mirror of
https://github.com/modelscope/DiffSynth-Studio.git
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46 lines
1.7 KiB
Python
46 lines
1.7 KiB
Python
from diffsynth import ModelManager, FluxImagePipeline, download_customized_models
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from modelscope import dataset_snapshot_download
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from examples.EntityControl.utils import visualize_masks
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from PIL import Image
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import torch
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# download and load model
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model_manager = ModelManager(torch_dtype=torch.bfloat16, device="cuda", model_id_list=["FLUX.1-dev"])
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model_manager.load_lora(
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download_customized_models(
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model_id="DiffSynth-Studio/Eligen",
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origin_file_path="model_bf16.safetensors",
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local_dir="models/lora/entity_control"
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),
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lora_alpha=1
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)
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pipe = FluxImagePipeline.from_model_manager(model_manager)
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# download and load mask images
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dataset_snapshot_download(dataset_id="DiffSynth-Studio/examples_in_diffsynth", local_dir="./", allow_file_pattern="data/examples/eligen/inpaint*")
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masks = [Image.open(f"./data/examples/eligen/inpaint_mask_{i}.png") for i in range(1, 3)]
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input_image = Image.open("./data/examples/eligen/inpaint_image.jpg")
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entity_prompts = ["A person wear red shirt", "Airplane"]
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global_prompt = "A person walking on the path in front of a house; An airplane in the sky"
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negative_prompt = "worst quality, low quality, monochrome, zombie, interlocked fingers, Aissist, cleavage, nsfw, blur"
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# generate image
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image = pipe(
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prompt=global_prompt,
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input_image=input_image,
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cfg_scale=3.0,
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negative_prompt=negative_prompt,
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num_inference_steps=50,
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embedded_guidance=3.5,
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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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enable_eligen_on_negative=False,
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enable_eligen_inpaint=True,
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)
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image.save(f"entity_inpaint.png")
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visualize_masks(image, masks, entity_prompts, f"entity_inpaint_with_mask.png")
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