import modules.scripts from modules import sd_samplers from modules.processing import StableDiffusionProcessing, Processed, StableDiffusionProcessingTxt2Img, \ StableDiffusionProcessingImg2Img, process_images from modules.shared import opts, cmd_opts import modules.shared as shared import modules.processing as processing from modules.ui import plaintext_to_html 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, hr_sampler_index: int, *args): p = StableDiffusionProcessingTxt2Img( sd_model=shared.sd_model, outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples, outpath_grids=opts.outdir_grids or opts.outdir_txt2img_grids, prompt=prompt, styles=prompt_styles, negative_prompt=negative_prompt, seed=seed, subseed=subseed, subseed_strength=subseed_strength, seed_resize_from_h=seed_resize_from_h, seed_resize_from_w=seed_resize_from_w, seed_enable_extras=seed_enable_extras, sampler_name=sd_samplers.samplers[sampler_index].name, batch_size=batch_size, n_iter=n_iter, steps=steps, cfg_scale=cfg_scale, width=width, height=height, restore_faces=restore_faces, tiling=tiling, enable_hr=enable_hr, denoising_strength=denoising_strength if enable_hr else None, hr_scale=hr_scale, hr_upscaler=hr_upscaler, hr_second_pass_steps=hr_second_pass_steps, hr_resize_x=hr_resize_x, hr_resize_y=hr_resize_y, hr_sampler=sd_samplers.samplers[hr_sampler_index - 1].name if hr_sampler_index != 0 else 0 ) p.scripts = modules.scripts.scripts_txt2img p.script_args = args if cmd_opts.enable_console_prompts: print(f"\ntxt2img: {prompt}", file=shared.progress_print_out) processed = modules.scripts.scripts_txt2img.run(p, *args) if processed is None: processed = process_images(p) p.close() shared.total_tqdm.clear() generation_info_js = processed.js() if opts.samples_log_stdout: print(generation_info_js) if opts.do_not_show_images: processed.images = [] return processed.images, generation_info_js, plaintext_to_html(processed.info), plaintext_to_html(processed.comments)