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Upload magic_prompt.py

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  1. magic_prompt.py +169 -0
magic_prompt.py ADDED
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+ """
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+ User script for AUTOMATIC111's SD WebUI that integrates MagicPrompt
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+ Copyright (C) 2022 Spaceginner
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+
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+ This user script is free software: you can redistribute it and/or modify
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+ it under the terms of the GNU General Public License as published by
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+ the Free Software Foundation, either version 3 of the License, or
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+ (at your option) any later version.
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+
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+ This user script is distributed in the hope that it will be useful,
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+ but WITHOUT ANY WARRANTY; without even the implied warranty of
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+ MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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+ GNU General Public License for more details.
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+
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+ You should have received a copy of the GNU General Public License
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+ along with this user script. If not, see <https://www.gnu.org/licenses/>.
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+
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+ Contact me via Discord (Spaceginner#7688), email (ivan.demian2009@gmail.com)
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+ or via "Issues" tab on Github page of this script
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+ (https://github.com/Spaceginner/MagicPrompt-awebui)
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+
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+ Credits:
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+ Special thanks to Gustavosta for creating MagicPrompt AI model.
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+ Also credits go to u/Letharguss (for creating basic script)
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+ and SoCalGuitarist#2586 (for figuring out how to change prompt batch to batch)
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+
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+ Version: 1.0.0
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+ """
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+
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+ import os
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+ import sys
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+ import subprocess
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+
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+ # Try to import aitextgen, if it is not found, download
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+ try:
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+ from aitextgen import aitextgen
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+ except:
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+ print("[MagicPrompt script] aitextgen module is not found, downloading...")
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+ if os.path.exists("./venv"):
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+ subprocess.call(["./venv/Scripts/python", "-m", "pip", "-q", "--disable-pip-version-check", "--no-input", "install", "aitextgen"])
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+ else:
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+ subprocess.call(["python", "-m", "pip", "-q", "--disable-pip-version-check", "--no-input", "install", "aitextgen"])
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+ print("[MagicPrompt script] aitextgen module is downloaded")
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+
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+ import gradio as gr
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+ import torch
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+
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+ import modules.scripts as scripts
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+ from modules.processing import Processed, process_images
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+ from modules.shared import state
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+
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+ # Searching for folder with MagicPrompt model, if not found, download model
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+ if (not os.path.isdir("./models/MagicPrompt/")):
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+ print("[MagicPrompt script] MagicPrompt model is not found, downloading MagicPrompt model...")
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+ os.mkdir("./models/MagicPrompt/")
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+ subprocess.call(["git", "clone", "--quiet", "https://huggingface.co/Gustavosta/MagicPrompt-Stable-Diffusion", "./models/MagicPrompt/."])
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+ print("[MagicPrompt script] MagicPrompt model is downloaded")
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+
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+ def getOrdinalNum(n):
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+ if str(n)[-1] == "1":
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+ return f"{n}st"
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+ elif str(n)[-1] == "2":
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+ return f"{n}nd"
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+ elif str(n)[-1] == "3":
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+ return f"{n}rd"
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+ else:
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+ return f"{n}th"
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+
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+ class Script(scripts.Script):
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+ # "Black magic to keep model between runs"
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+ gpt = None
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+
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+ def title(self):
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+ return "MagicPrompt"
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+
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+ def show(self, isImg2img):
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+ # Will show up only in txt2img tab
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+ return not isImg2img
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+
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+ def ui(self, isImg2img):
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+ # Some settings
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+ promptLength = gr.Slider(label="Prompt max. length", value=75, minimum=1, maximum=300, step=1)
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+ temp = gr.Slider(label="Temperature", value=0.7, minimum=0.1, maximum=2, step=0.1)
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+ useSameSeed = gr.Checkbox(label="Use same seed for each batch", value=False)
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+ useUniquePrompt = gr.Checkbox(label="Use unique prompt for each batch", value=True)
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+ isPrioritized = gr.Checkbox(label="Iniatial prompt will have more prority over generated one", value=False)
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+ doPregenerating = gr.Checkbox(label="Enable prompt pregenerating (Theoretical perfomance boost). If you dont know how many images do you want to generate, disable it", value=True)
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+ doUnloadModel = gr.Checkbox(label="Unload MagicPrompt model from VRAM/RAM after this run. (Decreased perfomance between runs, as it need to load again)", value=False)
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+
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+ return [promptLength, temp, useSameSeed, useUniquePrompt, isPrioritized, doPregenerating, doUnloadModel]
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+
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+ def run(self, p, promptLength, temp, useSameSeed, useUniquePrompt, isPrioritized, doPregenerating, doUnloadModel):
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+ print()
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+
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+ # Load MagicPrompt model
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+ if type(self.gpt) != aitextgen:
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+ self.gpt = aitextgen(model_folder="./models/MagicPrompt/", tokenizer_file="./models/MagicPrompt/tokenizer.json", to_gpu=torch.cuda.is_available())
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+
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+ p.do_not_save_grid = True
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+
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+ # If prompt is a list, take first time out of it.
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+ p.prompt = p.prompt[0] if type(p.prompt) == list else p.prompt
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+
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+ # As we will change prompt every batch
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+ # we need to process only 1 batch at a time
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+ state.job_count = p.n_iter
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+ p.n_iter = 1
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+
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+ # Init prompt prioritazing
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+ originalPrompt = p.prompt
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+ if (originalPrompt != "" and isPrioritized):
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+ originalPrompt = "(" + originalPrompt + ")"
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+
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+ # Pregenerating prompts
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+ prompts = []
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+ if (doPregenerating):
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+ print(f"[MagicPrompt script] Pregenerating prompt{'s' if state.job_count > 1 else ''}...")
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+ for i in range(state.job_count):
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+ if (i == 0 or useUniquePrompt):
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+ if state.interrupted:
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+ print(f"[MagicPrompt script] Pregeneration interrupted")
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+ break
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+
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+ prompts.append(self.gpt.generate_one(prompt=originalPrompt, max_length=promptLength, temperature=temp))
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+ if state.job_count > 1:
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+ print(f"[MagicPrompt script] Pregenerated {getOrdinalNum(i+1)} prompt...")
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+ else:
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+ break
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+ print("[MagicPrompt script] Pregenerating finished")
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+
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+ images = []
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+ for i in range(state.job_count):
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+ if state.skipped:
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+ print("Rendering of current batch skipped")
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+ continue
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+
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+ if state.interrupted:
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+ print(f"Rendering interrupted")
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+ break
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+
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+ state.job = f"{i+1} out of {state.job_count}"
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+
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+ # Remove total bar
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+ sys.stdout.write('\033[2K\033[1G')
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+ print("\n")
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+
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+ # Prompt applying
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+ if (i == 0 or useUniquePrompt):
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+ if doPregenerating:
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+ p.prompt = prompts[i]
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+ else:
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+ # ...or generate one if pregenerating is disabled
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+ print(f"[MagicPrompt script] Generating prompt for {getOrdinalNum(i+1)} batch...")
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+ p.prompt = self.gpt.generate_one(prompt=originalPrompt, max_length=promptLength, temperature=temp)
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+
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+ print(f"[MagicPrompt script] Generated prompt for {getOrdinalNum(i+1)} batch: {p.prompt}")
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+
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+ # for whatever reason .append() doesn't work
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+ images += process_images(p).images
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+
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+ if not useSameSeed:
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+ if not p.seed == -1:
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+ p.seed += 1
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+
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+ # Unload model
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+ if doUnloadModel:
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+ del self.gpt
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+
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+ return Processed(p, images, p.seed, "")