import os import tempfile from typing import List from PIL import Image from modules import shared, images, devices, scripts_manager, scripts_postprocessing, infotext from modules.shared import opts from modules.paths import resolve_output_path def run_postprocessing(extras_mode, image, image_folder: List[tempfile.NamedTemporaryFile], input_dir, output_dir, show_extras_results, *args, save_output: bool = True): devices.torch_gc() shared.state.begin('Extras') image_data = [] image_names = [] image_fullnames = [] image_ext = [] outputs = [] params = {} info = '' if extras_mode == 1: for img in image_folder: if isinstance(img, Image.Image): image = img fn = '' ext = None else: try: image = Image.open(os.path.abspath(img.name)) except Exception as e: shared.log.error(f'Failed to open image: file="{img.name}" {e}') continue fn, ext = os.path.splitext(img.orig_name) image_fullnames.append(img.name) image_data.append(image) image_names.append(fn) image_ext.append(ext) shared.log.debug(f'Process: mode=batch inputs={len(image_folder)} images={len(image_data)}') elif extras_mode == 2: assert input_dir, 'input directory not selected' image_list = os.listdir(input_dir) for filename in image_list: fn = os.path.join(input_dir, filename) try: image = Image.open(fn) except Exception as e: shared.log.error(f'Failed to open image: file="{fn}" {e}') continue image_fullnames.append(fn) image_data.append(image) image_names.append(fn) image_ext.append(None) shared.log.debug(f'Process: mode=folder inputs={input_dir} files={len(image_list)} images={len(image_data)}') else: image_data.append(image) image_names.append(None) image_ext.append(None) if extras_mode == 2 and output_dir != '': outpath = output_dir else: outpath = resolve_output_path(opts.outdir_samples, opts.outdir_extras_samples) processed_images = [] for image, name, ext in zip(image_data, image_names, image_ext): # pylint: disable=redefined-argument-from-local shared.log.debug(f'Process: image={image} {args}') info = '' if shared.state.interrupted: shared.log.debug('Postprocess interrupted') break if image is None: continue shared.state.textinfo = name pp = scripts_postprocessing.PostprocessedImage(image.convert("RGB")) scripts_manager.scripts_postproc.run(pp, args) geninfo, items = images.read_info_from_image(image) params = infotext.parse(geninfo) for k, v in items.items(): pp.image.info[k] = v if 'parameters' in items: info = items['parameters'] + ', ' if (params.get('size-1', 0) != pp.image.width) or (params.get('size-2', 0) != pp.image.height): params['size-1'] = pp.image.width params['size-2'] = pp.image.height info += f"Size: {pp.image.width}x{pp.image.height}, " info = info + ", ".join([k if k == v else f'{k}: {infotext.quote(v)}' for k, v in pp.info.items() if v is not None]) pp.image.info["postprocessing"] = info processed_images.append(pp.image) if save_output: if opts.use_original_name_batch and name is not None: forced_filename = os.path.splitext(os.path.basename(name))[0] images.save_image(pp.image, path=outpath, extension=ext or opts.samples_format, info=info, grid=False, pnginfo_section_name="extras", existing_info=pp.image.info, forced_filename=forced_filename) else: images.save_image(pp.image, path=outpath, extension=ext or opts.samples_format, info=info, grid=False, pnginfo_section_name="extras", existing_info=pp.image.info) if extras_mode != 2 or show_extras_results: outputs.append(pp.image) image.close() scripts_manager.scripts_postproc.postprocess(processed_images, args) devices.torch_gc() return outputs, info, params def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_dir, show_extras_results, gfpgan_visibility, codeformer_visibility, codeformer_weight, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility, save_output: bool = True): """old handler for API""" args = scripts_manager.scripts_postproc.create_args_for_run({ "Upscale": { "upscale_mode": resize_mode, "upscale_by": upscaling_resize, "upscale_to_width": upscaling_resize_w, "upscale_to_height": upscaling_resize_h, "upscale_crop": upscaling_crop, "upscaler_1_name": extras_upscaler_1, "upscaler_2_name": extras_upscaler_2, "upscaler_2_visibility": extras_upscaler_2_visibility, }, "GFPGAN": { "gfpgan_visibility": gfpgan_visibility, }, "CodeFormer": { "codeformer_visibility": codeformer_visibility, "codeformer_weight": codeformer_weight, }, }) return run_postprocessing(extras_mode, image, image_folder, input_dir, output_dir, show_extras_results, *args, save_output=save_output)