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171f557 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 | from diffsynth.diffusion.template import TemplatePipeline
from diffsynth.pipelines.flux2_image import Flux2ImagePipeline, ModelConfig
import torch
from modelscope import dataset_snapshot_download
from PIL import Image
pipe = Flux2ImagePipeline.from_pretrained(
torch_dtype=torch.bfloat16,
device="cuda",
model_configs=[
ModelConfig(model_id="black-forest-labs/FLUX.2-klein-base-4B", origin_file_pattern="transformer/*.safetensors"),
ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="text_encoder/*.safetensors"),
ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
],
tokenizer_config=ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="tokenizer/"),
)
template = TemplatePipeline.from_pretrained(
torch_dtype=torch.bfloat16,
device="cuda",
model_configs=[ModelConfig(model_id="DiffSynth-Studio/Template-KleinBase4B-ControlNet")],
)
dataset_snapshot_download(
"DiffSynth-Studio/examples_in_diffsynth",
allow_file_pattern=["templates/*"],
local_dir="data/examples",
)
image = template(
pipe,
prompt="A cat is sitting on a stone, bathed in bright sunshine.",
seed=0, cfg_scale=4, num_inference_steps=50,
template_inputs = [{
"image": Image.open("data/examples/templates/image_depth.jpg"),
"prompt": "A cat is sitting on a stone, bathed in bright sunshine.",
}],
negative_template_inputs = [{
"image": Image.open("data/examples/templates/image_depth.jpg"),
"prompt": "",
}],
)
image.save("image_ControlNet_sunshine.jpg")
image = template(
pipe,
prompt="A cat is sitting on a stone, surrounded by colorful magical particles.",
seed=0, cfg_scale=4, num_inference_steps=50,
template_inputs = [{
"image": Image.open("data/examples/templates/image_depth.jpg"),
"prompt": "A cat is sitting on a stone, surrounded by colorful magical particles.",
}],
negative_template_inputs = [{
"image": Image.open("data/examples/templates/image_depth.jpg"),
"prompt": "",
}],
)
image.save("image_ControlNet_magic.jpg")
|