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										 |  |  | import math | 
					
						
							|  |  |  | from collections import namedtuple | 
					
						
							|  |  |  | from copy import copy | 
					
						
							|  |  |  | import random | 
					
						
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							|  |  |  | import modules.scripts as scripts | 
					
						
							|  |  |  | import gradio as gr | 
					
						
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							|  |  |  | from modules import images | 
					
						
							|  |  |  | from modules.processing import process_images, Processed | 
					
						
							|  |  |  | from modules.shared import opts, cmd_opts, state | 
					
						
							|  |  |  | import modules.sd_samplers | 
					
						
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							|  |  |  | def draw_xy_grid(xs, ys, x_label, y_label, cell): | 
					
						
							|  |  |  |     res = [] | 
					
						
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							|  |  |  |     ver_texts = [[images.GridAnnotation(y_label(y))] for y in ys] | 
					
						
							|  |  |  |     hor_texts = [[images.GridAnnotation(x_label(x))] for x in xs] | 
					
						
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										 |  |  |     first_processed = None | 
					
						
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										 |  |  |     state.job_count = len(xs) * len(ys) | 
					
						
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										 |  |  |     for iy, y in enumerate(ys): | 
					
						
							|  |  |  |         for ix, x in enumerate(xs): | 
					
						
							|  |  |  |             state.job = f"{ix + iy * len(xs) + 1} out of {len(xs) * len(ys)}" | 
					
						
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							|  |  |  |             processed = cell(x, y) | 
					
						
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										 |  |  |             if first_processed is None: | 
					
						
							|  |  |  |                 first_processed = processed | 
					
						
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							|  |  |  |             res.append(processed.images[0]) | 
					
						
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							|  |  |  |     grid = images.image_grid(res, rows=len(ys)) | 
					
						
							|  |  |  |     grid = images.draw_grid_annotations(grid, res[0].width, res[0].height, hor_texts, ver_texts) | 
					
						
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										 |  |  |     first_processed.images = [grid] | 
					
						
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										 |  |  |     return first_processed | 
					
						
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							|  |  |  | class Script(scripts.Script): | 
					
						
							|  |  |  |     def title(self): | 
					
						
							|  |  |  |         return "Prompt matrix" | 
					
						
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										 |  |  |     def ui(self, is_img2img):         | 
					
						
							|  |  |  |         put_at_start = gr.Checkbox(label='Put variable parts at start of prompt', value=False, elem_id=self.elem_id("put_at_start")) | 
					
						
							|  |  |  |         different_seeds = gr.Checkbox(label='Use different seed for each picture', value=False, elem_id=self.elem_id("different_seeds")) | 
					
						
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										 |  |  |         return [put_at_start, different_seeds] | 
					
						
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										 |  |  |     def run(self, p, put_at_start, different_seeds): | 
					
						
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										 |  |  |         modules.processing.fix_seed(p) | 
					
						
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							|  |  |  |         original_prompt = p.prompt[0] if type(p.prompt) == list else p.prompt | 
					
						
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							|  |  |  |         all_prompts = [] | 
					
						
							|  |  |  |         prompt_matrix_parts = original_prompt.split("|") | 
					
						
							|  |  |  |         combination_count = 2 ** (len(prompt_matrix_parts) - 1) | 
					
						
							|  |  |  |         for combination_num in range(combination_count): | 
					
						
							|  |  |  |             selected_prompts = [text.strip().strip(',') for n, text in enumerate(prompt_matrix_parts[1:]) if combination_num & (1 << n)] | 
					
						
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							|  |  |  |             if put_at_start: | 
					
						
							|  |  |  |                 selected_prompts = selected_prompts + [prompt_matrix_parts[0]] | 
					
						
							|  |  |  |             else: | 
					
						
							|  |  |  |                 selected_prompts = [prompt_matrix_parts[0]] + selected_prompts | 
					
						
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							|  |  |  |             all_prompts.append(", ".join(selected_prompts)) | 
					
						
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							|  |  |  |         p.n_iter = math.ceil(len(all_prompts) / p.batch_size) | 
					
						
							|  |  |  |         p.do_not_save_grid = True | 
					
						
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							|  |  |  |         print(f"Prompt matrix will create {len(all_prompts)} images using a total of {p.n_iter} batches.") | 
					
						
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							|  |  |  |         p.prompt = all_prompts | 
					
						
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										 |  |  |         p.seed = [p.seed + (i if different_seeds else 0) for i in range(len(all_prompts))] | 
					
						
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										 |  |  |         p.prompt_for_display = original_prompt | 
					
						
							|  |  |  |         processed = process_images(p) | 
					
						
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							|  |  |  |         grid = images.image_grid(processed.images, p.batch_size, rows=1 << ((len(prompt_matrix_parts) - 1) // 2)) | 
					
						
							|  |  |  |         grid = images.draw_prompt_matrix(grid, p.width, p.height, prompt_matrix_parts) | 
					
						
							|  |  |  |         processed.images.insert(0, grid) | 
					
						
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										 |  |  |         processed.index_of_first_image = 1 | 
					
						
							|  |  |  |         processed.infotexts.insert(0, processed.infotexts[0]) | 
					
						
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										 |  |  |         if opts.grid_save: | 
					
						
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										 |  |  |             images.save_image(processed.images[0], p.outpath_grids, "prompt_matrix", extension=opts.grid_format, prompt=original_prompt, seed=processed.seed, grid=True, p=p) | 
					
						
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										 |  |  |         return processed |