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30 lines
1.3 KiB
Python
30 lines
1.3 KiB
Python
from diffsynth.pipelines.qwen_image import QwenImagePipeline, ModelConfig
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import torch
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from PIL import Image
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pipe = QwenImagePipeline.from_pretrained(
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torch_dtype=torch.bfloat16,
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device="cuda",
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model_configs=[
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ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="transformer/diffusion_pytorch_model*.safetensors"),
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ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="text_encoder/model*.safetensors"),
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ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
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],
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tokenizer_config=ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="tokenizer/"),
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)
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pipe.load_lora(pipe.dit, "models/train/Qwen-Image-EliGen_lora/epoch-4.safetensors")
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entity_prompts = ["A beautiful girl", "sign 'Entity Control'", "shorts", "shirt"]
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global_prompt = "A beautiful girl wearing shirt and shorts in the street, holding a sign 'Entity Control'"
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masks = [Image.open(f"data/example_image_dataset/eligen/{i}.png").convert('RGB') for i in range(len(entity_prompts))]
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image = pipe(global_prompt,
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seed=0,
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height=1024,
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width=1024,
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eligen_entity_prompts=entity_prompts,
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eligen_entity_masks=masks)
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image.save("Qwen-Image_EliGen.jpg")
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