30 lines
1.2 KiB
Python
30 lines
1.2 KiB
Python
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#!/usr/bin/env python3
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# Copyright (c) 2024 Julian Müller (ChaoticByte)
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from argparse import ArgumentParser
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from diffusers import AutoPipelineForText2Image
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if __name__ == "__main__":
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# parse cmdline args
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argp = ArgumentParser()
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argp.add_argument("-m", "--model", type=str, help="Path to the sdxl model folder", required=True)
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argp.add_argument("-p", "--prompt", type=str, help="Prompt for image inference")
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argp.add_argument("-n", "--steps", type=int, help="Number of inference steps", default=1)
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argp.add_argument("-o", "--output", type=str, help="Image output file", default="output.png")
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args = argp.parse_args()
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# create pipeline, process prompt(s), output file
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pipe = AutoPipelineForText2Image.from_pretrained(args.model, local_files_only=True)
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pipe.to("cpu")
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if args.prompt is None:
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try:
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while True:
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prompt = input("> ")
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pipe(prompt=prompt, num_inference_steps=args.steps, guidance_scale=0.0).images[0].save(args.output)
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except (EOFError, KeyboardInterrupt):
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print("bye.")
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exit(0)
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else:
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pipe(prompt=args.prompt, num_inference_steps=args.steps, guidance_scale=0.0).images[0].show(args.output)
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