mirror of
https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
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66 lines
2.6 KiB
Python
66 lines
2.6 KiB
Python
import modules.scripts
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from modules import sd_samplers
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from modules.processing import StableDiffusionProcessing, Processed, StableDiffusionProcessingTxt2Img, \
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StableDiffusionProcessingImg2Img, process_images
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from modules.shared import opts, cmd_opts
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import modules.shared as shared
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import modules.processing as processing
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from modules.ui import plaintext_to_html
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def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, *args):
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p = StableDiffusionProcessingTxt2Img(
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sd_model=shared.sd_model,
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outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples,
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outpath_grids=opts.outdir_grids or opts.outdir_txt2img_grids,
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prompt=prompt,
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styles=prompt_styles,
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negative_prompt=negative_prompt,
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seed=seed,
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subseed=subseed,
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subseed_strength=subseed_strength,
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seed_resize_from_h=seed_resize_from_h,
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seed_resize_from_w=seed_resize_from_w,
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seed_enable_extras=seed_enable_extras,
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sampler_name=sd_samplers.samplers[sampler_index].name,
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batch_size=batch_size,
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n_iter=n_iter,
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steps=steps,
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cfg_scale=cfg_scale,
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width=width,
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height=height,
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restore_faces=restore_faces,
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tiling=tiling,
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enable_hr=enable_hr,
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denoising_strength=denoising_strength if enable_hr else None,
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hr_scale=hr_scale,
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hr_upscaler=hr_upscaler,
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hr_second_pass_steps=hr_second_pass_steps,
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hr_resize_x=hr_resize_x,
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hr_resize_y=hr_resize_y,
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)
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p.scripts = modules.scripts.scripts_txt2img
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p.script_args = args
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if cmd_opts.enable_console_prompts:
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print(f"\ntxt2img: {prompt}", file=shared.progress_print_out)
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processed = modules.scripts.scripts_txt2img.run(p, *args)
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if processed is None:
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processed = process_images(p)
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p.close()
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shared.total_tqdm.clear()
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generation_info_js = processed.js()
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if opts.samples_log_stdout:
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print(generation_info_js)
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if opts.do_not_show_images:
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processed.images = []
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return processed.images, generation_info_js, plaintext_to_html(processed.info), plaintext_to_html(processed.comments)
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