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refine examples

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Artiprocher
2025-06-25 13:38:21 +08:00
parent 6c8bb6438b
commit b603acd36a
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examples/flux/model_inference/FLUX.1-dev-Controlnet-Union-alpha.py Normal file
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import torch
from diffsynth.pipelines.flux_image_new import FluxImagePipeline, ModelConfig, ControlNetInput
from diffsynth.controlnets.processors import Annotator
from diffsynth import download_models
download_models(["Annotators:Depth"])
pipe = FluxImagePipeline.from_pretrained(
torch_dtype=torch.bfloat16,
device="cuda",
model_configs=[
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="flux1-dev.safetensors"),
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="text_encoder/model.safetensors"),
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="text_encoder_2/"),
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="ae.safetensors"),
ModelConfig(model_id="InstantX/FLUX.1-dev-Controlnet-Union-alpha", origin_file_pattern="diffusion_pytorch_model.safetensors"),
],
)
image_1 = pipe(
prompt="a beautiful Asian girl, full body, red dress, summer",
height=1024, width=1024,
seed=6, rand_device="cuda",
)
image_1.save("image_1.jpg")
image_canny = Annotator("canny")(image_1)
image_depth = Annotator("depth")(image_1)
image_2 = pipe(
prompt="a beautiful Asian girl, full body, red dress, winter",
controlnet_inputs=[
ControlNetInput(image=image_canny, scale=0.3, processor_id="canny"),
ControlNetInput(image=image_depth, scale=0.3, processor_id="depth"),
],
height=1024, width=1024,
seed=7, rand_device="cuda",
)
image_2.save("image_2.jpg")