53 lines
1.4 KiB
Python
53 lines
1.4 KiB
Python
import os
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import random
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from comfy.sd import load_checkpoint_guess_config
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from comfy.model_management import unload_model
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from nodes import (
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VAEDecode,
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KSamplerAdvanced,
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EmptyLatentImage,
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SaveImage,
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CLIPTextEncode,
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)
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from modules.path import modelfile_path
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xl_base_filename = os.path.join(modelfile_path, 'sd_xl_base_1.0.safetensors')
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xl_refiner_filename = os.path.join(modelfile_path, 'sd_xl_refiner_1.0.safetensors')
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xl_base, xl_base_clip, xl_base_vae, xl_base_clipvision = load_checkpoint_guess_config(xl_base_filename)
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del xl_base_clipvision
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opCLIPTextEncode = CLIPTextEncode()
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opEmptyLatentImage = EmptyLatentImage()
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opKSamplerAdvanced = KSamplerAdvanced()
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opVAEDecode = VAEDecode()
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positive_conditions = opCLIPTextEncode.encode(clip=xl_base_clip, text='a handsome man in forest')[0]
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negative_conditions = opCLIPTextEncode.encode(clip=xl_base_clip, text='bad, ugly')[0]
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initial_latent_image = opEmptyLatentImage.generate(width=1024, height=1024, batch_size=1)[0]
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samples = opKSamplerAdvanced.sample(
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add_noise="enable",
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noise_seed=random.randint(1, 2 ** 64),
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steps=25,
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cfg=9,
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sampler_name="euler",
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scheduler="normal",
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start_at_step=0,
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end_at_step=25,
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return_with_leftover_noise="enable",
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model=xl_base,
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positive=positive_conditions,
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negative=negative_conditions,
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latent_image=initial_latent_image,
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)[0]
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unload_model()
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vae_decoded = opVAEDecode.decode(samples=samples, vae=xl_base_vae)[0]
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a = 0
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