mirror of
https://github.com/modelscope/DiffSynth-Studio.git
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52 lines
2.0 KiB
Python
52 lines
2.0 KiB
Python
import torch
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from diffsynth.pipelines.flux_image_new import FluxImagePipeline, ModelConfig, ControlNetInput
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from modelscope import dataset_snapshot_download
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from modelscope import snapshot_download
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from PIL import Image
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snapshot_download(
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"ByteDance/InfiniteYou",
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allow_file_pattern="supports/insightface/models/antelopev2/*",
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local_dir="models/ByteDance/InfiniteYou",
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)
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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="ByteDance/InfiniteYou", origin_file_pattern="infu_flux_v1.0/aes_stage2/image_proj_model.bin"),
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ModelConfig(model_id="ByteDance/InfiniteYou", origin_file_pattern="infu_flux_v1.0/aes_stage2/InfuseNetModel/*.safetensors"),
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],
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)
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dataset_snapshot_download(
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dataset_id="DiffSynth-Studio/examples_in_diffsynth",
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local_dir="./",
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allow_file_pattern=f"data/examples/infiniteyou/*",
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)
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prompt = "A man, portrait, cinematic"
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id_image = "data/examples/infiniteyou/man.jpg"
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id_image = Image.open(id_image).convert('RGB')
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image = pipe(
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prompt=prompt, seed=1,
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infinityou_id_image=id_image, infinityou_guidance=1.0,
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num_inference_steps=50, embedded_guidance=3.5,
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height=1024, width=1024,
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)
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image.save("man.jpg")
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prompt = "A woman, portrait, cinematic"
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id_image = "data/examples/infiniteyou/woman.jpg"
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id_image = Image.open(id_image).convert('RGB')
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image = pipe(
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prompt=prompt, seed=1,
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infinityou_id_image=id_image, infinityou_guidance=1.0,
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num_inference_steps=50, embedded_guidance=3.5,
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height=1024, width=1024,
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)
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image.save("woman.jpg") |