mirror of https://github.com/vladmandic/automatic
127 lines
6.3 KiB
Python
127 lines
6.3 KiB
Python
import os
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from modules import shared, processing, scripts_manager
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from modules.logger import log
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from modules.generation_parameters_copypaste import create_override_settings_dict
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from modules.ui_common import plaintext_to_html
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from modules.paths import resolve_output_path
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debug = log.trace if os.environ.get('SD_PROCESS_DEBUG', None) is not None else lambda *args, **kwargs: None
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debug('Trace: PROCESS')
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def txt2img(id_task, state,
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prompt, negative_prompt, prompt_styles,
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steps, sampler_index, hr_sampler_index,
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vae_type, tiling, hidiffusion,
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detailer_enabled, detailer_prompt, detailer_negative, detailer_steps, detailer_strength, detailer_resolution,
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n_iter, batch_size,
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guidance_name, guidance_scale, guidance_rescale, guidance_start, guidance_stop,
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cfg_scale, image_cfg_scale, diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end,
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clip_skip,
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seed, subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w,
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height, width,
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enable_hr, denoising_strength,
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hr_scale, hr_resize_mode, hr_resize_context, hr_upscaler, hr_force, hr_second_pass_steps, hr_resize_x, hr_resize_y,
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refiner_steps, refiner_start, refiner_prompt, refiner_negative,
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hdr_mode, hdr_brightness, hdr_color, hdr_sharpen, hdr_clamp, hdr_boundary, hdr_threshold, hdr_maximize, hdr_max_center, hdr_max_boundary, hdr_color_picker, hdr_tint_ratio, hdr_apply_hires,
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grading_brightness, grading_contrast, grading_saturation, grading_hue, grading_gamma, grading_sharpness, grading_color_temp,
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grading_shadows, grading_midtones, grading_highlights, grading_clahe_clip, grading_clahe_grid,
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grading_shadows_tint, grading_highlights_tint, grading_split_tone_balance,
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grading_vignette, grading_grain, grading_lut_file, grading_lut_strength,
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override_settings_texts,
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*args):
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debug(f'txt2img: {id_task}')
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if shared.sd_model is None:
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log.warning('Aborted: op=txt model not loaded')
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return [], '', '', 'Error: model not loaded'
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override_settings = create_override_settings_dict(override_settings_texts)
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if sampler_index is None:
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log.warning('Sampler: invalid')
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sampler_index = 0
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if hr_sampler_index is None:
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hr_sampler_index = sampler_index
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p = processing.StableDiffusionProcessingTxt2Img(
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sd_model=shared.sd_model,
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outpath_samples=resolve_output_path(shared.opts.outdir_samples, shared.opts.outdir_txt2img_samples),
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outpath_grids=resolve_output_path(shared.opts.outdir_grids, shared.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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sampler_name = processing.get_sampler_name(sampler_index),
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hr_sampler_name = processing.get_sampler_name(hr_sampler_index),
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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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guidance_name=guidance_name,
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guidance_scale=guidance_scale,
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guidance_rescale=guidance_rescale,
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guidance_start=guidance_start,
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guidance_stop=guidance_stop,
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cfg_scale=cfg_scale,
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image_cfg_scale=image_cfg_scale,
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diffusers_guidance_rescale=diffusers_guidance_rescale,
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pag_scale=pag_scale,
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pag_adaptive=pag_adaptive,
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cfg_end=cfg_end,
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clip_skip=clip_skip,
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width=width,
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height=height,
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vae_type=vae_type,
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detailer_enabled=detailer_enabled,
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detailer_prompt=detailer_prompt,
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detailer_negative=detailer_negative,
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detailer_steps=detailer_steps,
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detailer_strength=detailer_strength,
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detailer_resolution=detailer_resolution,
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tiling=tiling,
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hidiffusion=hidiffusion,
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enable_hr=enable_hr,
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denoising_strength=denoising_strength,
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hr_scale=hr_scale,
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hr_resize_mode=hr_resize_mode,
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hr_resize_context=hr_resize_context,
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hr_upscaler=hr_upscaler,
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hr_force=hr_force,
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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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refiner_steps=refiner_steps,
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refiner_start=refiner_start,
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refiner_prompt=refiner_prompt,
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refiner_negative=refiner_negative,
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hdr_mode=hdr_mode, hdr_brightness=hdr_brightness, hdr_color=hdr_color, hdr_sharpen=hdr_sharpen, hdr_clamp=hdr_clamp,
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hdr_boundary=hdr_boundary, hdr_threshold=hdr_threshold, hdr_maximize=hdr_maximize, hdr_max_center=hdr_max_center, hdr_max_boundary=hdr_max_boundary, hdr_color_picker=hdr_color_picker, hdr_tint_ratio=hdr_tint_ratio, hdr_apply_hires=hdr_apply_hires,
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grading_brightness=grading_brightness, grading_contrast=grading_contrast, grading_saturation=grading_saturation, grading_hue=grading_hue,
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grading_gamma=grading_gamma, grading_sharpness=grading_sharpness, grading_color_temp=grading_color_temp,
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grading_shadows=grading_shadows, grading_midtones=grading_midtones, grading_highlights=grading_highlights,
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grading_clahe_clip=grading_clahe_clip, grading_clahe_grid=grading_clahe_grid,
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grading_shadows_tint=grading_shadows_tint, grading_highlights_tint=grading_highlights_tint, grading_split_tone_balance=grading_split_tone_balance,
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grading_vignette=grading_vignette, grading_grain=grading_grain,
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grading_lut_file=grading_lut_file.name if grading_lut_file is not None else '', grading_lut_strength=grading_lut_strength,
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override_settings=override_settings,
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)
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p.scripts = scripts_manager.scripts_txt2img
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p.script_args = args
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p.state = state
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processed: processing.Processed = scripts_manager.scripts_txt2img.run(p, *args)
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if processed is None:
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processed = processing.process_images(p)
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processed = scripts_manager.scripts_txt2img.after(p, processed, *args)
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p.close()
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if processed is None:
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return [], '', '', 'Error: processing failed'
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generation_info_js = processed.js() if processed is not None else ''
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if processed is None:
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return [], generation_info_js, '', 'Error: no images'
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return processed.images, generation_info_js, processed.info, plaintext_to_html(processed.comments)
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