metadata
frameworks:
- Pytorch
license: Apache License 2.0
tasks:
- text-to-image-synthesis
base_model:
- Qwen/Qwen-Image
base_model_relation: adapter
new_version: DiffSynth-Studio/Qwen-Image-EliGen-V2
Qwen-Image 精确分区控制模型
模型介绍
本模型是基于 Qwen-Image 训练的精确分区控制模型，模型结构为 LoRA，可以通过输入每个实体的文本和区域条件（蒙版图）来控制每个实体的位置和形状。训练框架基于 DiffSynth-Studio 构建，采用的数据集是 DiffSynth-Studio/EliGenTrainSet。
效果展示
| 实体控制条件 | 生成图 |
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推理代码
git clone https://github.com/modelscope/DiffSynth-Studio.git
cd DiffSynth-Studio
pip install -e .
from diffsynth.pipelines.qwen_image import QwenImagePipeline, ModelConfig
from modelscope import dataset_snapshot_download, snapshot_download
import torch
from PIL import Image
pipe = QwenImagePipeline.from_pretrained(
torch_dtype=torch.bfloat16,
device="cuda",
model_configs=[
ModelConfig(model_id="Qwen/Qwen-Image", 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"),
],
tokenizer_config=ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="tokenizer/"),
)
snapshot_download("DiffSynth-Studio/Qwen-Image-EliGen", local_dir="models/DiffSynth-Studio/Qwen-Image-EliGen", allow_file_pattern="model.safetensors")
pipe.load_lora(pipe.dit, "models/DiffSynth-Studio/Qwen-Image-EliGen/model.safetensors")
global_prompt = "Qwen-Image-EliGen魔法咖啡厅的宣传海报，主体是两杯魔法咖啡，一杯冒着火焰，一杯冒着冰锥，背景是浅蓝色水雾，海报写着“Qwen-Image-EliGen魔法咖啡厅”、“新品上市”"
entity_prompts = ["一杯红色魔法咖啡，杯中火焰燃烧", "一杯红色魔法咖啡，杯中冰锥环绕", "字：“新品上市”", "字：“Qwen-Image-EliGen魔法咖啡厅”"]
dataset_snapshot_download(dataset_id="DiffSynth-Studio/examples_in_diffsynth", local_dir="./", allow_file_pattern=f"data/examples/eligen/qwen-image/example_6/*.png")
masks = [Image.open(f"./data/examples/eligen/qwen-image/example_6/{i}.png").convert('RGB').resize((1328, 1328)) for i in range(len(entity_prompts))]
image = pipe(
prompt=global_prompt,
seed=0,
eligen_entity_prompts=entity_prompts,
eligen_entity_masks=masks,
)
image.save("image.jpg")
引用
如果您觉得我们的工作对您有所帮助，欢迎引用我们的成果。
@article{zhang2025eligen,
title={Eligen: Entity-level controlled image generation with regional attention},
author={Zhang, Hong and Duan, Zhongjie and Wang, Xingjun and Chen, Yingda and Zhang, Yu},
journal={arXiv preprint arXiv:2501.01097},
year={2025}
}