import math import os import sys import traceback import modules.scripts as scripts import gradio as gr from modules.processing import Processed, process_images, setup_color_correction from PIL import Image from modules.shared import opts, cmd_opts, state class Script(scripts.Script): def title(self): return "Batch processing" def show(self, is_img2img): return is_img2img def ui(self, is_img2img): input_dir = gr.Textbox(label="Input directory", lines=1) output_dir = gr.Textbox(label="Output directory", lines=1) return [input_dir, output_dir] def run(self, p, input_dir, output_dir): images = [file for file in [os.path.join(input_dir, x) for x in os.listdir(input_dir)] if os.path.isfile(file)] batch_count = math.ceil(len(images) / p.batch_size) print(f"Will process {len(images)} images in {batch_count} batches.") p.batch_count = 1 p.do_not_save_grid = True p.do_not_save_samples = True state.job_count = batch_count for batch_no in range(batch_count): batch_images = [] for path in images[batch_no*p.batch_size:(batch_no+1)*p.batch_size]: try: img = Image.open(path) batch_images.append((img, path)) except: print(f"Error processing {path}:", file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) if len(batch_images) == 0: continue state.job = f"{batch_no} out of {batch_count}: {batch_images[0][1]}" p.init_images = [x[0] for x in batch_images] if opts.img2img_color_correction: p.color_corrections = [setup_color_correction(i) for i in p.init_images] proc = process_images(p) for image, (_, path) in zip(proc.images, batch_images): filename = os.path.basename(path) image.save(os.path.join(output_dir, filename)) return Processed(p, [], p.seed, "")