import modules.scripts 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(prompt: str, negative_prompt: str, prompt_style: int, 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, height: int, width: 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, prompt_style=prompt_style, 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, sampler_index=sampler_index, batch_size=batch_size, n_iter=n_iter, steps=steps, cfg_scale=cfg_scale, width=width, height=height, restore_faces=restore_faces, tiling=tiling, ) print(f"\ntxt2img: {prompt}", file=shared.progress_print_out) processed = modules.scripts.scripts_txt2img.run(p, *args) if processed is not None: pass else: processed = process_images(p) shared.total_tqdm.clear() return processed.images, processed.js(), plaintext_to_html(processed.info)