3.5,
    generator=torch.Generator(device="cuda").manual_seed(42),
).images[0]