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3c11df8 | 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 | from diffsynth.pipelines.qwen_image import QwenImagePipeline, ModelConfig, FlowMatchScheduler
from modelscope import dataset_snapshot_download
from PIL import Image
import torch
pipe = QwenImagePipeline.from_pretrained(
torch_dtype=torch.bfloat16,
device="cuda",
model_configs=[
ModelConfig(model_id="Qwen/Qwen-Image-Edit-2511", origin_file_pattern="transformer/diffusion_pytorch_model*.safetensors"),
ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="text_encoder/model*.safetensors"),
ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
],
processor_config=ModelConfig(model_id="Qwen/Qwen-Image-Edit", origin_file_pattern="processor/"),
)
lora = ModelConfig(
model_id="lightx2v/Qwen-Image-Edit-2511-Lightning",
origin_file_pattern="Qwen-Image-Edit-2511-Lightning-4steps-V1.0-bf16.safetensors"
)
pipe.load_lora(pipe.dit, lora, alpha=1)
pipe.scheduler = FlowMatchScheduler("Qwen-Image-Lightning")
dataset_snapshot_download(
"DiffSynth-Studio/example_image_dataset",
allow_file_pattern="qwen_image_edit/*",
local_dir="data/example_image_dataset",
)
prompt = "生成这两个人的合影"
edit_image = [
Image.open("data/example_image_dataset/qwen_image_edit/image1.jpg"),
Image.open("data/example_image_dataset/qwen_image_edit/image2.jpg"),
]
image = pipe(
prompt,
edit_image=edit_image,
seed=1,
num_inference_steps=4,
height=1152,
width=896,
edit_image_auto_resize=True,
zero_cond_t=True, # This is a special parameter introduced by Qwen-Image-Edit-2511
cfg_scale=1.0,
)
image.save("image.jpg")
# Qwen-Image-Edit-2511 is a multi-image editing model.
# Please use a list to input `edit_image`, even if the input contains only one image.
# edit_image = [Image.open("image.jpg")]
# Please do not input the image directly.
# edit_image = Image.open("image.jpg")
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