from contextlib import closing import modules.scripts from modules import processing from modules.generation_parameters_copypaste import create_override_settings_dict from modules.shared import opts import modules.shared as shared from modules.ui import plaintext_to_html import gradio as gr def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_name: str, n_iter: int, batch_size: int, cfg_scale: float, 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_checkpoint_name: str, hr_sampler_name: str, hr_prompt: str, hr_negative_prompt, override_settings_texts, request: gr.Request, *args): override_settings = create_override_settings_dict(override_settings_texts) p = processing.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, sampler_name=sampler_name, batch_size=batch_size, n_iter=n_iter, steps=steps, cfg_scale=cfg_scale, width=width, height=height, 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_checkpoint_name=None if hr_checkpoint_name == 'Use same checkpoint' else hr_checkpoint_name, hr_sampler_name=None if hr_sampler_name == 'Use same sampler' else hr_sampler_name, hr_prompt=hr_prompt, hr_negative_prompt=hr_negative_prompt, override_settings=override_settings, ) p.scripts = modules.scripts.scripts_txt2img p.script_args = args p.user = request.username if shared.opts.enable_console_prompts: print(f"\ntxt2img: {prompt}", file=shared.progress_print_out) with closing(p): processed = modules.scripts.scripts_txt2img.run(p, *args) if processed is None: processed = processing.process_images(p) 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, classname="comments")