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import torch
from controlnet_aux import CannyDetector
from diffusers import FluxControlPipeline
from diffusers.utils import load_image
from nunchaku import NunchakuFluxTransformer2dModel
from nunchaku.utils import get_precision
precision = get_precision() # auto-detect your precision is 'int4' or 'fp4' based on your GPU
transformer = NunchakuFluxTransformer2dModel.from_pretrained(
f"nunchaku-tech/nunchaku-flux.1-canny-dev/svdq-{precision}_r32-flux.1-canny-dev.safetensors"
)
pipe = FluxControlPipeline.from_pretrained(
"black-forest-labs/FLUX.1-Canny-dev", transformer=transformer, torch_dtype=torch.bfloat16
).to("cuda")
prompt = (
"A robot made of exotic candies and chocolates of different kinds. "
"The background is filled with confetti and celebratory gifts."
)
control_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/robot.png")
processor = CannyDetector()
control_image = processor(
control_image, low_threshold=50, high_threshold=200, detect_resolution=1024, image_resolution=1024
)
image = pipe(
prompt=prompt, control_image=control_image, height=1024, width=1024, num_inference_steps=50, guidance_scale=30.0
).images[0]
image.save(f"flux.1-canny-dev-{precision}.png")

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