31 lines
951 B
Python
31 lines
951 B
Python
import os
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import modules.core as core
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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 = core.load_model(xl_base_filename)
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positive_conditions = core.encode_prompt_condition(clip=xl_base.clip, prompt='a beautiful woman in forest')
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negative_conditions = core.encode_prompt_condition(clip=xl_base.clip, prompt='bad, ugly')
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empty_latent = core.generate_empty_latent(width=1024, height=1024, batch_size=1)
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sampled_latent = core.ksample(
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unet=xl_base.unet,
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positive_condition=positive_conditions,
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negative_condition=negative_conditions,
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latent_image=empty_latent
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)
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decoded_latent = core.decode_vae(vae=xl_base.vae, latent_image=sampled_latent)
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images = core.image_to_numpy(decoded_latent)
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for image in images:
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import cv2
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cv2.imwrite('a.png', image[:, :, ::-1])
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