From 72b25e37dbf8c323f49338e1e82dd07e43c2b2a3 Mon Sep 17 00:00:00 2001
From: suzukimain <131413573+suzukimain@users.noreply.github.com>
Date: Tue, 5 Mar 2024 08:04:44 +0900
Subject: [PATCH] Delete History directory
---
History/Image_generation_ver_Bete.ipynb | 1653 -----------------
.../Image_generation_ver_Bete.ipynb | 1126 -----------
2 files changed, 2779 deletions(-)
delete mode 100644 History/Image_generation_ver_Bete.ipynb
delete mode 100644 History/Other than the latest in beta version/Image_generation_ver_Bete.ipynb
diff --git a/History/Image_generation_ver_Bete.ipynb b/History/Image_generation_ver_Bete.ipynb
deleted file mode 100644
index fd2e91c..0000000
--- a/History/Image_generation_ver_Bete.ipynb
+++ /dev/null
@@ -1,1653 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "view-in-github",
- "colab_type": "text"
- },
- "source": [
- "![\"Open](\"https://colab.research.google.com/assets/colab-badge.svg\")
"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "b-akwUYrMpEY"
- },
- "source": [
- ">説明\n",
- "\n",
- "下の方に画像の生成方法とパスのコピーの方法を画像で説明しています。わからない方はご覧ください。\n",
- "\n",
- "(The method for copying the path of an image is explained with images below. If you are unsure, please take a look.)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "C4UJqC_WpaGw",
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "outputId": "44adb23f-a288-464b-b535-1f41cca763e2"
- },
- "outputs": [
- {
- "output_type": "stream",
- "name": "stdout",
- "text": [
- "Mounted at /content/drive\n",
- "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n",
- "GoogleDrive: \u001b[32m接続成功\u001b[0m\n",
- "\u001b[32mセットアップが完了しました。Step.2の実行に移ってください\u001b[0m\n"
- ]
- }
- ],
- "source": [
- "#@title #Step1.セットアップ (Setup){run: \"auto\", display-mode: \"form\"}\n",
- "\n",
- "import locale #この2行は非常に重要\n",
- "locale.getpreferredencoding = lambda: \"UTF-8\"\n",
- "\n",
- "Google_driveに接続 = True # @param {type:\"boolean\"}\n",
- "#@markdown Googleドライブに保存したいときにチェックをしてください\n",
- "from google.colab import drive\n",
- "import google.colab.drive as drive\n",
- "if Google_driveに接続:\n",
- " Gdrive=\"GoogleDrive: \\033[32m接続成功\\033[0m\"\n",
- " try:\n",
- " drive.mount('/content/drive')\n",
- " except:\n",
- " Gdrive=\"GoogleDrive: \\033[31m接続失敗\\033[0m\"\n",
- "else:\n",
- " Gdrive=\"GoogleDrive: \\033[33m接続なし\\033[0m\"\n",
- " if drive._os.path.ismount('/content/drive'):\n",
- " drive.flush_and_unmount()\n",
- " print(\"GoogleDriveの接続を解除しました\")\n",
- "\n",
- "import os\n",
- "\n",
- "\n",
- "try:\n",
- " import torch\n",
- " import diffusers\n",
- " import transformers\n",
- " import accelerate\n",
- " import scipy\n",
- " import safetensors\n",
- " import ftfy\n",
- " import regex\n",
- " import tqdm\n",
- " import xformers\n",
- " import sentencepiece\n",
- " import pysbd\n",
- " import huggingface_hub\n",
- " import sacremoses\n",
- "\n",
- "except:\n",
- " try:\n",
- " !pip install git+https://github.com/huggingface/transformers.git -q\n",
- " !pip install torch==2.0.1+cu118 diffusers==0.16.1 accelerate scipy==1.10.1 safetensors ftfy==6.1.1 regex==2022.10.31 tqdm==4.65.0 scipy==1.10.1 sentencepiece==0.1.99 pysbd==0.3.4 xformers huggingface_hub sacremoses -q\n",
- " import torch\n",
- " import diffusers\n",
- " import transformers\n",
- " import accelerate\n",
- " import scipy\n",
- " import safetensors\n",
- " import ftfy\n",
- " import regex\n",
- " import tqdm\n",
- " import xformers\n",
- " import sentencepiece\n",
- " import pysbd\n",
- " import huggingface_hub\n",
- " import sacremoses\n",
- "\n",
- " except:\n",
- " raise RuntimeError(\"ランタイムをGPUに変更お願いします。またはページの再読み込みをお願いします\")\n",
- "try:\n",
- " import clip\n",
- "except ModuleNotFoundError:\n",
- " !pip install git+https://github.com/openai/CLIP.git -q\n",
- " import clip\n",
- "diffusers_path = \"/content/diffusers\"\n",
- "if not os.path.exists(diffusers_path):\n",
- " !git clone https://github.com/huggingface/diffusers.git -q\n",
- "\n",
- "import requests\n",
- "import spacy\n",
- "import codecs\n",
- "import pickle\n",
- "import torch\n",
- "import random\n",
- "import numpy as np\n",
- "import transformers\n",
- "import sentencepiece\n",
- "import ipywidgets as widgets\n",
- "from PIL import Image\n",
- "import time, math\n",
- "from datetime import datetime\n",
- "from transformers import pipeline\n",
- "from transformers import GPT2Tokenizer, GPT2LMHeadModel, pipeline\n",
- "from torch import Generator, autocast\n",
- "from IPython.display import display, Markdown\n",
- "from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler\n",
- "from diffusers import EulerDiscreteScheduler, StableDiffusionImg2ImgPipeline\n",
- "from diffusers import DiffusionPipeline, AutoencoderKL, EulerAncestralDiscreteScheduler\n",
- "from diffusers import StableDiffusionImg2ImgPipeline\n",
- "from diffusers.models import AutoencoderKL\n",
- "from PIL import Image, PngImagePlugin\n",
- "from IPython.display import display\n",
- "from diffusers import DiffusionPipeline, EulerDiscreteScheduler, DPMSolverMultistepScheduler\n",
- "from google.colab import drive\n",
- "import google.colab.drive as drive\n",
- "\n",
- "\n",
- "if Google_driveに接続:\n",
- " try:\n",
- " drive.mount('/content/drive')\n",
- " except:\n",
- " print(\"\\033[31mGoogleDriveへの接続に失敗しました\\033[0m\")\n",
- "else:\n",
- " if drive._os.path.ismount('/content/drive'):\n",
- " drive.flush_and_unmount()\n",
- " print(\"GoogleDriveの接続を解除しました\")\n",
- "\n",
- "if drive._os.path.ismount('/content/drive'):\n",
- " Connect_Gdrive=\"GoogleDrive: \\033[32m接続成功\\033[0m\"\n",
- "\n",
- "else:\n",
- " Connect_Gdrive=\"GoogleDrive: \\033[33m接続なし\\033[0m\"\n",
- "\n",
- "step1_finish=True\n",
- "\n",
- "print(Connect_Gdrive)\n",
- "print(\"\\033[32mセットアップが完了しました。Step.2の実行に移ってください\\033[0m\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "2_TXXMSVDc5h"
- },
- "outputs": [],
- "source": [
- "#@title #Step2.パイプラインの作成 (Pipeline Creation){ run: \"auto\", display-mode: \"form\"}\n",
- "#form\n",
- "\n",
- "# @markdown #パイプライン設定\n",
- "# @markdown >モデルの選択 (Model Selection)\n",
- "\n",
- "model_select = \"stable diffusion-v2.1(basic)\" # @param [\"stable diffusion-v2.1(basic)\", \"Counterfeit-V2.5(Anime)(better)\", \"waifu diffusion-v1.4(Anime)\", \"Anything-v3.0(Anime)\", \"Anything-v4.5(Anime)\", \"anything-midjourney-v-4-1(Anime)\", \"ACertainThing(Anime)\", \"anime-kawai-diffusion(Anime)\", \"AB4.5_AC0.2(Anime)\", \"basil_mix(Anime)\", \"Counterfeit(Anime)\", \"Counterfeit-V2.0(Anime)\", \"Double-Exposure-Diffusion(Anime)\", \"EimisAnimeDiffusion_1.0v(Anime)\", \"7th_Layer(Anime)\", \"Riga_Collection(Anime)\", \"openjourney-v4(Reality)\", \"Realistic_Vision_V2.0(Reality)\",\"JWST-Deep-Space-diffusion(space)\",\"Custom\"]\n",
- "\n",
- "#削除モデル(使えないもの)\"epic-space-machine(space_ship)\",\"spacemidj(space)\",\"nasa_space_v2(space)\",\"loliDiffusion(Anime)\",\"chilled_remix(Anime)\"\n",
- "\n",
- "#@markdown Customを選択した場合、下の方に出てくるボックスに入力をお願いします\n",
- "\n",
- "# @markdown >モードの切り替え (mode change)\n",
- "mode_select = \"Quick\" #@param [\"Nomal(better)\",\"Quick\"]\n",
- "\n",
- "#@markdown * \"Nomal\" 品質と生成時間のバランス重視です\n",
- "\n",
- "#@markdown * \"Quick\" 少し品質が低下する代わりに生成時間が大幅に短縮します\n",
- "\n",
- "\n",
- "入力形式 = \"image_and_text\" #@param [\"text_only(better)\", \"image_and_text\"]\n",
- "\n",
- "# @markdown\n",
- "\n",
- "#text_generate_model= \"anime-anything-promptgen-v2\" #@param [\"MagicPrompt-Stable-Diffusion\",\"anime-anything-promptgen-v2\"]\n",
- "\n",
- "\n",
- "# @markdown #追加設定\n",
- "\n",
- "# @markdown >フィルターを調整\n",
- "\n",
- "# @markdown **注意事項 : 変更する時は注意して下さい**\n",
- "\n",
- "Filter_off = False # @param {type:\"boolean\"}\n",
- "\n",
- "\n",
- "# @markdown >同じモデルを使用(Custom設定時のみ)\n",
- "\n",
- "\n",
- "input_skip = True # @param {type:\"boolean\"}\n",
- "\n",
- "# @markdown input_skipは、Custom選択時、同じモデルを何度も使うときに入力の手間を省く機能ですが、違うモデルに変更する場合は上のチェックを外して新しいモデルの情報を入力してください。\n",
- "\n",
- "if \"step1_finish\" not in locals() and \"step1_finish\" not in globals():\n",
- " raise NameError(\"\\033[33m先にStep.1の実行をお願いします\\033[0m\")\n",
- "else:\n",
- " pass\n",
- "\n",
- "\n",
- "\n",
- "def print_text():\n",
- " if mode_select == \"Nomal(better)\":\n",
- " mode_text=\"mode: Nomal\\n\"\n",
- " else:\n",
- " mode_text=\"mode: Quick\\n\"\n",
- " return mode_text\n",
- "\n",
- "def print_format():\n",
- " if 入力形式 == \"text_only(better)\":\n",
- " word_format=\"入力形式: text_only\\n\"\n",
- " else:\n",
- " word_format=\"入力形式: image_and_text\\n\"\n",
- " return word_format\n",
- "\n",
- "mode_text=print_text()\n",
- "word_format=print_format()\n",
- "\n",
- "\n",
- "def result():\n",
- " if Filter_off == False:\n",
- " filter_level = \"フィルターの強度:通常\"\n",
- " else:\n",
- " filter_level = \"\\033[33mフィルターの強度:無効\\033[0m\"\n",
- " return filter_level\n",
- "\n",
- "def safe():\n",
- " if Filter_off ==False:\n",
- " safety_checker = \"\"\n",
- "\n",
- " else:\n",
- " safety_checker = None\n",
- " return safety_checker\n",
- "\n",
- "\n",
- "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
- "#model, preprocess = clip.load(\"laion/CLIP-ViT-H-14-laion2B-s32B-b79K\", device=device)\n",
- "\n",
- "\n",
- "if \"hugface_path\" not in locals() or not hugface_path:\n",
- " input_fin = False\n",
- "else:\n",
- " input_fin = True\n",
- "\n",
- "\n",
- "# 使用するモデルを設定\n",
- "if model_select ==\"Custom\":\n",
- " if input_skip and input_fin==True:\n",
- " pass\n",
- " elif not input_skip or input_fin==False:\n",
- " print(\n",
- " \"\\033[34m入力例 ： ＜user_name＞/＜repository_name＞\\n\"\n",
- " \" * stabilityai / stable-diffusion-2-1\\n\"\n",
- " \" * hakurei / waifu-diffusion\\n\"\n",
- " )\n",
- " hugface_path = input(\"hugface_path: \")\n",
- " else:\n",
- " print(\"申し訳ありません。バグが発生しました。\\n\"\n",
- " \"input_fin: {input_fin}\\n\"\n",
- " \"input_skip: {input_skip}\"\n",
- "\n",
- " )\n",
- " try:\n",
- " user_name, repository_name = hugface_path.split(\"/\")\n",
- " except:\n",
- " TypeError(\"パスを読み込めませんでした\")\n",
- " model_name = repository_name\n",
- " model_id = hugface_path\n",
- " can_EN = True\n",
- "\n",
- "elif model_select == \"stable diffusion-v2.1(basic)\":\n",
- " model_id = \"stabilityai/stable-diffusion-2-1\"\n",
- " model_name = \"stable_diffusion-v2.1\"\n",
- " can_EN=False\n",
- "\n",
- "elif model_select == \"waifu diffusion-v1.4(Anime)\":\n",
- " model_id = \"hakurei/waifu-diffusion\"\n",
- " model_name = \"waifu_diffusion-v1.4\"\n",
- " can_EN=False\n",
- "\n",
- "elif model_select == \"Anything-v3.0(Anime)\":\n",
- " model_id = \"Linaqruf/anything-v3.0\"\n",
- " model_name = \"Anything-v3.0\"\n",
- " can_EN=True\n",
- "\n",
- "elif model_select == \"anything-midjourney-v-4-1(Anime)\":\n",
- " model_id = \"Joeythemonster/anything-midjourney-v-4-1\"\n",
- " model_name =\"anything-midjourney-v-4-1\"\n",
- " can_EN=True\n",
- "\n",
- "elif model_select == \"Anything-v4.5(Anime)\":\n",
- " model_id = \"shibal1/anything-v4.5-clone\"\n",
- " model_name = \"Anything-v4.5\"\n",
- " can_EN=False\n",
- " #Airic/Anything-V4.5\n",
- "\n",
- "\n",
- "#elif model_select == \"loliDiffusion(Anime)\":\n",
- "# model_id = \"JosefJilek/loliDiffusion\"\n",
- "# model_name = \"loliDiffusion\"\n",
- "\n",
- "elif model_select == \"AB4.5_AC0.2(Anime)\":\n",
- " model_id = \"aioe/AB4.5_AC0.2\"\n",
- " model_name = \"AB4.5_AC0.2\"\n",
- " can_EN=False\n",
- "\n",
- "elif model_select == \"basil_mix(Anime)\":\n",
- " model_id = \"nuigurumi/basil_mix\"\n",
- " model_name = \"basil_mix\"\n",
- " can_EN=True\n",
- "\n",
- "\n",
- "elif model_select == \"Double-Exposure-Diffusion(Anime)\":\n",
- " model_id = \"joachimsallstrom/Double-Exposure-Diffusion\"\n",
- " model_name = \"Double-Exposure-Diffusion\"\n",
- " can_EN=True\n",
- "\n",
- "elif model_select == \"openjourney-v4(Reality)\":\n",
- " model_id = \"prompthero/openjourney-v4\"\n",
- " model_name= \"openjourney-v4\"\n",
- " can_EN=True\n",
- "\n",
- "\n",
- "elif model_select == \"ACertainThing(Anime)\":\n",
- " model_id =\"JosephusCheung/ACertainThing\"\n",
- " model_name=\"ACertainThing\"\n",
- " can_EN=True\n",
- "\n",
- "elif model_select == \"Counterfeit-V2.0(Anime)\":\n",
- " model_id = \"gsdf/Counterfeit-V2.0\"\n",
- " model_name= \"Counterfeit-V2.0\"\n",
- " can_EN=True\n",
- "\n",
- "\n",
- "elif model_select == \"Counterfeit-V2.5(Anime)(better)\":\n",
- " model_id = \"gsdf/Counterfeit-V2.5\"\n",
- " model_name =\"Counterfeit-V2.5\"\n",
- " can_EN=True\n",
- "\n",
- "elif model_select == \"7th_Layer(Anime)\":\n",
- " model_id = \"syaimu/7th_test\"\n",
- " model_name = \"7th_Layer\"\n",
- " can_EN=True\n",
- "\n",
- "\n",
- "elif model_select == \"EimisAnimeDiffusion_1.0v(Anime)\":\n",
- " model_id = \"eimiss/EimisAnimeDiffusion_1.0v\"\n",
- " model_name = \"EimisAnimeDiffusion_1.0v\"\n",
- " can_EN=True\n",
- "\n",
- "\n",
- "elif model_select==\"Riga_Collection(Anime)\":\n",
- " mdoel_id =\"natsusakiyomi/Riga_Collection\"\n",
- " model_name=\"Riga_Collection\"\n",
- " can_EN=True\n",
- "\n",
- "\n",
- "# モードの切り替え (mode change)\n",
- "elif model_select ==\"anime-kawai-diffusion(Anime)\":\n",
- " model_id=\"Ojimi/anime-kawai-diffusion\"\n",
- " model_name=\"anime-kawai-diffusion\"\n",
- " can_EN=True\n",
- "\n",
- "elif model_select == \"anything-midjourney-v-4-1(Anime)\":\n",
- " model_id = \"Joeythemonster/anything-midjourney-v-4-1\"\n",
- " model_name =\"anything-midjourney-v-4-1\"\n",
- " can_EN=True\n",
- "\n",
- "\n",
- "elif model_select==\"Realistic_Vision_V2.0(Reality)\":\n",
- " model_id=\"SG161222/Realistic_Vision_V2.0\"\n",
- " model_name=\"Realistic_Vision_V2.0\"\n",
- " can_EN=True\n",
- "\n",
- "\n",
- "elif model_select==\"JWST-Deep-Space-diffusion(space)\":\n",
- " model_id=\"dallinmackay/JWST-Deep-Space-diffusion\"\n",
- " model_name=\"JWST-Deep-Space-diffusion\"\n",
- " can_EN=True\n",
- "\n",
- "#入れられないけど Deyo/SEmix\n",
- "\n",
- "\n",
- "def pipe_setup():\n",
- " if 入力形式 == \"text_only(better)\":\n",
- " if Filter_off==True:\n",
- " try:\n",
- " pipe = StableDiffusionPipeline.from_pretrained(\n",
- " model_id, torch_dtype=torch.float16 if mode_select == \"Quick\" else torch.float32,\n",
- " safety_checker= None,\n",
- " use_safetensors=True,\n",
- " )\n",
- " pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)\n",
- " except:\n",
- " pipe = StableDiffusionPipeline.from_pretrained(\n",
- " model_id, torch_dtype=torch.float16 if mode_select == \"Quick\" else torch.float32,\n",
- " safety_checker= None\n",
- " )\n",
- " pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)\n",
- "\n",
- "\n",
- " else:\n",
- " try:\n",
- " pipe = StableDiffusionPipeline.from_pretrained(\n",
- " model_id, torch_dtype=torch.float16 if mode_select == \"Quick\" else torch.float32,\n",
- " use_safetensors=True,\n",
- " )\n",
- " #pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)\n",
- " except:\n",
- " pipe = StableDiffusionPipeline.from_pretrained(\n",
- " model_id, torch_dtype=torch.float16 if mode_select == \"Quick\" else torch.float32,\n",
- " )\n",
- " #pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)\n",
- "\n",
- "\n",
- " else:\n",
- " if Filter_off==True:\n",
- " try:\n",
- " pipe = StableDiffusionImg2ImgPipeline.from_pretrained(\n",
- " model_id, torch_dtype=torch.float16 if mode_select == \"Quick\" else torch.float32,\n",
- " safety_checker= None,\n",
- " use_safetensors=True,\n",
- " )\n",
- " pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)\n",
- " except:\n",
- " pipe = StableDiffusionImg2ImgPipeline.from_pretrained(\n",
- " model_id, torch_dtype=torch.float16 if mode_select == \"Quick\" else torch.float32,\n",
- " safety_checker= None,\n",
- " )\n",
- " pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)\n",
- "\n",
- "\n",
- " else:\n",
- " try:\n",
- " pipe = StableDiffusionImg2ImgPipeline.from_pretrained(\n",
- " model_id, torch_dtype=torch.float16 if mode_select == \"Quick\" else torch.float32,\n",
- " use_safetensors=True,\n",
- " )\n",
- " pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)\n",
- " except:\n",
- " pipe = StableDiffusionImg2ImgPipeline.from_pretrained(\n",
- " model_id, torch_dtype=torch.float16 if mode_select == \"Quick\" else torch.float32,\n",
- " )\n",
- " pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)\n",
- "\n",
- "\n",
- " pipe = pipe.to(device)\n",
- " return pipe\n",
- "\n",
- "\n",
- "#def ima3ima(modl_id):\n",
- " # model_T=\"stable_diffusion_txt2img\"+model_id\n",
- " #return model_T\n",
- "#ima3ima(model_id)\n",
- "# txt2img モードで Pipeline オブジェクトを作成\n",
- "#model_T = StableDiffusionPipeline.from_pretrained(model_id)\n",
- "\n",
- "# generate text using fine-tuned model\n",
- "#nlp = pipeline('text-generation', model=text_model_name)\n",
- "\n",
- "pipe=pipe_setup()\n",
- "EN='埋め込み: 有効\\n有効化の鍵: \"EasyNegative\" , bad-hands\",\"bad-artist-anime\",bad-artist,\"bad_prompt\",\"deep_negative\",\"bad_image_negative\"'\n",
- "if can_EN:\n",
- " EP=\"embed/negative\"\n",
- " try:\n",
- " pipe.load_textual_inversion(\n",
- " EP, weight_name=\"EasyNegativeV2.safetensors\", token=\"EasyNegative\"\n",
- " )\n",
- " pipe.load_textual_inversion(\n",
- " EP, weight_name=\"bad-artist-anime.pt\", token=\"bad-artist-anime\"\n",
- " )\n",
- " pipe.load_textual_inversion(\n",
- " EP, weight_name=\"bad-artist.pt\", token=\"bad-artist\"\n",
- " )\n",
- "\n",
- " pipe.load_textual_inversion(\n",
- " EP, weight_name=\"bad-hands-5.pt\", token=\"bad-hands\"\n",
- " )\n",
- " #pipe.load_textual_inversion(\n",
- " # EP, weight_name=\"bad-image-v2-39000.pt\", token=\"bad-image\"\n",
- " #)\n",
- " pipe.load_textual_inversion(\n",
- " EP, weight_name=\"bad_prompt_version2.pt\", token=\"bad_prompt\"\n",
- " )\n",
- " pipe.load_textual_inversion(\n",
- " EP, weight_name=\"ng_deepnegative_v1_75t.pt\", token=\"deep_negative\"\n",
- " )\n",
- " pipe.load_textual_inversion(\n",
- " EP, weight_name=\"verybadimagenegative_v1.3.pt\", token=\"bad_image_negative\"\n",
- " )\n",
- "\n",
- " except:\n",
- " if not model_select ==\"Custom\":\n",
- " print(\"\\033[31m埋め込みのロードに失敗しました。\\033[0m\")\n",
- " EN=\"埋め込み: ご利用になれません\"\n",
- " else:\n",
- " EN=\"\\033[33m埋め込み: このモデルに対応していません\\033[0m\"\n",
- "else:\n",
- " EN=\"\\033[33m埋め込み: このモデルに対応していません\\033[0m\"\n",
- "filter_level=result()\n",
- "\n",
- "\n",
- "#\\033[31mが赤、\\033[33mが黄色、\\033[34mが青、\\033[32mが緑、\\033[0mが白\n",
- "# \"\\033[32m\" は緑色に変更するための\"ANSI Escape Code\"であり、\"\\033[0m\"はデフォルトの文字色に戻すためのコードです。\n",
- "MS=\"____________________________________________________________________________\"\n",
- "Finish1=\"\\033[32m画像生成の準備が出来たので、手順3に移ってください。\\033[0m\"\n",
- "Finish2=\"\\033[32m(Now that the image generation is ready, please proceed to step 3.)\\033[0m\"\n",
- "status=(f\"\\n\\033[34m{MS}\\n\\nmodel_name: {model_name}\\n\\n{mode_text}\\n{word_format}\\n{EN}\\n\\n{filter_level}\\n\\n{Finish1}\\033[0m\")\n",
- "print(\"\\n※設定を変更した場合、再度実行をお願いします\")\n",
- "print(status)"
- ]
- },
- {
- "cell_type": "code",
- "source": [
- "#@title #Step2.パイプラインの作成 (Pipeline Creation){ run: \"auto\", display-mode: \"form\"}\n",
- "\n",
- "#変更\n",
- "\n",
- "#form\n",
- "\n",
- "\n",
- "# @markdown #パイプライン設定\n",
- "# @markdown >モデルの選択 (Model Selection)\n",
- "\n",
- "model_select = \"stable diffusion-v2.1(basic)\" # @param [\"stable diffusion-v2.1(basic)\", \"Counterfeit-V2.5(Anime)(better)\", \"waifu diffusion-v1.4(Anime)\", \"Anything-v3.0(Anime)\", \"Anything-v4.5(Anime)\", \"anything-midjourney-v-4-1(Anime)\", \"ACertainThing(Anime)\", \"anime-kawai-diffusion(Anime)\", \"AB4.5_AC0.2(Anime)\", \"basil_mix(Anime)\", \"Counterfeit(Anime)\", \"Counterfeit-V2.0(Anime)\", \"Double-Exposure-Diffusion(Anime)\", \"EimisAnimeDiffusion_1.0v(Anime)\", \"7th_Layer(Anime)\", \"Riga_Collection(Anime)\", \"openjourney-v4(Reality)\", \"Realistic_Vision_V2.0(Reality)\",\"JWST-Deep-Space-diffusion(space)\",\"Custom\"]\n",
- "\n",
- "#削除モデル(使えないもの)\"epic-space-machine(space_ship)\",\"spacemidj(space)\",\"nasa_space_v2(space)\",\"loliDiffusion(Anime)\",\"chilled_remix(Anime)\"\n",
- "\n",
- "#@markdown Customを選択した場合、下の方に出てくるボックスに入力をお願いします\n",
- "\n",
- "# @markdown >モードの切り替え (mode change)\n",
- "mode_select = \"Quick\" #@param [\"Nomal(better)\",\"Quick\"]\n",
- "\n",
- "#@markdown * \"Nomal\" 品質と生成時間のバランス重視です\n",
- "\n",
- "#@markdown * \"Quick\" 少し品質が低下する代わりに生成時間が大幅に短縮します\n",
- "\n",
- "\n",
- "入力形式 = \"image_and_text\" #@param [\"text_only(better)\", \"image_and_text\"]\n",
- "\n",
- "# @markdown\n",
- "\n",
- "#text_generate_model= \"anime-anything-promptgen-v2\" #@param [\"MagicPrompt-Stable-Diffusion\",\"anime-anything-promptgen-v2\"]\n",
- "\n",
- "\n",
- "# @markdown #追加設定\n",
- "\n",
- "# @markdown >フィルターを調整\n",
- "\n",
- "# @markdown **注意事項 : 変更する時は注意して下さい**\n",
- "\n",
- "Filter_off = False # @param {type:\"boolean\"}\n",
- "\n",
- "\n",
- "# @markdown >同じモデルを使用(Custom設定時のみ)\n",
- "\n",
- "\n",
- "input_skip = True # @param {type:\"boolean\"}\n",
- "\n",
- "# @markdown input_skipは、Custom選択時、同じモデルを何度も使うときに入力の手間を省く機能ですが、違うモデルに変更する場合は上のチェックを外して新しいモデルの情報を入力してください。\n",
- "\n",
- "if \"step1_finish\" not in locals() and \"step1_finish\" not in globals():\n",
- " raise NameError(\"\\033[33m先にStep.1の実行をお願いします\\033[0m\")\n",
- "else:\n",
- " pass\n",
- "\n",
- "\n",
- "\n",
- "def print_text():\n",
- " if mode_select == \"Nomal(better)\":\n",
- " mode_text=\"mode: Nomal\\n\"\n",
- " else:\n",
- " mode_text=\"mode: Quick\\n\"\n",
- " return mode_text\n",
- "\n",
- "def print_format():\n",
- " if 入力形式 == \"text_only(better)\":\n",
- " word_format=\"入力形式: text_only\\n\"\n",
- " else:\n",
- " word_format=\"入力形式: image_and_text\\n\"\n",
- " return word_format\n",
- "\n",
- "mode_text=print_text()\n",
- "word_format=print_format()\n",
- "\n",
- "\n",
- "def result():\n",
- " if Filter_off == False:\n",
- " filter_level = \"フィルターの強度:通常\"\n",
- " else:\n",
- " filter_level = \"\\033[33mフィルターの強度:無効\\033[0m\"\n",
- " return filter_level\n",
- "\n",
- "def safe():\n",
- " if Filter_off ==False:\n",
- " safety_checker = \"\"\n",
- "\n",
- " else:\n",
- " safety_checker = None\n",
- " return safety_checker\n",
- "\n",
- "\n",
- "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
- "#model, preprocess = clip.load(\"laion/CLIP-ViT-H-14-laion2B-s32B-b79K\", device=device)\n",
- "\n",
- "\n",
- "if \"hugface_path\" not in locals() or not hugface_path:\n",
- " input_fin = False\n",
- "else:\n",
- " input_fin = True\n",
- "\n",
- "\n",
- "# 使用するモデルを設定\n",
- "if model_select ==\"Custom\":\n",
- " if input_skip and input_fin==True:\n",
- " pass\n",
- " elif not input_skip or input_fin==False:\n",
- " print(\n",
- " \"\\033[34m入力例 ： ＜user_name＞/＜repository_name＞\\n\"\n",
- " \" * stabilityai / stable-diffusion-2-1\\n\"\n",
- " \" * hakurei / waifu-diffusion\\n\"\n",
- " )\n",
- " hugface_path = input(\"hugface_path: \")\n",
- " else:\n",
- " print(\"申し訳ありません。バグが発生しました。\\n\"\n",
- " \"input_fin: {input_fin}\\n\"\n",
- " \"input_skip: {input_skip}\"\n",
- "\n",
- " )\n",
- " try:\n",
- " user_name, repository_name = hugface_path.split(\"/\")\n",
- " except:\n",
- " TypeError(\"パスを読み込めませんでした\")\n",
- " model_name = repository_name\n",
- " model_id = hugface_path\n",
- " can_EN = True\n",
- "\n",
- "elif model_select == \"stable diffusion-v2.1(basic)\":\n",
- " model_id = \"stabilityai/stable-diffusion-2-1\"\n",
- " model_name = \"stable_diffusion-v2.1\"\n",
- " can_EN=False\n",
- "\n",
- "elif model_select == \"waifu diffusion-v1.4(Anime)\":\n",
- " model_id = \"hakurei/waifu-diffusion\"\n",
- " model_name = \"waifu_diffusion-v1.4\"\n",
- " can_EN=False\n",
- "\n",
- "elif model_select == \"Anything-v3.0(Anime)\":\n",
- " model_id = \"Linaqruf/anything-v3.0\"\n",
- " model_name = \"Anything-v3.0\"\n",
- " can_EN=True\n",
- "\n",
- "elif model_select == \"anything-midjourney-v-4-1(Anime)\":\n",
- " model_id = \"Joeythemonster/anything-midjourney-v-4-1\"\n",
- " model_name =\"anything-midjourney-v-4-1\"\n",
- " can_EN=True\n",
- "\n",
- "elif model_select == \"Anything-v4.5(Anime)\":\n",
- " model_id = \"shibal1/anything-v4.5-clone\"\n",
- " model_name = \"Anything-v4.5\"\n",
- " can_EN=False\n",
- " #Airic/Anything-V4.5\n",
- "\n",
- "\n",
- "#elif model_select == \"loliDiffusion(Anime)\":\n",
- "# model_id = \"JosefJilek/loliDiffusion\"\n",
- "# model_name = \"loliDiffusion\"\n",
- "\n",
- "elif model_select == \"AB4.5_AC0.2(Anime)\":\n",
- " model_id = \"aioe/AB4.5_AC0.2\"\n",
- " model_name = \"AB4.5_AC0.2\"\n",
- " can_EN=False\n",
- "\n",
- "elif model_select == \"basil_mix(Anime)\":\n",
- " model_id = \"nuigurumi/basil_mix\"\n",
- " model_name = \"basil_mix\"\n",
- " can_EN=True\n",
- "\n",
- "\n",
- "elif model_select == \"Double-Exposure-Diffusion(Anime)\":\n",
- " model_id = \"joachimsallstrom/Double-Exposure-Diffusion\"\n",
- " model_name = \"Double-Exposure-Diffusion\"\n",
- " can_EN=True\n",
- "\n",
- "elif model_select == \"openjourney-v4(Reality)\":\n",
- " model_id = \"prompthero/openjourney-v4\"\n",
- " model_name= \"openjourney-v4\"\n",
- " can_EN=True\n",
- "\n",
- "\n",
- "elif model_select == \"ACertainThing(Anime)\":\n",
- " model_id =\"JosephusCheung/ACertainThing\"\n",
- " model_name=\"ACertainThing\"\n",
- " can_EN=True\n",
- "\n",
- "elif model_select == \"Counterfeit-V2.0(Anime)\":\n",
- " model_id = \"gsdf/Counterfeit-V2.0\"\n",
- " model_name= \"Counterfeit-V2.0\"\n",
- " can_EN=True\n",
- "\n",
- "\n",
- "elif model_select == \"Counterfeit-V2.5(Anime)(better)\":\n",
- " model_id = \"gsdf/Counterfeit-V2.5\"\n",
- " model_name =\"Counterfeit-V2.5\"\n",
- " can_EN=True\n",
- "\n",
- "elif model_select == \"7th_Layer(Anime)\":\n",
- " model_id = \"syaimu/7th_test\"\n",
- " model_name = \"7th_Layer\"\n",
- " can_EN=True\n",
- "\n",
- "\n",
- "elif model_select == \"EimisAnimeDiffusion_1.0v(Anime)\":\n",
- " model_id = \"eimiss/EimisAnimeDiffusion_1.0v\"\n",
- " model_name = \"EimisAnimeDiffusion_1.0v\"\n",
- " can_EN=True\n",
- "\n",
- "\n",
- "elif model_select==\"Riga_Collection(Anime)\":\n",
- " mdoel_id =\"natsusakiyomi/Riga_Collection\"\n",
- " model_name=\"Riga_Collection\"\n",
- " can_EN=True\n",
- "\n",
- "\n",
- "# モードの切り替え (mode change)\n",
- "elif model_select ==\"anime-kawai-diffusion(Anime)\":\n",
- " model_id=\"Ojimi/anime-kawai-diffusion\"\n",
- " model_name=\"anime-kawai-diffusion\"\n",
- " can_EN=True\n",
- "\n",
- "elif model_select == \"anything-midjourney-v-4-1(Anime)\":\n",
- " model_id = \"Joeythemonster/anything-midjourney-v-4-1\"\n",
- " model_name =\"anything-midjourney-v-4-1\"\n",
- " can_EN=True\n",
- "\n",
- "\n",
- "elif model_select==\"Realistic_Vision_V2.0(Reality)\":\n",
- " model_id=\"SG161222/Realistic_Vision_V2.0\"\n",
- " model_name=\"Realistic_Vision_V2.0\"\n",
- " can_EN=True\n",
- "\n",
- "\n",
- "elif model_select==\"JWST-Deep-Space-diffusion(space)\":\n",
- " model_id=\"dallinmackay/JWST-Deep-Space-diffusion\"\n",
- " model_name=\"JWST-Deep-Space-diffusion\"\n",
- " can_EN=True\n",
- "\n",
- "#入れられないけど Deyo/SEmix\n",
- "\n",
- "\n",
- "def pipe_setup():\n",
- " if 入力形式 == \"text_only(better)\":\n",
- " if Filter_off==True:\n",
- " try:\n",
- " pipe = StableDiffusionPipeline.from_pretrained(\n",
- " model_id, torch_dtype=torch.float16 if mode_select == \"Quick\" else torch.float32,\n",
- " safety_checker= None,\n",
- " use_safetensors=True,\n",
- " )\n",
- " pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)\n",
- " except:\n",
- " pipe = StableDiffusionPipeline.from_pretrained(\n",
- " model_id, torch_dtype=torch.float16 if mode_select == \"Quick\" else torch.float32,\n",
- " safety_checker= None\n",
- " )\n",
- " pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)\n",
- "\n",
- "\n",
- " else:\n",
- " try:\n",
- " pipe = StableDiffusionPipeline.from_pretrained(\n",
- " model_id, torch_dtype=torch.float16 if mode_select == \"Quick\" else torch.float32,\n",
- " use_safetensors=True,\n",
- " )\n",
- " #pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)\n",
- " except:\n",
- " pipe = StableDiffusionPipeline.from_pretrained(\n",
- " model_id, torch_dtype=torch.float16 if mode_select == \"Quick\" else torch.float32,\n",
- " )\n",
- " #pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)\n",
- "\n",
- "\n",
- " else:\n",
- " if Filter_off==True:\n",
- " try:\n",
- " pipe = StableDiffusionImg2ImgPipeline.from_pretrained(\n",
- " model_id, torch_dtype=torch.float16 if mode_select == \"Quick\" else torch.float32,\n",
- " safety_checker= None,\n",
- " use_safetensors=True,\n",
- " )\n",
- " pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)\n",
- " except:\n",
- " pipe = StableDiffusionImg2ImgPipeline.from_pretrained(\n",
- " model_id, torch_dtype=torch.float16 if mode_select == \"Quick\" else torch.float32,\n",
- " safety_checker= None,\n",
- " )\n",
- " pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)\n",
- "\n",
- "\n",
- " else:\n",
- " try:\n",
- " pipe = StableDiffusionImg2ImgPipeline.from_pretrained(\n",
- " model_id, torch_dtype=torch.float16 if mode_select == \"Quick\" else torch.float32,\n",
- " use_safetensors=True,\n",
- " )\n",
- " pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)\n",
- " except:\n",
- " pipe = StableDiffusionImg2ImgPipeline.from_pretrained(\n",
- " model_id, torch_dtype=torch.float16 if mode_select == \"Quick\" else torch.float32,\n",
- " )\n",
- " pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)\n",
- "\n",
- "\n",
- " pipe = pipe.to(device)\n",
- " return pipe\n",
- "\n",
- "\n",
- "#def ima3ima(modl_id):\n",
- " # model_T=\"stable_diffusion_txt2img\"+model_id\n",
- " #return model_T\n",
- "#ima3ima(model_id)\n",
- "# txt2img モードで Pipeline オブジェクトを作成\n",
- "#model_T = StableDiffusionPipeline.from_pretrained(model_id)\n",
- "\n",
- "# generate text using fine-tuned model\n",
- "#nlp = pipeline('text-generation', model=text_model_name)\n",
- "\n",
- "pipe=pipe_setup()\n",
- "EN='埋め込み: 有効\\n有効化の鍵: \"EasyNegative\" , bad-hands\",\"bad-artist-anime\",bad-artist,\"bad_prompt\",\"deep_negative\",\"bad_image_negative\"'\n",
- "if can_EN:\n",
- " EP=\"embed/negative\"\n",
- " try:\n",
- " pipe.load_textual_inversion(\n",
- " EP, weight_name=\"EasyNegativeV2.safetensors\", token=\"EasyNegative\"\n",
- " )\n",
- " pipe.load_textual_inversion(\n",
- " EP, weight_name=\"bad-artist-anime.pt\", token=\"bad-artist-anime\"\n",
- " )\n",
- " pipe.load_textual_inversion(\n",
- " EP, weight_name=\"bad-artist.pt\", token=\"bad-artist\"\n",
- " )\n",
- "\n",
- " pipe.load_textual_inversion(\n",
- " EP, weight_name=\"bad-hands-5.pt\", token=\"bad-hands\"\n",
- " )\n",
- " #pipe.load_textual_inversion(\n",
- " # EP, weight_name=\"bad-image-v2-39000.pt\", token=\"bad-image\"\n",
- " #)\n",
- " pipe.load_textual_inversion(\n",
- " EP, weight_name=\"bad_prompt_version2.pt\", token=\"bad_prompt\"\n",
- " )\n",
- " pipe.load_textual_inversion(\n",
- " EP, weight_name=\"ng_deepnegative_v1_75t.pt\", token=\"deep_negative\"\n",
- " )\n",
- " pipe.load_textual_inversion(\n",
- " EP, weight_name=\"verybadimagenegative_v1.3.pt\", token=\"bad_image_negative\"\n",
- " )\n",
- "\n",
- " except:\n",
- " if not model_select ==\"Custom\":\n",
- " print(\"\\033[31m埋め込みのロードに失敗しました。\\033[0m\")\n",
- " EN=\"埋め込み: ご利用になれません\"\n",
- " else:\n",
- " EN=\"\\033[33m埋め込み: このモデルに対応していません\\033[0m\"\n",
- "else:\n",
- " EN=\"\\033[33m埋め込み: このモデルに対応していません\\033[0m\"\n",
- "filter_level=result()\n",
- "\n",
- "\n",
- "#\\033[31mが赤、\\033[33mが黄色、\\033[34mが青、\\033[32mが緑、\\033[0mが白\n",
- "# \"\\033[32m\" は緑色に変更するための\"ANSI Escape Code\"であり、\"\\033[0m\"はデフォルトの文字色に戻すためのコードです。\n",
- "MS=\"____________________________________________________________________________\"\n",
- "Finish1=\"\\033[32m画像生成の準備が出来たので、手順3に移ってください。\\033[0m\"\n",
- "Finish2=\"\\033[32m(Now that the image generation is ready, please proceed to step 3.)\\033[0m\"\n",
- "status=(f\"\\n\\033[34m{MS}\\n\\nmodel_name: {model_name}\\n\\n{mode_text}\\n{word_format}\\n{EN}\\n\\n{filter_level}\\n\\n{Finish1}\\033[0m\")\n",
- "print(\"\\n※設定を変更した場合、再度実行をお願いします\")\n",
- "print(status)"
- ],
- "metadata": {
- "id": "aHJENwr7xwIG"
- },
- "execution_count": null,
- "outputs": []
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "xXSW3nl8UT7x"
- },
- "outputs": [],
- "source": [
- "#@title #Step3.画像の生成 (iamge generation){display-mode: \"form\"}\n",
- "\n",
- "#@markdown #自動生成\n",
- "\n",
- "自動で条件を決めて生成 = False #@param {type:\"boolean\"}\n",
- "\n",
- "#@markdown **操作がよくわからない方はチェックをつけて下さい。自動で生成します**\n",
- "\n",
- "#@markdown >この機能の詳細\n",
- "#@markdown * 詳細設定を推奨の値に設定\n",
- "#@markdown * プロンプトが入力されていない場合、初期値として \"1girl\" / \"1woman\" のいずれかを入力\n",
- "\n",
- "#@markdown >次の機能をオンにします\n",
- "#@markdown * 画面に表示\n",
- "#@markdown * 画像の質を上げるプロントを追加する\n",
- "#@markdown * プロンプトアシストを使う ( MagicPrompt )\n",
- "#@markdown * 推奨するネガティブプロントを使用\n",
- "#@markdown * 条件をメタデーターとして追加する\n",
- "\n",
- "\n",
- "#@markdown\n",
- "\n",
- "#@markdown -----\n",
- "\n",
- "# @markdown >生成したい枚数を入力してください / Please enter the number of images you want to generate here.\n",
- "生成する枚数 = 3 #@param {type:\"slider\", min:1, max:100, step:1}\n",
- "枚数制限なし = False #@param {type:\"boolean\"}\n",
- "#if 生成する枚数 <= 0 or isinstance(生成する枚数, float):\n",
- " # print(\"\\033[31m警告:無効な数字が入力された為デフォルトの1枚に設定しました\\033[0m\")\n",
- " # 生成する枚数 = 1\n",
- "#if 生成する枚数 is None:\n",
- " # print(\"\\033[31m警告:無効な形式な為デフォルトの1枚に設定しました\\033[0m\")\n",
- "# 生成する枚数 = 1\n",
- "\n",
- "# @markdown デフォルトでは1回につき1枚生成します。(By default, one image will be generated per run.)\n",
- "\n",
- "# @markdown ------\n",
- "\n",
- "# @markdown >生成する画像の条件を**英語で**入力してください (Please input the conditions for generating images in **English**.)\n",
- "\n",
- "Prompt = \"\" #@param {type:\"string\"}\n",
- "画像の質を上げるプロントを追加する = True #@param {type:\"boolean\"}\n",
- "#プロンプトアシストを使う = True #@param {type:\"boolean\"}\n",
- "日本語入力 = False #@param {type:\"boolean\"}\n",
- "\n",
- "\n",
- "# @markdown >**プロンプトの例**\n",
- "# @markdown * cute, cat\n",
- "# @markdown * Earth, space, high resolution\n",
- "# @markdown * Please draw a beautiful Mount Fuji with the sun rising from the summit\n",
- "# @markdown * smail,1girl, white hair, medium hair, cat ears, looking at viewer, :3, cute,white_dress\n",
- "\n",
- "\n",
- "# @markdown ------\n",
- "# @markdown >プロンプトアシスタントの選択\n",
- "text_generate_model= \"None\" #@param [\"None\",\"MagicPrompt-Stable-Diffusion\",\"anime-anything-promptgen-v2\",\"gpt2-650k-sd-prompt-generator\"]\n",
- "\n",
- "# @markdown アニメ調の画像に適したアシスタントは \" anime-anything-promptgen-v2 \"\n",
- "\n",
- "# @markdown 多目的のアシスタントは \" MagicPrompt-Stable-Diffusion \"\n",
- "\n",
- "# @markdown 使用しない場合は \" None \" の選択をお願いします\n",
- "\n",
- "条件を統一する = False #@param {type:\"boolean\"}\n",
- "\n",
- "#@markdown 最初の画像のプロンプトを繰り返し使用します\n",
- "\n",
- "# @markdown ------\n",
- "\n",
- "# @markdown >画像を入力として送リます。\n",
- "\n",
- "入力する画像 = \"\" #@param {type:\"string\"}\n",
- "# @markdown 入力形式を \"image_and_text\" とした場合のみに使えます\n",
- "\n",
- "\n",
- "# @markdown ------\n",
- "\n",
- "#@markdown #詳細設定\n",
- "\n",
- "seed = None #@param {type:\"number\"}\n",
- "guidance_scale = 15 #@param {type:\"slider\", min:1, max:30, step:1}\n",
- "#温度 = 0.7 #@param {type:\"slider\", min:0, max:1, step:0.1}\n",
- "#top_k = 17 #@param {type:\"slider\", min:1, max:40, step:1}\n",
- "#top_p = 0 #@param {type:\"slider\", min:0, max:1, step:0.01}\n",
- "#雰囲気 = 0.9 #@param {type:\"slider\", min:0.1, max:1, step:0.1}\n",
- "拡散ステップ = 30 # @param {type:\"number\"}\n",
- "#safe_level = \"safe\" #@param [\"safe\", \"Questionable\", \"Explicit\"]\n",
- "縦の大きさ = \"512\" #@param [\"480\",\"512\",\"600\", \"768\",\"800\", \"1080\",\"1152\", \"1440\", \"1920\", \"3840\", \"7680\"]\n",
- "横の大きさ = \"512\" #@param [\"480\",\"512\",\"600\", \"768\",\"800\", \"1080\",\"1152\", \"1440\", \"1920\", \"3840\", \"7680\"]\n",
- "seed値を固定する = False # @param {type:\"boolean\"}\n",
- "\n",
- "height = int(縦の大きさ)\n",
- "width = int(横の大きさ)\n",
- "\n",
- "#@markdown >用語の説明\n",
- "\n",
- "#@markdown * seed (\"0\"以上) / seed値を指定します。指定しない場合ランダムな数字を割り当てます。\n",
- "\n",
- "#@markdown * guidance_scale (5≦30 推奨\"8\") / どのくらい細かく描くかを指定します。\n",
- "\n",
- "##@markdown * 温度(0.1≦1.0 推奨\"0.8\") / どのくらい条件に合わせるかを指定します。\n",
- "\n",
- "#@markdown * 拡散ステップ(1≦1000 推奨\"50\") / 計算をする回数を指定します。回数を減らすほど生成速度が速くなります\n",
- "\n",
- "#@markdown * 縦・横の大きさ ( 推奨\"512\" ) / 画像の大きさを指定します。大きくすればするほど生成速度が遅くなります\n",
- "\n",
- "# @markdown ------\n",
- "\n",
- "# @markdown >必要であればネガティブプロンプトを入力してください。人物を生成するときにおすすめです\n",
- "\n",
- "# @markdown よくわからない方ボタンを押してください。おすすめのネガティブプロントを使います\n",
- "\n",
- "## @markdown (If necessary, please enter a negative prompt. It is recommended for generating characters.)\n",
- "\n",
- "N_prompt = \"\" # @param {type:\"string\"}\n",
- "推奨するネガティブプロントを使用 = True #@param {type:\"boolean\"}\n",
- "埋め込みを使用 = False #@param {type:\"boolean\"}\n",
- "# @markdown (使用可能の場合)\n",
- "\n",
- "# @markdown ネガティブプロンプトとは、**ネガティブな要素を除く**ものです。\n",
- "\n",
- "## @markdown (Negative prompts are used to exclude negative elements from an image. For example, you can use a negative prompt to exclude low quality images or images that are not beautiful.)\n",
- "\n",
- "# @markdown ------\n",
- "\n",
- "#@markdown >保存する先を指定します\n",
- "\n",
- "## @markdown (If you would like to specify a location to save the generated image, please enter the path.)\n",
- "\n",
- "保存する先のパス = \"\" # @param {type:\"string\"}\n",
- "#@markdown デフォルトでは /content/Generated_images に保存されます。なければ作るようになっています。\n",
- "\n",
- "##@markdown (If no path is specified, the images will be saved to \"/content/生成した画像\". The directory will be created if it doesn't exist.)\n",
- "\n",
- "# @markdown\n",
- "\n",
- "\n",
- "## @markdown (P.S.You can see the images generated at '/content/生成した画像' by clicking the file icon in the left taskbar.)\n",
- "\n",
- "# @markdown ------\n",
- "\n",
- "# @markdown >追加設定\n",
- "\n",
- "画面に表示 = True # @param {type:\"boolean\"}\n",
- "プロンプトを表示 = True # @param {type:\"boolean\"}\n",
- "条件をメタデーターとして追加する = True # @param {type:\"boolean\"}\n",
- "画像の名前 = \"GIMG_No.(number).png\" # @param [\"GIMG_No.(number).png\", \"(seed)_(model_name)_(guidance_scale)_(time).png\"]\n",
- "\n",
- "if \"pipe\" not in locals() and \"pipe\" not in globals():\n",
- " raise NameError(\"\\033[33mパイプラインが見つかりませんでした。Step.2を再度実行してください\\033[0m\")\n",
- "\n",
- "if \"can_EN\" not in locals() and \"can_EN\" not in globals():\n",
- " can_EN = False\n",
- "\n",
- "\n",
- "if 入力形式==\"image_and_text\":\n",
- " try:\n",
- " init_image = Image.open(入力する画像)\n",
- " #init_image = init_image.convert(\"RGB\")\n",
- " init_image = init_image.resize((768, 768))\n",
- " except:\n",
- " raise FileNotFoundError('入力する画像が見つかりませんでした。画像を入力しない場合は、Step.1の入力形式を\"text_only\"に変更お願いします')\n",
- "else:\n",
- " if 入力する画像 is not None or not 入力する画像==\"\":\n",
- " print('\\033[33m画像が反映されていません。画像を使用する場合は、入力形式を ”image_and_text” に変更してください\\033[0m')\n",
- "\n",
- "\n",
- "\n",
- "#bad_words=[\"cleavage\"]\n",
- "#bad_words_ids = [tokenizer(bad_word, add_prefix_space=True, add_special_tokens=False).input_ids for bad_word in bad_words]\n",
- "if 自動で条件を決めて生成 and text_generate_model == \"None\":\n",
- " auto_text=True\n",
- "else:\n",
- " auto_text=False\n",
- "\n",
- "if 画像の質を上げるプロントを追加する or 自動で条件を決めて生成:\n",
- " mini_prompt=True\n",
- "else:\n",
- " mini_prompt=False\n",
- "if text_generate_model == \"None\" and auto_text==False:\n",
- " text_model_name=\"\"\n",
- "elif text_generate_model == \"MagicPrompt-Stable-Diffusion\" or auto_text:\n",
- " text_model_name = \"Gustavosta/MagicPrompt-Stable-Diffusion\"\n",
- " if \"MagicPrompt\" not in locals() or not MagicPrompt:\n",
- " MagicPrompt = pipeline('text-generation', model=text_model_name , do_sample=True , top_k=4 , temperature=0.7)\n",
- "elif text_generate_model == \"anime-anything-promptgen-v2\":\n",
- " text_model_name = \"FredZhang7/anime-anything-promptgen-v2\"\n",
- " if \"AnythingPrompt\" not in locals() or not AnythingPrompt:\n",
- " AnythingPrompt = pipeline('text-generation', model=text_model_name , do_sample=True , top_k=4 , temperature=0.7)\n",
- "elif text_generate_model == \"gpt2-650k-sd-prompt-generator\":\n",
- " text_model_name = \"Ar4ikov/gpt2-650k-stable-diffusion-prompt-generator\"\n",
- " if \"gpt2_sd_prompt\" not in locals() or not gpt2_sd_prompt:\n",
- " gpt2_sd_prompt = pipeline('text-generation', model=text_model_name , do_sample=True , top_k=4 , temperature=0.7)\n",
- "\n",
- "\n",
- "\n",
- "\n",
- "else:\n",
- " print(\"\\033[33m申し訳ありません。想定以外の処理が実行されてしまったため、アシスタントはオフになりました\\033[0m\")\n",
- "#early_stopping=True を削除\n",
- "\n",
- "def word_preprocessing(Prompt):\n",
- " if not Prompt==\"\":\n",
- " if 日本語入力:\n",
- " texts = Prompt\n",
- " encoded_text = codecs.encode(texts, 'utf-8')\n",
- " decoded_text = codecs.decode(encoded_text, 'utf-8')\n",
- " pos_tagger = spacy.load('en_core_web_sm')\n",
- " fugu_translator = pipeline('translation', model='staka/fugumt-ja-en')\n",
- " translation = fugu_translator(decoded_text, src_lang=\"ja\", tgt_lang=\"en\")[0][\"translation_text\"]\n",
- " Prompt_2 = translation #After_Prompt\n",
- " else:\n",
- " Prompt_2 = Prompt\n",
- " else:\n",
- " add_word=random.choice([\"1girl\", \"1woman\"])\n",
- " Prompt_2=add_word\n",
- " print(f\"プロンプトが未入力の為'{add_word}'を入力しました\")\n",
- " return Prompt_2\n",
- "\n",
- "def easy_prompt(Prompt_2,text_model_name):\n",
- " 追加 = \"(masterpiece:2.0),best_quality,high_quality,\"\n",
- " if text_generate_model == \"None\":\n",
- " if mini_prompt==True:\n",
- " Prompt_4 = 追加+Prompt_2\n",
- " else:\n",
- " Prompt_4 = Prompt_2\n",
- " #elif プロンプトアシストを使う or 自動で条件を決めて生成:\n",
- " elif text_generate_model == \"MagicPrompt-Stable-Diffusion\" or 自動で条件を決めて生成:\n",
- " if mini_prompt==True:\n",
- " Prompt_4_P = MagicPrompt(Prompt_2, max_length=67, do_sample=True , top_k=4 , temperature=0.7)[0][\"generated_text\"]\n",
- " Prompt_4=追加+Prompt_4_P\n",
- " else:\n",
- " Prompt_4 = MagicPrompt(Prompt_2, max_length=73, do_sample=True , top_k=4 , temperature=0.7)[0][\"generated_text\"]\n",
- "\n",
- "\n",
- " elif text_generate_model == \"gpt2-650k-sd-prompt-generator\":\n",
- " if mini_prompt==True:\n",
- " Prompt_4_P = gpt2_sd_prompt(Prompt_2, max_length=27, do_sample=True , top_k=4 , temperature=0.7)[0][\"generated_text\"]\n",
- " Prompt_4=追加+Prompt_4_P\n",
- " else:\n",
- " Prompt_4 = gpt2_sd_prompt(Prompt_2, max_length=73, do_sample=True , top_k=4 , temperature=0.7)[0][\"generated_text\"]\n",
- " else:\n",
- " Prompt_4 = Prompt_2\n",
- "\n",
- "\n",
- " return Prompt_4\n",
- "\n",
- "\n",
- "def main_task():\n",
- " Prompt_2=word_preprocessing(Prompt)\n",
- " Prompt_4=easy_prompt(Prompt_2,text_model_name)\n",
- " #prompt=Prompt_4\n",
- " return Prompt_4\n",
- "\n",
- "Prompt_4 = main_task()\n",
- "\n",
- "\n",
- "if seed is None:\n",
- " seed = random.randint(1,1000000)\n",
- "\n",
- "\n",
- "\n",
- "\n",
- "if 推奨するネガティブプロントを使用 or 自動で条件を決めて生成 :\n",
- " if can_EN and 埋め込みを使用:\n",
- " おすすめのネガティブプロント = \",,Loss of eye highlights:1.5,Fingers fused together:1.3,Writing Sweet Fingers:2.0,bad hands:2.0,bad legs:2.0,worst quality:2.0, low quality:2.0,Not five fingers.:2.0,blurred,Missing finger:1.7,Cat with deformed face:1.3 ,medium quality, purple hair,Loss of eye highlights:1.5,Fingers fused together:1.3,Writing Sweet Fingers:2.0 ,deleted:0.5, lowres,Low quality animals, deformed animals ,hands emerging from impossible places:1.7, bad anatomy, more than three limbs hands/legs:1.5, low resolution, blurry, absurdres,pixelated, sketchy, nonsensical anatomy, unrealistic pose, mosaic, unclear details, distorted colors, unrealistic proportions, poor quality, fuzzy, missing head:1.6, out of focus, hazy, grainy, text, error, missing fingers:0.9, extra digit, fewer digits, cropped, jpeg artifacts, signature, watermark, username, standard quality, bad feet_hand_finger_leg_eye, bad, text font ui, bad shadow, poorly drawn, black-white, ugly, duplicate, mutation, mutilated, malformed mutated:1.1, malformed:1.1, The background is incoherent, simple background, low-quality background, low background, bad body, long body, broken limb, anatomical nonsense, extra limbs, missing limb, incorrect limb, multiple heads, twisted head, poorly drawn face, 1 unit with multiple heads:1.3, heads together:1.0, abnormal eye:1.2 proportion, cropped:1.0, bad eyes, fused eyes, poorly drawn eyes, bad mouth, poorly drawn mouth, bad tongue, too long tongue, bad ears, poorly drawn ears, extra ears, heavy ears, long neck, too thick neck, bad neck, bad breasts, missing arms, disappearing arms, extra arms, three arms:2.0, mutated hands and fingers, fused hand, missing fingers, extra digits, huge thighs, disappearing thigh, missing thighs, extra thighs, bad feet, huge calf, disappearing legs, bad gloves, fused gloves, beard, artist name, text watermark, unnatural, obviously wrong, distorted face, floating hair, floating body parts, severed body parts, incorrect leg position, deformed, fused body and hands, disregard of physics, distorted shape, doll-like object not present in the image, body fusion, abnormal fingers, fingers resembling fish fins, dot eyes, unclear background, mosaic, body bending, incorrect leg-to-torso ratio, excessively large breasts, unsettling appearance, eyes filled with solid color, lack of lower body, splitting, creepy doll-like appearance, distorted eyes, lines on the skin, legs bending in unnatural directions, abnormal finger count, missing arms, floating hands, lack of nose or mouth,, incorrect body part ratios, bad, longbody, lowres, bad anatomy, bad hands, missing fingers, Distorted eye contour, Missing part from the ankles onward, extra digit, fewer digits, split wings, Vampire wings floating in the air, bad wing, comic\"\n",
- " else:\n",
- " おすすめのネガティブプロント = \",Loss of eye highlights:1.5,Fingers fused together:1.3,Writing Sweet Fingers:2.0,bad hands:2.0,bad legs:2.0,worst quality:2.0, low quality:2.0,Not five fingers:2.0,blurred,Missing finger:1.7,Cat with deformed face:1.3 ,medium quality, purple hair,Loss of eye highlights:1.5,Fingers fused together:1.3,Writing Sweet Fingers:2.0 ,deleted:0.5, lowres,Low quality animals, deformed animals ,hands emerging from impossible places:1.7, bad anatomy, more than three limbs hands/legs:1.5, low resolution, blurry, absurdres,pixelated, sketchy, nonsensical anatomy, unrealistic pose, mosaic, unclear details, distorted colors, unrealistic proportions, poor quality, fuzzy, missing head:1.6, out of focus, hazy, grainy, text, error, missing fingers:0.9, extra digit, fewer digits, cropped, jpeg artifacts, signature, watermark, username, standard quality, bad feet_hand_finger_leg_eye, bad, text font ui, bad shadow, poorly drawn, black-white, ugly, duplicate, mutation, mutilated, malformed mutated:1.1, malformed:1.1, The background is incoherent, simple background, low-quality background, low background, bad body, long body, broken limb, anatomical nonsense, extra limbs, missing limb, incorrect limb, multiple heads, twisted head, poorly drawn face, 1 unit with multiple heads:1.3, heads together:1.0, abnormal eye:1.2 proportion, cropped:1.0, bad eyes, fused eyes, poorly drawn eyes, bad mouth, poorly drawn mouth, bad tongue, too long tongue, bad ears, poorly drawn ears, extra ears, heavy ears, long neck, too thick neck, bad neck, bad breasts, missing arms, disappearing arms, extra arms, three arms:2.0, mutated hands and fingers, fused hand, missing fingers, extra digits, huge thighs, disappearing thigh, missing thighs, extra thighs, bad feet, huge calf, disappearing legs, bad gloves, fused gloves, beard, artist name, text watermark, unnatural, obviously wrong, distorted face, floating hair, floating body parts, severed body parts, incorrect leg position, deformed, fused body and hands, disregard of physics, distorted shape, doll-like object not present in the image, body fusion, abnormal fingers, fingers resembling fish fins, dot eyes, unclear background, mosaic, body bending, incorrect leg-to-torso ratio, excessively large breasts, unsettling appearance, eyes filled with solid color, lack of lower body, splitting, creepy doll-like appearance, distorted eyes, lines on the skin, legs bending in unnatural directions, abnormal finger count, missing arms, floating hands, lack of nose or mouth,, incorrect body part ratios, bad, longbody, lowres, bad anatomy, bad hands, missing fingers, Distorted eye contour, Missing part from the ankles onward, extra digit, fewer digits, split wings, Vampire wings floating in the air, bad wing, comic\"\n",
- "else:\n",
- " おすすめのネガティブプロント =\"\"\n",
- "\n",
- "\n",
- "negative_prompt2 = N_prompt + おすすめのネガティブプロント\n",
- "\n",
- "if 枚数制限なし:\n",
- " 生成する枚数=10000000\n",
- "st=生成する枚数\n",
- "\n",
- "\n",
- "if 保存する先のパス:\n",
- " if not Google_driveに接続:\n",
- " if \"/content/drive/MyDrive\" in 保存する先のパス:\n",
- " image_save_path=\"/content/生成した画像\"\n",
- " print(\"\\033[31mGoogleドライブに接続されていないためデフォルトのパスに保存しました\\033[0m\")\n",
- " else:\n",
- " image_save_path=保存する先のパス\n",
- " else:\n",
- " image_save_path=保存する先のパス\n",
- "else:\n",
- " image_save_path=\"/content/Generated_images\"\n",
- "if not os.path.exists(image_save_path):\n",
- " os.makedirs(image_save_path)\n",
- "\n",
- "def seed_set():\n",
- " seed = random.randint(1,1000000)\n",
- " return seed\n",
- "\n",
- "\n",
- "def seeed(device):\n",
- " #generator=\"\"\n",
- " global generator\n",
- " seed=seed_set()\n",
- " generator = torch.Generator(device).manual_seed(seed)\n",
- " return generator,seed\n",
- "generator,seed=seeed(device)\n",
- "\n",
- "\n",
- "sd_step=拡散ステップ\n",
- "\n",
- "if \"generate_image_number\" not in globals():\n",
- " generate_image_number=1\n",
- "\n",
- "def gin():\n",
- " global generate_image_number\n",
- " generate_image_number+=1\n",
- " return generate_image_number\n",
- "\n",
- "\n",
- "\n",
- "def generate_images(st,Prompt_4,generator,image_save_path,sd_step,seed,generate_image_number,model_name):\n",
- " i=1\n",
- " generate_time_all=0\n",
- " for i in range(生成する枚数):\n",
- " generate_start_time = time.time()\n",
- " j=i+1\n",
- " now = datetime.now()\n",
- " date_str = now.strftime(\"%Y-%m-%d_UTC-%H:%M:%S\")\n",
- "\n",
- " if 画像の名前 == \"GIMG_No.(number).png\":\n",
- " filenames = (f\"GIMG_No.{generate_image_number}.png\")\n",
- " else:\n",
- " filenames = (f\"seed({seed})_model({model_name})_guidance_scale({guidance_scale})_{date_str}.png\")\n",
- " path = os.path.join(image_save_path, filenames)\n",
- " if not 条件を統一する:\n",
- " if i >= 1:\n",
- " Prompt_4 = main_task()\n",
- " if not seed値を固定する:\n",
- " if i >= 1:\n",
- " generator,seed=seeed(device)\n",
- " if 入力形式 == \"image_and_text\":\n",
- " with autocast(\"cuda\"):\n",
- " result = pipe(prompt=Prompt_4, image=init_image, negative_prompt=negative_prompt2, num_inference_steps=sd_step,guidance_scale=guidance_scale,generator=generator)\n",
- " make_image = result.images[0]\n",
- " else:\n",
- " with autocast(\"cuda\"):\n",
- " result = pipe(prompt=Prompt_4, negative_prompt=negative_prompt2, guidance_scale=guidance_scale, num_inference_steps=sd_step,height=height,width=width,generator=generator)\n",
- " make_image = result.images[0]\n",
- " info = make_image.info\n",
- " if 条件をメタデーターとして追加する or 自動で条件を決めて生成:\n",
- " metadata = {\n",
- " \"Seed\": seed,\n",
- " \"model\": model_name,\n",
- " \"G_scale\":guidance_scale,\n",
- " \"D_step\":sd_step,\n",
- " \"Prompt\": Prompt_4,\n",
- " \"n_prompt\":negative_prompt2\n",
- " }\n",
- " pnginfo = PngImagePlugin.PngInfo()\n",
- " for key, value in metadata.items():\n",
- " pnginfo.add_text(key, str(value))\n",
- " make_image.save(path, pnginfo=pnginfo)\n",
- " else:\n",
- " make_image.save(path)\n",
- " generate_end_time = time.time()\n",
- " generate_time = generate_end_time - generate_start_time\n",
- " generate_time_all += generate_time\n",
- " generate_time_after= round(generate_time, 2)\n",
- " #generate_time_after=(\"{:.2f}s\".format(generate_time))\n",
- " generate_start_time= \"\"\n",
- " generate_end_time=\"\"\n",
- " generate_image_number=gin()\n",
- " if 枚数制限なし:\n",
- " print(f\"\\033[34m画像生成が完了しました ({j}/∞) {generate_time_after}s\")\n",
- " else:\n",
- " print(f\"\\033[34m画像生成が完了しました ({j}/{st}) {generate_time_after}s\")\n",
- " print(f\"\\033[32mseed値: {seed}\")\n",
- " print(f\"ファイルの名前:( \\033[32m{filenames}\\033[34m )\")\n",
- " print(f\"保存先のパス:( \\033[32m{path}\\033[34m )\")\n",
- " print('メタデータをご覧になる場合は、「保存先のパス」をコピー＆ペーストしてください')\n",
- " print(\"上記のようになります。ご確認ください\\033[0m\")\n",
- " if 画面に表示 or 自動で条件を決めて生成:\n",
- " img = Image.open(path)\n",
- " display(img)\n",
- " if プロンプトを表示:\n",
- " print('\\033[92mプロンプト: ' + Prompt_4 + '\\033[0m\\n') # \"\\033[38;2;135;206;235m\" はスカイブルー \"\\033[38;2;255;165;0m\"はオレンジ\n",
- " generate_time_all_after=generate_time_all//生成する枚数\n",
- " generate_time_all_after2=round(generate_time_all_after, 2)\n",
- " print(f\"\\033[38;2;135;206;235m1枚あたりの生成時間の平均: {generate_time_all_after2}s \\033[0m\\n\")\n",
- "generate_images(st,Prompt_4,generator,image_save_path,sd_step,seed,generate_image_number,model_name)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "cellView": "form",
- "id": "fNvVEw3IqFsl"
- },
- "outputs": [],
- "source": [
- "#@title 画像を高画質化\n",
- "from PIL import Image\n",
- "from diffusers import StableDiffusionUpscalePipeline\n",
- "import torch\n",
- "プロンプト = \"\" # @param {type:\"string\"}\n",
- "\n",
- "\n",
- "高画質化する画像のパス = \"\" # @param {type:\"string\"}\n",
- "\n",
- "\n",
- "model_id = \"stabilityai/stable-diffusion-x4-upscaler\"\n",
- "pipeline = StableDiffusionUpscalePipeline.from_pretrained(model_id, torch_dtype=torch.float16)\n",
- "pipeline = pipeline.to(\"cuda\")\n",
- "\n",
- "\n",
- "low_res_img = Image.open(高画質化する画像のパス)\n",
- "low_res_img = low_res_img.resize((128, 128))\n",
- "\n",
- "upscaled_image = pipeline(prompt=プロンプト, image=low_res_img).images[0]\n",
- "upscaled_image.save(\"upsampled_cat.png\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "rWELM49rSTXq"
- },
- "outputs": [],
- "source": [
- "#@title 画像フォルダを削除 {display-mode: \"form\"}\n",
- "import shutil\n",
- "画像フォルダを削除 = True #@param {type:\"boolean\"}\n",
- "#@markdown /content/Generated_imagesを削除します\n",
- "if 画像フォルダを削除:\n",
- " try:\n",
- " shutil.rmtree('/content/Generated_images')\n",
- " except:\n",
- " print(\"\\033[31m/content/Generated_images が見つかりませんでした\\033[0m\")\n",
- "else:\n",
- " print(\"画像フォルダを削除にチェックをお願いします\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "FxGYicFhvS6Y",
- "outputId": "597b14f6-af61-44f2-c928-26b38e4be3e4"
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "seed: 756527\n",
- "\n",
- "diffusion_step: 40\n",
- "\n",
- "guidance_scale: 12\n",
- "\n",
- "model_name : Counterfeit-V2.5\n",
- "\n",
- "prompt: \u001b[92mGirl eating popcorn in image.,upper body, \u001b[0m\n",
- "\n"
- ]
- }
- ],
- "source": [
- "#@title 画像のメタデータを見る {display-mode: \"form\"}\n",
- "from PIL import Image, PngImagePlugin\n",
- "import os\n",
- "image_metadata_path = \"/content/Generated_images/GIMG_No.4.png\" #@param {type:\"string\"}\n",
- "if not os.path.exists(image_metadata_path):\n",
- " raise FileNotFoundError(\"ファイルが見つかりませんでした\")\n",
- "try:\n",
- " output_info = Image.open(image_metadata_path).info\n",
- "except:\n",
- " raise FileNotFoundError(\"画像を読み込めませんでした\")\n",
- "\n",
- "try:\n",
- " print(\"seed: \"+output_info[\"Seed\"]+\"\\n\")\n",
- " print(\"diffusion_step: \"+output_info[\"D_step\"]+\"\\n\")\n",
- " print(\"guidance_scale: \"+output_info[\"G_scale\"]+\"\\n\")\n",
- " print(\"model_name : \"+output_info[\"model\"]+\"\\n\")\n",
- " print(\"prompt: \\033[92m\"+output_info[\"Prompt\"]+\"\\033[0m\\n\")\n",
- "except:\n",
- " print(\"\\033[31mメタデーターが見つかりませんでした\\033[0m\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "uPxapx46KtcH"
- },
- "outputs": [],
- "source": [
- "#@title {display-mode: \"form\"}\n",
- "#@markdown >zip形式にしてダウンロードします。\n",
- "\n",
- "#@markdown ダウンロード対象のフォルダ: /content/Generated_images\n",
- "from google.colab import files\n",
- "import shutil\n",
- "import os\n",
- "base_save_dir=\"/content/Generated_images\"\n",
- "\n",
- "if not os.path.exists(base_save_dir):\n",
- " raise FileNotFoundError(\"生成した画像が見つかりませんでした\")\n",
- "\n",
- "try:\n",
- " zip_number=zip_number+1\n",
- "except:\n",
- " zip_number=1\n",
- "\n",
- "zip_name=f\"Generated_images-No.{zip_number}\"\n",
- "zip_save_dir=os.path.join(\"/content\",zip_name)\n",
- "zippath=zip_save_dir+\".zip\"\n",
- "try:\n",
- " shutil.make_archive(zip_save_dir, \"zip\", base_save_dir)\n",
- " files.download(zippath)\n",
- " print(\"\\033[32mzipファイルへ圧縮が正常に完了しました\")\n",
- " print(f'zipファイル名前は\\033[34m\"{zip_name}\"\\033[32mですご確認ください\\033[0m')\n",
- "except:\n",
- " zip_number=zip_number-1\n",
- " print(\"\\033[31mzipファイルへの圧縮に失敗しました\\033[0m\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "tPjosOVDWYII"
- },
- "outputs": [],
- "source": [
- "#@title {display-mode: \"form\"}\n",
- "ランタイムを一時的に切断する = False #@param {type: 'boolean'}\n",
- "#@markdown 作業を中断するときなどにチェックをつけて実行してください /Please check and execute when interrupting the task.\n",
- "if ランタイムを一時的に切断する == True:\n",
- " from google.colab import runtime\n",
- " runtime.unassign()\n",
- "else:\n",
- " print('ランタイムの切断をキャンセルしました')"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "_20K18NBcgLL"
- },
- "source": [
- "# **Image generation methods**\n",
- "\n",
- "\n",
- "\n",
- ""
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "qnoU8WBIgR4j"
- },
- "source": [
- "# **How to copy the path of an image**\n",
- "\n",
- " **Please modify the steps as needed**\n",
- "\n",
- "> Step.1\n",
- "\n",
- "\n",
- "\n",
- "> Step.2\n",
- "\n",
- "\n",
- "\n",
- "\n",
- "\n",
- "\n",
- "> Step.3\n",
- "\n",
- "\n",
- "\n",
- "\n",
- "\n",
- "\n",
- "\n",
- "> Step.4\n",
- "\n",
- "\n",
- "\n",
- "\n",
- "\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "dcFcNdQdH-BF"
- },
- "source": [
- "埋め込みが適用可能なのは、追加学習のベースモデルがstable diffusion-v1.5までのバージョンのみです。\n",
- "現在の最新のバージョンであるstable diffusion-v2.1をベースモデルとしたものには使用できません。"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "MJXQRW_E3AsI"
- },
- "source": [
- "#**Readme**(日本語版)\n",
- "#利用規約\n",
- "\n",
- "本画像生成ノーブックを使用するにあたって、利用規約の内容に全て同意したとみなします。\n",
- "\n",
- "# **重要な注意点**：\n",
- "* **商用利用はご遠慮ください。**\n",
- "* **画像生成によって起こった問題について、私は一切責任を負いません。**\n",
- "\n",
- ">免責事項:\n",
- "* 使用にあたっては、自己責任でお願いします。\n",
- "* 本モデルは予告なく変更・非公開・削除する可能性があります。\n",
- "* 利用規約は予告なく変更する場合があります。\n",
- "* このモデルは、趣味で作成したものであり、商用利用などは意図していません。\n",
- "* 使用にあたって発生した通信量、電気料金など金銭に関わるものの負担は追い兼ねます\n",
- "* Stable Diffusion-Ver2.1やその他の追加ライブラリに関する規約がある場合は、それらも確認することを強くお勧めします。\n",
- "* 本プロジェクトを利用することにより生じた一切の問題について、私は一切責任を負いません。\n",
- "\n",
- "ー本プロジェクトとは、本画像生成ノートブックや、githubのページなどをさします\n",
- "___\n",
- "#本プロジェクトの説明\n",
- "Stable Diffusion-Ver2.1をベースにした画像生成ノートブックです。\n",
- "\n",
- "\n",
- ">使用させていただいたライブラリ\n",
- "- Stable Diffusion-ver2.1\n",
- "- CLIP\n",
- "- tqdm\n",
- "- ftfy\n",
- "- scipy\n",
- "- regex\n",
- "- torch\n",
- "- diffusers\n",
- "- accelerate\n",
- "- safetensors\n",
- "- transformers\n",
- "\n",
- "※2023/5/12時点\n",
- "---\n",
- "\n",
- "謝辞\n",
- "\n",
- "本画像生成ノートブックの作成にあたり、オープンソースのリソースやフリーのツールを使用させていただきました。個人的な利用でしたが、これらのリソースやツールがあったからこそ、本プロジェクトを実現することができました。\n",
- "この場を借りて、オープンソースのコミュニティや、フリーのツールを提供してくださった方々に感謝の意を表します。素晴らしいツールや技術を提供してくださり、本プロジェクトを支援してくださったことに心から感謝いたします。"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "XKISm_HGOcgG"
- },
- "source": [
- "#**Readme(English_ver)**\n",
- "# Terms of Use\n",
- "\n",
- "By using this image generation notebook, you agree to all the contents of the Terms of Use.\n",
- "\n",
- "Important Notice:\n",
- "**Please refrain from using for commercial purposes.**\n",
- "**I am not responsible for any problems caused by image generation.**\n",
- "\n",
- ">Disclaimer:\n",
- "* Please use it at your own risk.\n",
- "* This NoteBook may be changed, unpublished, or deleted without notice.\n",
- "* The terms of use may be changed without notice.\n",
- "* This NoteBook is created for personal use and is not intended for commercial use.\n",
- "* If there are terms and conditions for Stable Diffusion-Ver2.1 and other additional libraries, it is strongly recommended to confirm them as well.\n",
- "* I am not responsible for any problems caused by using this project.\n",
- "\n",
- "ー This project refers to the image generation notebook and GitHub pages.\n",
- "\n",
- "---\n",
- "\n",
- "# Description of this project\n",
- "\n",
- "This is an image generation notebook based on Stable Diffusion-Ver2.1.\n",
- "\n",
- "**Tools used**\n",
- "* As of 2023/5/12\n",
- "\n",
- ">**Libraries used**\n",
- "- Stable Diffusion-ver2.1\n",
- "- CLIP\n",
- "- tqdm\n",
- "- ftfy\n",
- "- scipy\n",
- "- regex\n",
- "- torch\n",
- "- diffusers\n",
- "- accelerate\n",
- "- safetensors\n",
- "- transformers\n",
- "\n",
- "---\n",
- "\n",
- "# Acknowledgements\n",
- "\n",
- "I used open source resources and free tools to create this image generation notebook. Although it was for personal use, it was only possible to realize this project because of these resources and tools.\n",
- "I would like to express my gratitude to the open source community and those who provide free tools. I sincerely appreciate your support for this project by providing great tools and technologies.\n"
- ]
- }
- ],
- "metadata": {
- "accelerator": "GPU",
- "colab": {
- "provenance": [],
- "include_colab_link": true
- },
- "kernelspec": {
- "display_name": "Python 3",
- "name": "python3"
- },
- "language_info": {
- "name": "python"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 0
-}
\ No newline at end of file
diff --git a/History/Other than the latest in beta version/Image_generation_ver_Bete.ipynb b/History/Other than the latest in beta version/Image_generation_ver_Bete.ipynb
deleted file mode 100644
index ff63043..0000000
--- a/History/Other than the latest in beta version/Image_generation_ver_Bete.ipynb
+++ /dev/null
@@ -1,1126 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "view-in-github",
- "colab_type": "text"
- },
- "source": [
- ""
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "b-akwUYrMpEY"
- },
- "source": [
- ">補足\n",
- "\n",
- "下の方に画像の生成方法とパスのコピーの方法を画像で説明しています。わからない方はご覧ください。\n",
- "\n",
- "(The method for copying the path of an image is explained with images below. If you are unsure, please take a look.)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "OSUkVnrbrgWn"
- },
- "source": [
- ">お知らせ\n",
- "\n",
- "2023/07/19 時点でパラメーターの温度と雰囲気が反映されていないことに気づいたため、一時的に消しています。"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "C4UJqC_WpaGw",
- "outputId": "95f9557b-44d1-408e-8ee6-cee14b9f53a2"
- },
- "outputs": [
- {
- "output_type": "stream",
- "name": "stdout",
- "text": [
- "GoogleDrive: \u001b[33m接続なし\u001b[0m\n",
- "\u001b[32mセットアップが完了しました。必要に応じて '/content/入力するモデルファイル'に使いたいモデルファイルを入れてください\u001b[0m\n"
- ]
- }
- ],
- "source": [
- "#@title #🔽実行する時このような三角のボタンを押してください{run: \"auto\", display-mode: \"form\"}\n",
- "#@markdown #Step1.セットアップ (Setup)\n",
- "\n",
- "import locale #この2行は非常に重要\n",
- "locale.getpreferredencoding = lambda: \"UTF-8\"\n",
- "\n",
- "Google_driveに接続 = False # @param {type:\"boolean\"}\n",
- "#@markdown Googleドライブに保存したいときにチェックをしてください\n",
- "from google.colab import drive\n",
- "import google.colab.drive as drive\n",
- "if Google_driveに接続:\n",
- " Gdrive=\"GoogleDrive: \\033[32m接続成功\\033[0m\"\n",
- " try:\n",
- " drive.mount('/content/drive')\n",
- " except:\n",
- " Gdrive=\"GoogleDrive: \\033[31m接続失敗\\033[0m\"\n",
- "else:\n",
- " Gdrive=\"GoogleDrive: \\033[33m接続なし\\033[0m\"\n",
- " if drive._os.path.ismount('/content/drive'):\n",
- " drive.flush_and_unmount()\n",
- " print(\"GoogleDriveの接続を解除しました\")\n",
- "\n",
- "import os\n",
- "\n",
- "\n",
- "try:\n",
- " import torch\n",
- " import diffusers\n",
- " import transformers\n",
- " import accelerate\n",
- " import scipy\n",
- " import safetensors\n",
- " import ftfy\n",
- " import regex\n",
- " import tqdm\n",
- " import xformers\n",
- " import sentencepiece\n",
- " import pysbd\n",
- " import huggingface_hub\n",
- " import sacremoses\n",
- "\n",
- "except:\n",
- " try:\n",
- " !pip install torch==2.0.1+cu118 diffusers==0.16.1 transformers==4.29.2 accelerate==0.19.0 scipy==1.10.1 safetensors==0.3.1 ftfy==6.1.1 regex==2022.10.31 tqdm==4.65.0 scipy==1.10.1 sentencepiece==0.1.99 pysbd==0.3.4 xformers huggingface_hub sacremoses -q\n",
- " !git clone https://github.com/huggingface/diffusers.git\n",
- " import torch\n",
- " import diffusers\n",
- " import transformers\n",
- " import accelerate\n",
- " import scipy\n",
- " import safetensors\n",
- " import ftfy\n",
- " import regex\n",
- " import tqdm\n",
- " import xformers\n",
- " import sentencepiece\n",
- " import pysbd\n",
- " import huggingface_hub\n",
- " import sacremoses\n",
- "\n",
- " except:\n",
- " raise RuntimeError(\"ランタイムをGPUに変更お願いします。またはページの再読み込みをお願いします\")\n",
- "try:\n",
- " import clip\n",
- "except ModuleNotFoundError:\n",
- " !pip install git+https://github.com/openai/CLIP.git -q\n",
- " import clip\n",
- "diffusers_path = \"/content/diffusers\"\n",
- "if not os.path.exists(diffusers_path):\n",
- " !git clone https://github.com/huggingface/diffusers.git -q\n",
- "\n",
- "import requests\n",
- "import spacy\n",
- "import codecs\n",
- "import pickle\n",
- "import torch\n",
- "import random\n",
- "import numpy as np\n",
- "import transformers\n",
- "import sentencepiece\n",
- "import ipywidgets as widgets\n",
- "from PIL import Image\n",
- "import time, math\n",
- "from datetime import datetime\n",
- "from transformers import pipeline\n",
- "from transformers import GPT2Tokenizer, GPT2LMHeadModel, pipeline\n",
- "from torch import Generator, autocast\n",
- "from IPython.display import display, Markdown\n",
- "from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler\n",
- "from diffusers import EulerDiscreteScheduler, StableDiffusionImg2ImgPipeline\n",
- "from diffusers import DiffusionPipeline, AutoencoderKL, EulerAncestralDiscreteScheduler\n",
- "from diffusers import StableDiffusionImg2ImgPipeline\n",
- "from diffusers.models import AutoencoderKL\n",
- "from PIL import Image, PngImagePlugin\n",
- "from IPython.display import display\n",
- "from diffusers import DiffusionPipeline, EulerDiscreteScheduler, DPMSolverMultistepScheduler\n",
- "from google.colab import drive\n",
- "import google.colab.drive as drive\n",
- "m_dir = '/content/モデルフォルダ'\n",
- "if not os.path.exists(m_dir):\n",
- " os.makedirs(m_dir)\n",
- "def model_paths(m_dir):\n",
- " file_name = os.listdir(m_dir)[0] # フォルダ内の最初のファイル名を取得\n",
- " model_path=os.path.join(m_dir)\n",
- " return model_path\n",
- "\n",
- "from google.colab import drive\n",
- "import google.colab.drive as drive\n",
- "if Google_driveに接続:\n",
- " try:\n",
- " drive.mount('/content/drive')\n",
- " except:\n",
- " print(\"\\033[31mGoogleDriveへの接続に失敗しました\\033[0m\")\n",
- "else:\n",
- " if drive._os.path.ismount('/content/drive'):\n",
- " drive.flush_and_unmount()\n",
- " print(\"GoogleDriveの接続を解除しました\")\n",
- "\n",
- "if drive._os.path.ismount('/content/drive'):\n",
- " Connect_Gdrive=\"GoogleDrive: \\033[32m接続成功\\033[0m\"\n",
- "\n",
- "else:\n",
- " Connect_Gdrive=\"GoogleDrive: \\033[33m接続なし\\033[0m\"\n",
- "\n",
- "step1_finish=True\n",
- "\n",
- "print(Connect_Gdrive)\n",
- "print(\"\\033[32mセットアップが完了しました。必要に応じて '/content/入力するモデルファイル'に使いたいモデルファイルを入れてください\\033[0m\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "2_TXXMSVDc5h"
- },
- "outputs": [],
- "source": [
- "#@title #Step2.モードの選択 (Mode Selection){ run: \"auto\", display-mode: \"form\"}\n",
- "\n",
- "\n",
- "#\"\\033[31m先にStep.1を実行してください\\033[0m\"\n",
- "\n",
- "\n",
- "# @markdown >使用するモデルの切り替え (model change)\n",
- "\n",
- "model_select = \"Counterfeit-V2.5(Anime)(better)\" #@param [\"stable diffusion-v2.1(basic)\", \"Counterfeit-V2.5(Anime)(better)\", \"waifu diffusion-v1.4(Anime)\", \"Anything-v3.0(Anime)\", \"Anything-v4.5(Anime)\", \"anything-midjourney-v-4-1(Anime)\", \"ACertainThing(Anime)\", \"anime-kawai-diffusion(Anime)\", \"AB4.5_AC0.2(Anime)\", \"basil_mix(Anime)\", \"Counterfeit(Anime)\", \"Counterfeit-V2.0(Anime)\", \"Double-Exposure-Diffusion(Anime)\", \"EimisAnimeDiffusion_1.0v(Anime)\", \"7th_Layer(Anime)\", \"Riga_Collection(Anime)\", \"openjourney-v4(Reality)\", \"Realistic_Vision_V2.0(Reality)\", \"Custom\"]\n",
- "\n",
- "#削除モデル(使えないもの)\"epic-space-machine(space_ship)\",\"spacemidj(space)\",\"nasa_space_v2(space)\",\"loliDiffusion(Anime)\",\"chilled_remix(Anime)\"\n",
- "\n",
- "#@markdown Customモードは \"入力するモデルフォルダ\" に１つのモデルファイルを入れてください\n",
- "\n",
- "# @markdown >モードの切り替え (mode change)\n",
- "mode_select = \"Quick\" #@param [\"Nomal(better)\",\"Quick\"]\n",
- "\n",
- "#@markdown * \"Nomal\" 品質と生成時間のバランス重視です\n",
- "\n",
- "#@markdown * \"Quick\" 少し品質が低下する代わりに生成時間が大幅に短縮します\n",
- "\n",
- "\n",
- "入力形式 = \"text_only(better)\" #@param [\"text_only(better)\", \"image_and_text\"]\n",
- "\n",
- "# @markdown\n",
- "\n",
- "#text_generate_model= \"anime-anything-promptgen-v2\" #@param [\"MagicPrompt-Stable-Diffusion\",\"anime-anything-promptgen-v2\"]\n",
- "\n",
- "\n",
- "# @markdown\n",
- "\n",
- "# @markdown >フィルターを調整\n",
- "\n",
- "# @markdown **注意事項 : 変更する時は注意して下さい**\n",
- "\n",
- "Filter_off = False # @param {type:\"boolean\"}\n",
- "\n",
- "# @markdown 追記:人が映り込んだだけでフィルタリングされることがあったので追加しました\n",
- "\n",
- "\n",
- "if \"step1_finish\" not in locals() or not step1_finish:\n",
- " raise NameError(\"\\033[33m先にStep.1の実行をお願いします\\033[0m\")\n",
- "else:\n",
- " pass\n",
- "\n",
- "\n",
- "\n",
- "def print_text():\n",
- " if mode_select == \"Nomal(better)\":\n",
- " mode_text=\"mode: Nomal\\n\"\n",
- " else:\n",
- " mode_text=\"mode: Quick\\n\"\n",
- " return mode_text\n",
- "\n",
- "def print_format():\n",
- " if 入力形式 == \"text_only(better)\":\n",
- " word_format=\"入力形式: text_only\\n\"\n",
- " else:\n",
- " word_format=\"入力形式: image_and_text\\n\"\n",
- " return word_format\n",
- "\n",
- "mode_text=print_text()\n",
- "word_format=print_format()\n",
- "\n",
- "\n",
- "def result():\n",
- " if Filter_off == False:\n",
- " filter_level = \"フィルターの強度:通常\"\n",
- " else:\n",
- " filter_level = \"\\033[33mフィルターの強度:無効\\033[0m\"\n",
- " return filter_level\n",
- "\n",
- "def safe():\n",
- " if Filter_off ==False:\n",
- " safety_checker = \"\"\n",
- "\n",
- " else:\n",
- " safety_checker = None\n",
- " return safety_checker\n",
- "\n",
- "\n",
- "import requests\n",
- "import spacy\n",
- "import codecs\n",
- "import pickle\n",
- "import torch\n",
- "import random\n",
- "import numpy as np\n",
- "import transformers\n",
- "import sentencepiece\n",
- "import ipywidgets as widgets\n",
- "from diffusers import StableDiffusionPipeline\n",
- "from huggingface_hub import hf_hub_download\n",
- "from safetensors.torch import save_file\n",
- "from PIL import Image\n",
- "from datetime import datetime\n",
- "from transformers import pipeline\n",
- "from torch import Generator, autocast\n",
- "from IPython.display import display, Markdown\n",
- "from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler\n",
- "from diffusers import EulerDiscreteScheduler, StableDiffusionImg2ImgPipeline\n",
- "from diffusers import DiffusionPipeline, AutoencoderKL, EulerAncestralDiscreteScheduler, UNet2DConditionModel, PNDMScheduler\n",
- "from diffusers.models import AutoencoderKL\n",
- "from transformers import CLIPTextModel, CLIPTokenizer\n",
- "from transformers import AutoModel, AutoTokenizer\n",
- "\n",
- "\n",
- "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
- "#model, preprocess = clip.load(\"laion/CLIP-ViT-H-14-laion2B-s32B-b79K\", device=device)\n",
- "\n",
- "# 使用するモデルを設定\n",
- "if model_select ==\"Custom\":\n",
- " model_id=\"Custom\"\n",
- " model_name=\"Custom\"\n",
- " can_EN=False #念の為\n",
- "\n",
- "elif model_select == \"stable diffusion-v2.1(basic)\":\n",
- " model_id = \"stabilityai/stable-diffusion-2-1\"\n",
- " model_name = \"stable_diffusion-v2.1\"\n",
- " can_EN=False\n",
- "\n",
- "elif model_select == \"waifu diffusion-v1.4(Anime)\":\n",
- " model_id = \"hakurei/waifu-diffusion\"\n",
- " model_name = \"waifu_diffusion-v1.4\"\n",
- " can_EN=False\n",
- "\n",
- "elif model_select == \"Anything-v3.0(Anime)\":\n",
- " model_id = \"Linaqruf/anything-v3.0\"\n",
- " model_name = \"Anything-v3.0\"\n",
- " can_EN=True\n",
- "\n",
- "elif model_select == \"anything-midjourney-v-4-1(Anime)\":\n",
- " model_id = \"Joeythemonster/anything-midjourney-v-4-1\"\n",
- " model_name =\"anything-midjourney-v-4-1\"\n",
- " can_EN=True\n",
- "\n",
- "elif model_select == \"Anything-v4.5(Anime)\":\n",
- " model_id = \"shibal1/anything-v4.5-clone\"\n",
- " model_name = \"Anything-v4.5\"\n",
- " can_EN=False\n",
- " #Airic/Anything-V4.5\n",
- "\n",
- "\n",
- "#elif model_select == \"loliDiffusion(Anime)\":\n",
- "# model_id = \"JosefJilek/loliDiffusion\"\n",
- "# model_name = \"loliDiffusion\"\n",
- "\n",
- "elif model_select == \"AB4.5_AC0.2(Anime)\":\n",
- " model_id = \"aioe/AB4.5_AC0.2\"\n",
- " model_name = \"AB4.5_AC0.2\"\n",
- " can_EN=False\n",
- "\n",
- "elif model_select == \"basil_mix(Anime)\":\n",
- " model_id = \"nuigurumi/basil_mix\"\n",
- " model_name = \"basil_mix\"\n",
- " can_EN=True\n",
- "\n",
- "\n",
- "elif model_select == \"Double-Exposure-Diffusion(Anime)\":\n",
- " model_id = \"joachimsallstrom/Double-Exposure-Diffusion\"\n",
- " model_name = \"Double-Exposure-Diffusion\"\n",
- " can_EN=True\n",
- "\n",
- "elif model_select == \"openjourney-v4(Reality)\":\n",
- " model_id = \"prompthero/openjourney-v4\"\n",
- " model_name= \"openjourney-v4\"\n",
- " can_EN=True\n",
- "\n",
- "\n",
- "elif model_select == \"ACertainThing(Anime)\":\n",
- " model_id =\"JosephusCheung/ACertainThing\"\n",
- " model_name=\"ACertainThing\"\n",
- " can_EN=True\n",
- "\n",
- "elif model_select == \"Counterfeit-V2.0(Anime)\":\n",
- " model_id = \"gsdf/Counterfeit-V2.0\"\n",
- " model_name= \"Counterfeit-V2.0\"\n",
- " can_EN=True\n",
- "\n",
- "\n",
- "elif model_select == \"Counterfeit-V2.5(Anime)(better)\":\n",
- " model_id = \"gsdf/Counterfeit-V2.5\"\n",
- " model_name =\"Counterfeit-V2.5\"\n",
- " can_EN=True\n",
- "\n",
- "elif model_select == \"7th_Layer(Anime)\":\n",
- " model_id = \"syaimu/7th_test\"\n",
- " model_name = \"7th_Layer\"\n",
- " can_EN=True\n",
- "\n",
- "\n",
- "elif model_select == \"EimisAnimeDiffusion_1.0v(Anime)\":\n",
- " model_id = \"eimiss/EimisAnimeDiffusion_1.0v\"\n",
- " model_name = \"EimisAnimeDiffusion_1.0v\"\n",
- " can_EN=True\n",
- "\n",
- "\n",
- "elif model_select==\"Riga_Collection(Anime)\":\n",
- " mdoel_id =\"natsusakiyomi/Riga_Collection\"\n",
- " model_name=\"Riga_Collection\"\n",
- " can_EN=True\n",
- "\n",
- "\n",
- "# モードの切り替え (mode change)\n",
- "elif model_select ==\"anime-kawai-diffusion(Anime)\":\n",
- " model_id=\"Ojimi/anime-kawai-diffusion\"\n",
- " model_name=\"anime-kawai-diffusion\"\n",
- " can_EN=True\n",
- "\n",
- "elif model_select == \"anything-midjourney-v-4-1(Anime)\":\n",
- " model_id = \"Joeythemonster/anything-midjourney-v-4-1\"\n",
- " model_name =\"anything-midjourney-v-4-1\"\n",
- " can_EN=True\n",
- "\n",
- "\n",
- "elif model_select==\"Realistic_Vision_V2.0(Reality)\":\n",
- " model_id=\"SG161222/Realistic_Vision_V2.0\"\n",
- " model_name=\"Realistic_Vision_V2.0\"\n",
- " can_EN=True\n",
- "\n",
- "#入れられないけど Deyo/SEmix\n",
- "\n",
- "\n",
- "def pipe_setup():\n",
- " if not model_id==\"Custom\":\n",
- " #vae = AutoencoderKL.from_pretrained(\"stabilityai/sd-vae-ft-mse\")\n",
- " if 入力形式 == \"text_only(better)\":\n",
- " if Filter_off==True:\n",
- " # StableDiffusion(メインのモジュール)パイプライン設定\n",
- " # もしも何かあったら\"torch_dtype=torch.float16\"をつける\n",
- " pipe = StableDiffusionPipeline.from_pretrained(\n",
- " model_id, torch_dtype=torch.float16 if mode_select == \"Quick\" else torch.float32,\n",
- " safety_checker= None,\n",
- " use_safetensors=True,\n",
- " #tokenizer=text_tokenizer,\n",
- " #text_encoder=text_encoder,\n",
- "\n",
- " #vae=vae\n",
- " )\n",
- " pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)\n",
- "\n",
- " else:\n",
- " pipe = DiffusionPipeline.from_pretrained(\n",
- " model_id, torch_dtype=torch.float16 if mode_select == \"Quick\" else torch.float32,\n",
- " #use_safetensors=True,\n",
- " #tokenizer=text_tokenizer,\n",
- " #text_encoder=text_encoder\n",
- " #vae=vae\n",
- " )\n",
- " pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)\n",
- " else:\n",
- " if Filter_off==True:\n",
- " pipe = StableDiffusionImg2ImgPipeline.from_pretrained(\n",
- " model_id, torch_dtype=torch.float16 if mode_select == \"Quick\" else torch.float32,\n",
- " safety_checker= None,\n",
- " use_safetensors=True,\n",
- " #tokenizer=tokenizer,\n",
- " #text_encoder=text_encoder,\n",
- " #vae=vae\n",
- " )\n",
- " pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)\n",
- " else:\n",
- " pipe = StableDiffusionImg2ImgPipeline.from_pretrained(\n",
- " model_id, torch_dtype=torch.float16 if mode_select == \"Quick\" else torch.float32,\n",
- " use_safetensors=True,\n",
- " #tokenizer=tokenizer,\n",
- " #text_encoder=text_encoder,\n",
- " #vae=vae\n",
- " )\n",
- " pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)\n",
- " else:\n",
- " try:\n",
- " model_path=model_paths(m_dir,file_name)\n",
- " pipe = StableDiffusionPipeline.from_ckpt(model_path)\n",
- " except:\n",
- " raise FileNotFoundError(\"'入力するモデルファイル'からモデルを読み込めませんでした。モデルファイルが存在しないか対応していない形式の可能性があります\")\n",
- " pipe = pipe.to(device)\n",
- " return pipe\n",
- "\n",
- "\n",
- "#def ima3ima(modl_id):\n",
- " # model_T=\"stable_diffusion_txt2img\"+model_id\n",
- " #return model_T\n",
- "#ima3ima(model_id)\n",
- "# txt2img モードで Pipeline オブジェクトを作成\n",
- "#model_T = StableDiffusionPipeline.from_pretrained(model_id)\n",
- "\n",
- "# generate text using fine-tuned model\n",
- "#nlp = pipeline('text-generation', model=text_model_name)\n",
- "\n",
- "pipe=pipe_setup()\n",
- "EN=\"埋め込み: 有効\\n有効化の鍵: 'EasyNegative' , 'bat_hands'\"\n",
- "if can_EN:\n",
- " try:\n",
- " pipe.load_textual_inversion(\n",
- " \"sayakpaul/EasyNegative-test\", weight_name=\"EasyNegative.safetensors\", token=\"EasyNegative\"\n",
- " )\n",
- " pipe.load_textual_inversion(\n",
- " \"yesyeahvh/bad-hands-5\", weight_name=\"bad-hands-5.pt\", token=\"bad-hands\"\n",
- " )\n",
- "\n",
- " except:\n",
- " print(\"\\033[31m埋め込みのロードに失敗しました。\\033[0m\")\n",
- " EN=\"埋め込み: このモデルでは使用不可です\"\n",
- "else:\n",
- " EN=\"\\033[33m埋め込み: このモデルでは使用不可です\\033[0m\"\n",
- "\n",
- "filter_level=result()\n",
- "\n",
- "\n",
- "#\\033[31mが赤、\\033[33mが黄色、\\033[34mが青、\\033[32mが緑、\\033[0mが白\n",
- "# \"\\033[32m\" は緑色に変更するための\"ANSI Escape Code\"であり、\"\\033[0m\"はデフォルトの文字色に戻すためのコードです。\n",
- "MS=\"____________________________________________________________________________\"\n",
- "Finish1=\"\\033[32m画像生成の準備が出来たので、手順3に移ってください。\\033[0m\"\n",
- "Finish2=\"\\033[32m(Now that the image generation is ready, please proceed to step 3.)\\033[0m\"\n",
- "status=(f\"\\n\\033[34m{MS}\\n\\nmodel_name: {model_name}\\n\\n{mode_text}\\n{word_format}\\n{EN}\\n\\n{filter_level}\\n\\n{Finish1}\\033[0m\")\n",
- "print(status)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "xXSW3nl8UT7x"
- },
- "outputs": [],
- "source": [
- "#@title #Step3.画像の生成 (iamge generation){display-mode: \"form\"}\n",
- "\n",
- "#@markdown #自動生成\n",
- "\n",
- "自動で条件を決めて生成 = False #@param {type:\"boolean\"}\n",
- "\n",
- "#@markdown **操作がよくわからない方はチェックをつけて下さい。自動で生成します**\n",
- "\n",
- "#@markdown >この機能の詳細\n",
- "#@markdown * 詳細設定を推奨の値に設定\n",
- "#@markdown * プロンプトが入力されていない場合、初期値として \"1girl\" / \"1woman\" のいずれかを入力\n",
- "\n",
- "#@markdown >次の機能をオンにします\n",
- "#@markdown * 画面に表示\n",
- "#@markdown * 画像の質を上げるプロントを追加する\n",
- "#@markdown * プロンプトアシストを使う ( MagicPrompt )\n",
- "#@markdown * 推奨するネガティブプロントを使用\n",
- "#@markdown * 条件をメタデーターとして追加する\n",
- "\n",
- "\n",
- "#@markdown\n",
- "\n",
- "#@markdown -----\n",
- "\n",
- "# @markdown >生成したい枚数を入力してください / Please enter the number of images you want to generate here.\n",
- "生成する枚数 = 30 #@param {type:\"slider\", min:1, max:100, step:1}\n",
- "枚数制限なし = False #@param {type:\"boolean\"}\n",
- "#if 生成する枚数 <= 0 or isinstance(生成する枚数, float):\n",
- " # print(\"\\033[31m警告:無効な数字が入力された為デフォルトの1枚に設定しました\\033[0m\")\n",
- " # 生成する枚数 = 1\n",
- "#if 生成する枚数 is None:\n",
- " # print(\"\\033[31m警告:無効な形式な為デフォルトの1枚に設定しました\\033[0m\")\n",
- "# 生成する枚数 = 1\n",
- "\n",
- "# @markdown デフォルトでは1回につき1枚生成します。(By default, one image will be generated per run.)\n",
- "\n",
- "# @markdown ------\n",
- "\n",
- "# @markdown >生成する画像の条件を**英語で**入力してください (Please input the conditions for generating images in **English**.)\n",
- "\n",
- "Prompt = \"Please draw a beautiful Mount Fuji with the sun rising from the summit\" #@param {type:\"string\"}\n",
- "画像の質を上げるプロントを追加する = True #@param {type:\"boolean\"}\n",
- "#プロンプトアシストを使う = True #@param {type:\"boolean\"}\n",
- "日本語入力 = False #@param {type:\"boolean\"}\n",
- "\n",
- "\n",
- "# @markdown >**プロンプトの例**\n",
- "# @markdown * cute, cat\n",
- "# @markdown * Earth, space, high resolution\n",
- "# @markdown * Please draw a beautiful Mount Fuji with the sun rising from the summit\n",
- "# @markdown * smail,1girl, white hair, medium hair, cat ears, looking at viewer, :3, cute,white_dress\n",
- "\n",
- "\n",
- "# @markdown ------\n",
- "# @markdown >プロンプトアシスタントの選択\n",
- "text_generate_model= \"anime-anything-promptgen-v2\" #@param [\"None\",\"MagicPrompt-Stable-Diffusion\",\"anime-anything-promptgen-v2\"]\n",
- "\n",
- "# @markdown アニメ調の画像に適したアシスタントは \" anime-anything-promptgen-v2 \"\n",
- "\n",
- "# @markdown 多目的のアシスタントは \" MagicPrompt-Stable-Diffusion \"\n",
- "\n",
- "# @markdown 使用しない場合は \" None \" の選択をお願いします\n",
- "\n",
- "条件を統一する = False #@param {type:\"boolean\"}\n",
- "\n",
- "#@markdown 最初の画像のプロンプトを繰り返し使用します\n",
- "\n",
- "# @markdown ------\n",
- "\n",
- "# @markdown >画像を入力として送リます。\n",
- "\n",
- "入力する画像 = \"\" #@param {type:\"string\"}\n",
- "# @markdown 入力形式を \"image_and_text\" とした場合のみに使えます\n",
- "\n",
- "\n",
- "# @markdown ------\n",
- "\n",
- "#@markdown #詳細設定\n",
- "\n",
- "seed = None #@param {type:\"number\"}\n",
- "guidance_scale = 11 #@param {type:\"slider\", min:1, max:30, step:1}\n",
- "#温度 = 0.7 #@param {type:\"slider\", min:0, max:1, step:0.1}\n",
- "#top_k = 17 #@param {type:\"slider\", min:1, max:40, step:1}\n",
- "#top_p = 0 #@param {type:\"slider\", min:0, max:1, step:0.01}\n",
- "#雰囲気 = 0.9 #@param {type:\"slider\", min:0.1, max:1, step:0.1}\n",
- "拡散ステップ = 50 # @param {type:\"number\"}\n",
- "#safe_level = \"safe\" #@param [\"safe\", \"Questionable\", \"Explicit\"]\n",
- "縦の大きさ = \"480\" #@param [\"480\",\"512\",\"600\", \"768\",\"800\", \"1080\",\"1152\", \"1440\", \"1920\", \"3840\", \"7680\"]\n",
- "横の大きさ = \"480\" #@param [\"480\",\"512\",\"600\", \"768\",\"800\", \"1080\",\"1152\", \"1440\", \"1920\", \"3840\", \"7680\"]\n",
- "\n",
- "\n",
- "height = int(縦の大きさ)\n",
- "width = int(横の大きさ)\n",
- "\n",
- "#@markdown >用語の説明\n",
- "\n",
- "#@markdown * seed (\"0\"以上) / seed値を指定します。指定しない場合ランダムな数字を割り当てます。\n",
- "\n",
- "#@markdown * guidance_scale (5≦30 推奨\"8\") / どのくらい細かく描くかを指定します。\n",
- "\n",
- "##@markdown * 温度(0.1≦1.0 推奨\"0.8\") / どのくらい条件に合わせるかを指定します。\n",
- "\n",
- "#@markdown * 拡散ステップ(1≦1000 推奨\"50\") / 計算をする回数を指定します。回数を減らすほど生成速度が速くなります\n",
- "\n",
- "#@markdown * 縦・横の大きさ ( 推奨\"512\" ) / 画像の大きさを指定します。大きくすればするほど生成速度が遅くなります\n",
- "\n",
- "# @markdown ------\n",
- "\n",
- "# @markdown >必要であればネガティブプロンプトを入力してください。人物を生成するときにおすすめです\n",
- "\n",
- "# @markdown よくわからない方ボタンを押してください。おすすめのネガティブプロントを使います\n",
- "\n",
- "## @markdown (If necessary, please enter a negative prompt. It is recommended for generating characters.)\n",
- "\n",
- "N_prompt = \"\" # @param {type:\"string\"}\n",
- "推奨するネガティブプロントを使用 = False #@param {type:\"boolean\"}\n",
- "# @markdown ネガティブプロンプトとは、**ネガティブな要素を除く**ものです。\n",
- "\n",
- "## @markdown (Negative prompts are used to exclude negative elements from an image. For example, you can use a negative prompt to exclude low quality images or images that are not beautiful.)\n",
- "\n",
- "# @markdown ------\n",
- "\n",
- "#@markdown >保存する先を指定します\n",
- "\n",
- "## @markdown (If you would like to specify a location to save the generated image, please enter the path.)\n",
- "\n",
- "保存する先のパス = \"\" # @param {type:\"string\"}\n",
- "#@markdown デフォルトでは /content/Generated_images に保存されます。なければ作るようになっています。\n",
- "\n",
- "##@markdown (If no path is specified, the images will be saved to \"/content/生成した画像\". The directory will be created if it doesn't exist.)\n",
- "\n",
- "# @markdown\n",
- "\n",
- "\n",
- "## @markdown (P.S.You can see the images generated at '/content/生成した画像' by clicking the file icon in the left taskbar.)\n",
- "\n",
- "# @markdown ------\n",
- "\n",
- "# @markdown >生成した画像を画面に表示します\n",
- "\n",
- "画面に表示 = True # @param {type:\"boolean\"}\n",
- "プロンプトを表示 = True # @param {type:\"boolean\"}\n",
- "条件をメタデーターとして追加する = False # @param {type:\"boolean\"}\n",
- "\n",
- "\n",
- "if \"pipe\" not in locals() or not pipe:\n",
- " raise NameError(\"\\033[33mパイプラインが見つかりませんでした。Step.2を再度実行してください\\033[0m\")\n",
- "\n",
- "if \"can_EN\" not in locals() or not can_EN:\n",
- " can_EN = False\n",
- "\n",
- "if 入力形式==\"image_and_text\":\n",
- " try:\n",
- " init_image = Image.open(入力する画像)\n",
- " init_image = init_image.convert(\"RGB\")\n",
- " init_image = init_image.resize((512, 512))\n",
- " except:\n",
- " raise FileNotFoundError('入力する画像が見つかりませんでした。画像を入力しない場合は、Step.1の入力形式を\"text_only\"に変更お願いします')\n",
- "\n",
- "if 自動で条件を決めて生成 and text_generate_model == \"None\":\n",
- " auto_text=True\n",
- "else:\n",
- " auto_text=False\n",
- "\n",
- "if 画像の質を上げるプロントを追加する or 自動で条件を決めて生成:\n",
- " mini_prompt=True\n",
- "else:\n",
- " mini_prompt=False\n",
- "if text_generate_model == \"None\" and auto_text==False:\n",
- " text_model_name=\"\"\n",
- "elif text_generate_model == \"MagicPrompt-Stable-Diffusion\" or auto_text:\n",
- " text_model_name = \"Gustavosta/MagicPrompt-Stable-Diffusion\"\n",
- " if \"MagicPrompt\" not in locals() or not MagicPrompt:\n",
- " MagicPrompt = pipeline('text-generation', model=text_model_name , do_sample=True , top_k=4 , temperature=0.7)\n",
- "elif text_generate_model == \"anime-anything-promptgen-v2\":\n",
- " text_model_name = \"FredZhang7/anime-anything-promptgen-v2\"\n",
- " if \"AnythingPrompt\" not in locals() or not AnythingPrompt:\n",
- " AnythingPrompt = pipeline('text-generation', model=text_model_name , do_sample=True , top_k=4 , temperature=0.7)\n",
- "\n",
- "else:\n",
- " print(\"\\033[33m申し訳ありません。想定以外の処理が実行されてしまったため、アシスタントをオフはオフになりました\\033[0m\")\n",
- "#early_stopping=True を削除\n",
- "\n",
- "def word_preprocessing(Prompt):\n",
- " if not Prompt==\"\":\n",
- " if 日本語入力:\n",
- " texts = Prompt\n",
- " encoded_text = codecs.encode(texts, 'utf-8')\n",
- " decoded_text = codecs.decode(encoded_text, 'utf-8')\n",
- " pos_tagger = spacy.load('en_core_web_sm')\n",
- " fugu_translator = pipeline('translation', model='staka/fugumt-ja-en')\n",
- " translation = fugu_translator(decoded_text, src_lang=\"ja\", tgt_lang=\"en\")[0][\"translation_text\"]\n",
- " Prompt_2 = translation #After_Prompt\n",
- " else:\n",
- " Prompt_2 = Prompt\n",
- " else:\n",
- " add_word=random.choice([\"1girl\", \"1woman\"])\n",
- " Prompt_2=add_word\n",
- " print(f\"プロンプトが未入力の為'{add_word}'を入力しました\")\n",
- " return Prompt_2\n",
- "\n",
- "def easy_prompt(Prompt_2,text_model_name):\n",
- " 追加 = \"masterpiece:2.0,best quality,high quality,\"\n",
- " if text_generate_model == \"None\":\n",
- " Prompt_4 = Prompt_2\n",
- " #elif プロンプトアシストを使う or 自動で条件を決めて生成:\n",
- " elif text_generate_model == \"MagicPrompt-Stable-Diffusion\" or 自動で条件を決めて生成:\n",
- " if mini_prompt==True:\n",
- " Prompt_4_P = MagicPrompt(Prompt_2, max_length=27, do_sample=True , top_k=4 , temperature=0.7)[0][\"generated_text\"]\n",
- " Prompt_4=追加+Prompt_4_P\n",
- " else:\n",
- " Prompt_4 = MagicPrompt(Prompt_2, max_length=73, do_sample=True , top_k=4 , temperature=0.7)[0][\"generated_text\"]\n",
- "\n",
- " elif text_generate_model == \"anime-anything-promptgen-v2\":\n",
- " if mini_prompt==True:\n",
- " Prompt_4_P = AnythingPrompt(Prompt_2, max_length=27, do_sample=True , top_k=4 , temperature=0.7)[0][\"generated_text\"]\n",
- " Prompt_4=追加+Prompt_4_P\n",
- " else:\n",
- " Prompt_4 = AnythingPrompt(Prompt_2, max_length=73, do_sample=True , top_k=4 , temperature=0.7)[0][\"generated_text\"]\n",
- " else:\n",
- " Prompt_4 = Prompt_2\n",
- " return Prompt_4\n",
- "\n",
- "\n",
- "def main_task():\n",
- " Prompt_2=word_preprocessing(Prompt)\n",
- " Prompt_4=easy_prompt(Prompt_2,text_model_name)\n",
- " #prompt=Prompt_4\n",
- " return Prompt_4\n",
- "\n",
- "Prompt_4 = main_task()\n",
- "\n",
- "\n",
- "if seed is None:\n",
- " seed = random.randint(1,1000000)\n",
- "\n",
- "\n",
- "\n",
- "if 推奨するネガティブプロントを使用 or 自動で条件を決めて生成 :\n",
- " if can_EN:\n",
- " おすすめのネガティブプロント = \",EasyNegative , bat_hands,Loss of eye highlights:1.5,Fingers fused together:1.3,Writing Sweet Fingers:2.0,bad hands:2.0,bad legs:2.0,worst quality:2.0, low quality:2.0,Not five fingers.:2.0,blurred,Missing finger:1.7,Cat with deformed face:1.3 ,medium quality, purple hair,Loss of eye highlights:1.5,Fingers fused together:1.3,Writing Sweet Fingers:2.0 ,deleted:0.5, lowres,Low quality animals, deformed animals ,hands emerging from impossible places:1.7, bad anatomy, more than three limbs hands/legs:1.5, low resolution, blurry, absurdres,pixelated, sketchy, nonsensical anatomy, unrealistic pose, mosaic, unclear details, distorted colors, unrealistic proportions, poor quality, fuzzy, missing head:1.6, out of focus, hazy, grainy, text, error, missing fingers:0.9, extra digit, fewer digits, cropped, jpeg artifacts, signature, watermark, username, standard quality, bad feet_hand_finger_leg_eye, bad, text font ui, bad shadow, poorly drawn, black-white, ugly, duplicate, mutation, mutilated, malformed mutated:1.1, malformed:1.1, The background is incoherent, simple background, low-quality background, low background, bad body, long body, broken limb, anatomical nonsense, extra limbs, missing limb, incorrect limb, multiple heads, twisted head, poorly drawn face, 1 unit with multiple heads:1.3, heads together:1.0, abnormal eye:1.2 proportion, cropped:1.0, bad eyes, fused eyes, poorly drawn eyes, bad mouth, poorly drawn mouth, bad tongue, too long tongue, bad ears, poorly drawn ears, extra ears, heavy ears, long neck, too thick neck, bad neck, bad breasts, missing arms, disappearing arms, extra arms, three arms:2.0, mutated hands and fingers, fused hand, missing fingers, extra digits, huge thighs, disappearing thigh, missing thighs, extra thighs, bad feet, huge calf, disappearing legs, bad gloves, fused gloves, beard, artist name, text watermark, unnatural, obviously wrong, distorted face, floating hair, floating body parts, severed body parts, incorrect leg position, deformed, fused body and hands, disregard of physics, distorted shape, doll-like object not present in the image, body fusion, abnormal fingers, fingers resembling fish fins, dot eyes, unclear background, mosaic, body bending, incorrect leg-to-torso ratio, excessively large breasts, unsettling appearance, eyes filled with solid color, lack of lower body, splitting, creepy doll-like appearance, distorted eyes, lines on the skin, legs bending in unnatural directions, abnormal finger count, missing arms, floating hands, lack of nose or mouth,, incorrect body part ratios, bad, longbody, lowres, bad anatomy, bad hands, missing fingers, Distorted eye contour, Missing part from the ankles onward, extra digit, fewer digits, split wings, Vampire wings floating in the air, bad wing, comic\"\n",
- " else:\n",
- " おすすめのネガティブプロント = \",Loss of eye highlights:1.5,Fingers fused together:1.3,Writing Sweet Fingers:2.0,bad hands:2.0,bad legs:2.0,worst quality:2.0, low quality:2.0,Not five fingers:2.0,blurred,Missing finger:1.7,Cat with deformed face:1.3 ,medium quality, purple hair,Loss of eye highlights:1.5,Fingers fused together:1.3,Writing Sweet Fingers:2.0 ,deleted:0.5, lowres,Low quality animals, deformed animals ,hands emerging from impossible places:1.7, bad anatomy, more than three limbs hands/legs:1.5, low resolution, blurry, absurdres,pixelated, sketchy, nonsensical anatomy, unrealistic pose, mosaic, unclear details, distorted colors, unrealistic proportions, poor quality, fuzzy, missing head:1.6, out of focus, hazy, grainy, text, error, missing fingers:0.9, extra digit, fewer digits, cropped, jpeg artifacts, signature, watermark, username, standard quality, bad feet_hand_finger_leg_eye, bad, text font ui, bad shadow, poorly drawn, black-white, ugly, duplicate, mutation, mutilated, malformed mutated:1.1, malformed:1.1, The background is incoherent, simple background, low-quality background, low background, bad body, long body, broken limb, anatomical nonsense, extra limbs, missing limb, incorrect limb, multiple heads, twisted head, poorly drawn face, 1 unit with multiple heads:1.3, heads together:1.0, abnormal eye:1.2 proportion, cropped:1.0, bad eyes, fused eyes, poorly drawn eyes, bad mouth, poorly drawn mouth, bad tongue, too long tongue, bad ears, poorly drawn ears, extra ears, heavy ears, long neck, too thick neck, bad neck, bad breasts, missing arms, disappearing arms, extra arms, three arms:2.0, mutated hands and fingers, fused hand, missing fingers, extra digits, huge thighs, disappearing thigh, missing thighs, extra thighs, bad feet, huge calf, disappearing legs, bad gloves, fused gloves, beard, artist name, text watermark, unnatural, obviously wrong, distorted face, floating hair, floating body parts, severed body parts, incorrect leg position, deformed, fused body and hands, disregard of physics, distorted shape, doll-like object not present in the image, body fusion, abnormal fingers, fingers resembling fish fins, dot eyes, unclear background, mosaic, body bending, incorrect leg-to-torso ratio, excessively large breasts, unsettling appearance, eyes filled with solid color, lack of lower body, splitting, creepy doll-like appearance, distorted eyes, lines on the skin, legs bending in unnatural directions, abnormal finger count, missing arms, floating hands, lack of nose or mouth,, incorrect body part ratios, bad, longbody, lowres, bad anatomy, bad hands, missing fingers, Distorted eye contour, Missing part from the ankles onward, extra digit, fewer digits, split wings, Vampire wings floating in the air, bad wing, comic\"\n",
- "else:\n",
- " おすすめのネガティブプロント =\"\"\n",
- "\n",
- "\n",
- "negative_prompt2 = N_prompt + おすすめのネガティブプロント\n",
- "\n",
- "if 枚数制限なし:\n",
- " 生成する枚数=100000\n",
- "st=生成する枚数\n",
- "\n",
- "\n",
- "GE_images_dir=\"/tmp/generated_images\"\n",
- "if not os.path.exists(GE_images_dir):\n",
- " os.makedirs(GE_images_dir)\n",
- "\n",
- "\n",
- "if 保存する先のパス:\n",
- " if not Google_driveに接続:\n",
- " if \"/content/drive/MyDrive\" in 保存する先のパス:\n",
- " image_save_path=\"/content/生成した画像\"\n",
- " print(\"\\033[31mGoogleドライブに接続されていないためデフォルトのパスに保存しました\\033[0m\")\n",
- " else:\n",
- " image_save_path=保存する先のパス\n",
- " else:\n",
- " image_save_path=保存する先のパス\n",
- "else:\n",
- " image_save_path=\"/content/Generated_images\"\n",
- "if not os.path.exists(image_save_path):\n",
- " os.makedirs(image_save_path)\n",
- "\n",
- "generator = torch.Generator(device).manual_seed(seed)\n",
- "\n",
- "sd_step=拡散ステップ\n",
- "\n",
- "\n",
- "def generate_images(st,Prompt_4,generator,image_save_path,sd_step,seed,model_name):\n",
- " i=1\n",
- " generate_time_all=0\n",
- " for i in range(生成する枚数):\n",
- " generate_start_time = time.time()\n",
- " j=i+1\n",
- " now = datetime.now()\n",
- " date_str = now.strftime(\"%Y-%m-%d_UTC-%H:%M:%S\")\n",
- " filenames = f\"seed({seed})_model({model_name})_guidance_scale({guidance_scale})_{date_str}.png\"\n",
- " path = os.path.join(image_save_path, filenames)\n",
- " GE_images_path = os.path.join(GE_images_dir, filenames)\n",
- " if not 条件を統一する:\n",
- " if i >= 1:\n",
- " Prompt_4 = main_task()\n",
- " if 入力形式 == \"image_and_text\":\n",
- " with autocast(\"cuda\"):\n",
- " result = pipe(Prompt_4, image=init_image, negative_prompt=negative_prompt2, num_inference_steps=sd_step,guidance_scale=guidance_scale,generator=generator)\n",
- " make_image = result.images[0]\n",
- " else:\n",
- " with autocast(\"cuda\"):\n",
- " result = pipe(Prompt_4, negative_prompt=negative_prompt2, guidance_scale=guidance_scale, num_inference_steps=sd_step,height=height,width=width,generator=generator)\n",
- " make_image = result.images[0]\n",
- " info = make_image.info\n",
- " if 条件をメタデーターとして追加する or 自動で条件を決めて生成:\n",
- " metadata = {\n",
- " \"Seed\": seed,\n",
- " \"model\": model_name,\n",
- " \"G_scale\":guidance_scale,\n",
- " \"D_step\":sd_step,\n",
- " \"Prompt\": Prompt_4,\n",
- " \"n_prompt\":negative_prompt2\n",
- " }\n",
- " pnginfo = PngImagePlugin.PngInfo()\n",
- " for key, value in metadata.items():\n",
- " pnginfo.add_text(key, str(value))\n",
- " make_image.save(path, pnginfo=pnginfo)\n",
- " else:\n",
- " make_image.save(path)\n",
- " generate_end_time = time.time()\n",
- " generate_time = generate_end_time - generate_start_time\n",
- " generate_time_all += generate_time\n",
- " generate_time_after=(\"{:.2f}s\".format(generate_time))\n",
- " generate_start_time= \"\"\n",
- " generate_end_time=\"\"\n",
- " if 枚数制限なし:\n",
- " print(f\"\\033[34m画像生成が完了しました ({j}/∞) {generate_time_after}\")\n",
- " else:\n",
- " print(f\"\\033[34m画像生成が完了しました ({j}/{st}) {generate_time_after}\")\n",
- " print(f\"ファイルの名前:( \\033[32m{filenames}\\033[34m )\")\n",
- " print(f\"保存先のパス:( \\033[32m{path}\\033[34m )\")\n",
- " print('メタデータをご覧になる場合は、「保存先のパス」をコピー＆ペーストしてください')\n",
- " print(\"上記のようになります。ご確認ください\\033[0m\")\n",
- " if 画面に表示 or 自動で条件を決めて生成:\n",
- " img = Image.open(path)\n",
- " display(img)\n",
- " if プロンプトを表示:\n",
- " print('\\033[92mプロンプト: ' + Prompt_4 + '\\033[0m\\n') # \"\\033[38;2;135;206;235m\" はスカイブルー \"\\033[38;2;255;165;0m\"はオレンジ\n",
- " generate_time_all_after=generate_time_all//生成する枚数\n",
- " print(\"\\033[38;2;135;206;235m1枚あたりの生成時間の平均: {:.2f}s\\033[0m\".format(generate_time_all_after))\n",
- "generate_images(st,Prompt_4,generator,image_save_path,sd_step,seed,model_name)\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "FxGYicFhvS6Y"
- },
- "outputs": [],
- "source": [
- "#@title 画像のメタデータを見る {display-mode: \"form\"}\n",
- "from PIL import Image, PngImagePlugin\n",
- "import os\n",
- "image_metadata_path = \"\" #@param {type:\"string\"}\n",
- "if not os.path.exists(image_metadata_path):\n",
- " raise FileNotFoundError(\"ファイルが見つかりませんでした\")\n",
- "try:\n",
- " output_info = Image.open(image_metadata_path).info\n",
- "except:\n",
- " raise FileNotFoundError(\"画像を読み込めませんでした\")\n",
- "\n",
- "try:\n",
- " print(\"seed: \"+output_info[\"Seed\"]+\"\\n\")\n",
- " print(\"diffusion_step: \"+output_info[\"D_step\"]+\"\\n\")\n",
- " print(\"guidance_scale: \"+output_info[\"G_scale\"]+\"\\n\")\n",
- " print(\"model_name : \"+output_info[\"model\"]+\"\\n\")\n",
- " print(\"prompt: \\033[92m\"+output_info[\"Prompt\"]+\"\\033[0m\\n\")\n",
- "except:\n",
- " print(\"\\033[31mメタデーターが見つかりませんでした\\033[0m\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "uPxapx46KtcH"
- },
- "outputs": [],
- "source": [
- "#@title {display-mode: \"form\"}\n",
- "#@markdown >zip形式にしてダウンロードします。\n",
- "#@markdown ダウンロード対象のフォルダ: /content/Generated_images\n",
- "from google.colab import files\n",
- "import shutil\n",
- "import os\n",
- "\n",
- "try:\n",
- " zip_number=zip_number+1\n",
- "except:\n",
- " zip_number=1\n",
- "base_save_dir=\"/content/Generated_images\"\n",
- "zip_name=f\"Generated_images-No.{zip_number}\"\n",
- "zip_save_dir=os.path.join(\"/content\",zip_name)\n",
- "zippath=zip_save_dir+\".zip\"\n",
- "try:\n",
- " shutil.make_archive(zip_save_dir, \"zip\", base_save_dir)\n",
- " files.download(zippath)\n",
- " print(\"\\033[32mzipファイルへ圧縮が正常に完了しました\")\n",
- " print(f'zipファイル名前は\\033[34m\"{zip_name}\"\\033[32mですご確認ください\\033[0m')\n",
- "except:\n",
- " print(\"\\033[31m生成した画像が見つかりませんでした\\033[0m\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "tPjosOVDWYII"
- },
- "outputs": [],
- "source": [
- "#@title {display-mode: \"form\"}\n",
- "ランタイムを一時的に切断する = False #@param {type: 'boolean'}\n",
- "#@markdown 作業を中断するときなどにチェックをつけて実行してください /Please check and execute when interrupting the task.\n",
- "if ランタイムを一時的に切断する == True:\n",
- " from google.colab import runtime\n",
- " runtime.unassign()\n",
- "else:\n",
- " print('ランタイムの切断をキャンセルしました')"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "_20K18NBcgLL"
- },
- "source": [
- "# **Image generation methods**\n",
- "\n",
- "\n",
- "\n",
- ""
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "qnoU8WBIgR4j"
- },
- "source": [
- "# **How to copy the path of an image**\n",
- "\n",
- " **Please modify the steps as needed**\n",
- "\n",
- "> Step.1\n",
- "\n",
- "\n",
- "\n",
- "> Step.2\n",
- "\n",
- "\n",
- "\n",
- "\n",
- "\n",
- "\n",
- "> Step.3\n",
- "\n",
- "\n",
- "\n",
- "\n",
- "\n",
- "\n",
- "\n",
- "> Step.4\n",
- "\n",
- "\n",
- "\n",
- "\n",
- "\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "dcFcNdQdH-BF"
- },
- "source": [
- "埋め込みが適用可能なのは、追加学習のベースモデルがstable diffusion-v1.5までのバージョンのみです。\n",
- "現在の最新のバージョンであるstable diffusion-v2.1をベースモデルとしたものには使用できません。"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "MJXQRW_E3AsI"
- },
- "source": [
- "#**Readme**(日本語版)\n",
- "#利用規約\n",
- "\n",
- "本画像生成ノーブックを使用するにあたって、利用規約の内容に全て同意したとみなします。\n",
- "\n",
- "# **重要な注意点**：\n",
- "* **商用利用はご遠慮ください。**\n",
- "* **画像生成によって起こった問題について、私は一切責任を負いません。**\n",
- "\n",
- ">免責事項:\n",
- "* 使用にあたっては、自己責任でお願いします。\n",
- "* 本モデルは予告なく変更・非公開・削除する可能性があります。\n",
- "* 利用規約は予告なく変更する場合があります。\n",
- "* このモデルは、趣味で作成したものであり、商用利用などは意図していません。\n",
- "* 使用にあたって発生した通信量、電気料金など金銭に関わるものの負担は追い兼ねます\n",
- "* Stable Diffusion-Ver2.1やその他の追加ライブラリに関する規約がある場合は、それらも確認することを強くお勧めします。\n",
- "* 本プロジェクトを利用することにより生じた一切の問題について、私は一切責任を負いません。\n",
- "\n",
- "ー本プロジェクトとは、本画像生成ノートブックや、githubのページなどをさします\n",
- "___\n",
- "#本プロジェクトの説明\n",
- "Stable Diffusion-Ver2.1をベースにした画像生成ノートブックです。\n",
- "\n",
- "\n",
- ">使用させていただいたライブラリ\n",
- "- Stable Diffusion-ver2.1\n",
- "- CLIP\n",
- "- tqdm\n",
- "- ftfy\n",
- "- scipy\n",
- "- regex\n",
- "- torch\n",
- "- diffusers\n",
- "- accelerate\n",
- "- safetensors\n",
- "- transformers\n",
- "\n",
- "※2023/5/12時点\n",
- "---\n",
- "\n",
- "謝辞\n",
- "\n",
- "本画像生成ノートブックの作成にあたり、オープンソースのリソースやフリーのツールを使用させていただきました。個人的な利用でしたが、これらのリソースやツールがあったからこそ、本プロジェクトを実現することができました。\n",
- "この場を借りて、オープンソースのコミュニティや、フリーのツールを提供してくださった方々に感謝の意を表します。素晴らしいツールや技術を提供してくださり、本プロジェクトを支援してくださったことに心から感謝いたします。"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "XKISm_HGOcgG"
- },
- "source": [
- "#**Readme(English_ver)**\n",
- "# Terms of Use\n",
- "\n",
- "By using this image generation notebook, you agree to all the contents of the Terms of Use.\n",
- "\n",
- "Important Notice:\n",
- "**Please refrain from using for commercial purposes.**\n",
- "**I am not responsible for any problems caused by image generation.**\n",
- "\n",
- ">Disclaimer:\n",
- "* Please use it at your own risk.\n",
- "* This NoteBook may be changed, unpublished, or deleted without notice.\n",
- "* The terms of use may be changed without notice.\n",
- "* This NoteBook is created for personal use and is not intended for commercial use.\n",
- "* If there are terms and conditions for Stable Diffusion-Ver2.1 and other additional libraries, it is strongly recommended to confirm them as well.\n",
- "* I am not responsible for any problems caused by using this project.\n",
- "\n",
- "ー This project refers to the image generation notebook and GitHub pages.\n",
- "\n",
- "---\n",
- "\n",
- "# Description of this project\n",
- "\n",
- "This is an image generation notebook based on Stable Diffusion-Ver2.1.\n",
- "\n",
- "**Tools used**\n",
- "* As of 2023/5/12\n",
- "\n",
- ">**Libraries used**\n",
- "- Stable Diffusion-ver2.1\n",
- "- CLIP\n",
- "- tqdm\n",
- "- ftfy\n",
- "- scipy\n",
- "- regex\n",
- "- torch\n",
- "- diffusers\n",
- "- accelerate\n",
- "- safetensors\n",
- "- transformers\n",
- "\n",
- "---\n",
- "\n",
- "# Acknowledgements\n",
- "\n",
- "I used open source resources and free tools to create this image generation notebook. Although it was for personal use, it was only possible to realize this project because of these resources and tools.\n",
- "I would like to express my gratitude to the open source community and those who provide free tools. I sincerely appreciate your support for this project by providing great tools and technologies.\n"
- ]
- }
- ],
- "metadata": {
- "accelerator": "GPU",
- "colab": {
- "provenance": [],
- "include_colab_link": true
- },
- "kernelspec": {
- "display_name": "Python 3",
- "name": "python3"
- },
- "language_info": {
- "name": "python"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 0
-}
\ No newline at end of file