├── README.md
└── improved_prompt_matrix.py


/README.md:
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 1 | # ⚠️ This script has been deprecated ⚠️
 2 | Please use the integrated [XYZ grid](https://github.com/AUTOMATIC1111/stable-diffusion-webui/blob/master/scripts/xyz_grid.py) or the [sd-dynamic-prompts](https://github.com/adieyal/sd-dynamic-prompts) extension instead.
 3 | 
 4 | ---
 5 | 
 6 | ## auto1111-improved-prompt-matrix
 7 | 
 8 | This script is [advanced-prompt-matrix](https://github.com/GRMrGecko/stable-diffusion-webui-automatic/blob/advanced_matrix/scripts/advanced_prompt_matrix.py) modified to support `batch count`.
 9 | 
10 | ### Usage
11 | 
12 | Use `<` `>` to create a group of alternate texts. Separate text options with `|`. Multiple groups and multiple options can be used. For example:
13 | 
14 | An input of `a <corgi|cat> wearing <goggles|a hat>`  
15 | Will output 4 prompts: `a corgi wearing goggles`, `a corgi wearing a hat`, `a cat wearing goggles`, `a cat wearing a hat`
16 | 
17 | Each output prompt will be generated for each seed when using a `batch count` > 1. `batch size` is ignored.
18 | 


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/improved_prompt_matrix.py:
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 1 | import re
 2 | import gradio as gr
 3 | import modules.shared as shared
 4 | import modules.scripts as scripts
 5 | import modules.sd_samplers
 6 | from modules.processing import process_images, StableDiffusionProcessingTxt2Img
 7 | 
 8 | rex = r'(<(?!lora:)([^>]+)>)'
 9 | 
10 | class Script(scripts.Script):
11 |     def title(self):
12 |         return "Improved prompt matrix"
13 | 
14 |     def ui(self, is_img2img):
15 |         dummy = gr.Checkbox(label="Usage: a <corgi|cat> wearing <goggles|a hat>")
16 |         return [dummy]
17 | 
18 |     def run(self, p, dummy):
19 |         modules.processing.fix_seed(p)
20 | 
21 |         original_prompt = p.prompt[0] if type(p.prompt) == list else p.prompt
22 | 
23 |         matrix_count = 0
24 |         prompt_matrix_parts = []
25 |         for data in re.finditer(rex, original_prompt):
26 |             if data:
27 |                 matrix_count += 1
28 |                 span = data.span(1)
29 |                 items = data.group(2).split("|")
30 |                 prompt_matrix_parts.extend(items)
31 | 
32 |         all_prompts = [original_prompt]
33 |         while True:
34 |             found_matrix = False
35 |             for this_prompt in all_prompts:
36 |                 for data in re.finditer(rex, this_prompt):
37 |                     if data:
38 |                         found_matrix = True
39 |                         # Remove last prompt as it has a found_matrix
40 |                         all_prompts.remove(this_prompt)
41 |                         span = data.span(1)
42 |                         items = data.group(2).split("|")
43 |                         for item in items:
44 |                             new_prompt = this_prompt[:span[0]] + item.strip() + this_prompt[span[1]:]
45 |                             all_prompts.append(new_prompt.strip())
46 |                     break
47 |                 if found_matrix:
48 |                     break
49 |             if not found_matrix:
50 |                 break
51 | 
52 |         total_images = len(all_prompts) * p.n_iter
53 |         print(f"Prompt matrix will create {total_images} images")
54 | 
55 |         total_steps = p.steps * total_images
56 |         if isinstance(p, StableDiffusionProcessingTxt2Img) and p.enable_hr:
57 |             total_steps *= 2
58 |         shared.total_tqdm.updateTotal(total_steps)
59 | 
60 |         p.prompt = all_prompts * p.n_iter
61 |         p.seed = [item for item in range(int(p.seed), int(p.seed) + p.n_iter) for _ in range(len(all_prompts))]
62 |         p.n_iter = total_images
63 |         p.prompt_for_display = original_prompt
64 | 
65 |         return process_images(p)
66 | 


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