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Artiprocher
2025-11-17 14:37:10 +08:00
parent 47246060d6
commit 416ff5df74
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examples/flux/model_inference/FLUX.1-dev-InfiniteYou.py Normal file
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import torch
from diffsynth.pipelines.flux_image import FluxImagePipeline, ModelConfig, ControlNetInput
from modelscope import dataset_snapshot_download
from modelscope import snapshot_download
from PIL import Image
import numpy as np
snapshot_download(
"ByteDance/InfiniteYou",
allow_file_pattern="supports/insightface/models/antelopev2/*",
local_dir="models/ByteDance/InfiniteYou",
)
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/*.safetensors"),
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="ae.safetensors"),
ModelConfig(model_id="ByteDance/InfiniteYou", origin_file_pattern="infu_flux_v1.0/aes_stage2/image_proj_model.bin"),
ModelConfig(model_id="ByteDance/InfiniteYou", origin_file_pattern="infu_flux_v1.0/aes_stage2/InfuseNetModel/*.safetensors"),
],
)
dataset_snapshot_download(
dataset_id="DiffSynth-Studio/examples_in_diffsynth",
local_dir="./",
allow_file_pattern=f"data/examples/infiniteyou/*",
)
height, width = 1024, 1024
controlnet_image = Image.fromarray(np.zeros([height, width, 3]).astype(np.uint8))
controlnet_inputs = [ControlNetInput(image=controlnet_image, scale=1.0, processor_id="None")]
prompt = "A man, portrait, cinematic"
id_image = "data/examples/infiniteyou/man.jpg"
id_image = Image.open(id_image).convert('RGB')
image = pipe(
prompt=prompt, seed=1,
infinityou_id_image=id_image, infinityou_guidance=1.0,
controlnet_inputs=controlnet_inputs,
num_inference_steps=50, embedded_guidance=3.5,
height=height, width=width,
)
image.save("man.jpg")
prompt = "A woman, portrait, cinematic"
id_image = "data/examples/infiniteyou/woman.jpg"
id_image = Image.open(id_image).convert('RGB')
image = pipe(
prompt=prompt, seed=1,
infinityou_id_image=id_image, infinityou_guidance=1.0,
controlnet_inputs=controlnet_inputs,
num_inference_steps=50, embedded_guidance=3.5,
height=height, width=width,
)
image.save("woman.jpg")