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20 lines
1003 B
Python
20 lines
1003 B
Python
from PIL import Image
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import torch
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from diffsynth.pipelines.qwen_image import QwenImagePipeline, ModelConfig
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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-In-Context-Control-Union_lora/epoch-4.safetensors")
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image = Image.open("data/example_image_dataset/canny/image_1.jpg").resize((1024, 1024))
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prompt = "Context_Control. a dog"
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image = pipe(prompt=prompt, seed=0, context_image=image, height=1024, width=1024)
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image.save("image_context.jpg")
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