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30 lines
1.3 KiB
Python
30 lines
1.3 KiB
Python
import torch
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from PIL import Image
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from diffsynth import save_video, VideoData, download_models
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from diffsynth.pipelines.flux_image_new import FluxImagePipeline, ModelConfig
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from modelscope import dataset_snapshot_download
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#TODO: repalce the local path with model_id
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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/"),
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ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="ae.safetensors"),
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ModelConfig(model_id="InstantX/FLUX.1-dev-IP-Adapter", origin_file_pattern="ip-adapter.bin"),
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ModelConfig(path="models/IpAdapter/InstantX/FLUX.1-dev-IP-Adapter/image_encoder")
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],
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)
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seed = 42
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origin_prompt = "a rabbit in a garden, colorful flowers"
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image = pipe(prompt=origin_prompt, height=1280, width=960, seed=seed)
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image.save("style image.jpg")
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torch.manual_seed(seed)
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image = pipe(prompt="A piggy", height=1280, width=960, seed=seed,
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ipadapter_images=[image], ipadapter_scale=0.7)
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image.save("A piggy.jpg")
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