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34 lines
1.3 KiB
Python
34 lines
1.3 KiB
Python
import torch
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from PIL import Image
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from diffsynth.pipelines.flux_image import FluxImagePipeline, ModelConfig
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pipe = FluxImagePipeline.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="black-forest-labs/FLUX.1-dev", origin_file_pattern="flux1-dev.safetensors"),
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ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="text_encoder/model.safetensors"),
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ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="text_encoder_2/*.safetensors"),
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ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="ae.safetensors"),
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],
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)
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pipe.load_lora(pipe.dit, "models/train/FLUX.1-dev-EliGen_lora/epoch-4.safetensors", alpha=1)
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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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# generate image
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image = pipe(
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prompt=global_prompt,
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cfg_scale=1.0,
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num_inference_steps=50,
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embedded_guidance=3.5,
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seed=42,
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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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)
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image.save(f"EliGen_lora.png")
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