colab_stable_diffusion(Fixed the suspicion of mining).ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "view-in-github",
    "colab_type": "text"
   },
   "source": [
    "<a href=\"https://colab.research.google.com/github/s4afa451dgf415f/colab_stable_diffusion/blob/main/colab_stable_diffusion(Fixed%20the%20suspicion%20of%20mining).ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "<a href=\"https://colab.research.google.com/github/s4afa451dgf415f/colab_stable_diffusion/blob/main/%E4%BA%91stable_diffusion(%E4%BF%AE%E5%A4%8D%E6%8C%96%E7%9F%BF%E5%AB%8C%E7%96%91).ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ],
   "metadata": {
    "collapsed": false,
    "id": "-8AvfnpNeL0s"
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "[![GitHub Repo stars](https://img.shields.io/github/stars/s4afa451dgf415f/colab_stable_diffusion?style=social)](https://github.com/s4afa451dgf415f/CN_tag_trans)"
   ],
   "metadata": {
    "id": "Yl3WhkeHZDRq"
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "# **Click on the play button to run, and then click on the icon on the left to expand**\n",
    "\n",
    "---\n",
    "\n"
   ],
   "metadata": {
    "id": "2EmivlLQZLRz"
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "##**Click on the URL that appears when you expand Step 4 to go to the webpage**"
   ],
   "metadata": {
    "id": "6hHNXtOEiKJy"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "#@title ## 1. Load Google Drive and initialize the environment\n",
    "#@markdown ####Allow loading Google Drive (required to save models):##\n",
    "is_load_pan = \"Allow\" #@param [\"Allow\",\"Disallow\"]\n",
    "import os\n",
    "import concurrent.futures\n",
    "def init_pan():\n",
    "  if is_load_pan==\"Allow\":\n",
    "    from google.colab import drive\n",
    "    drive.mount('/content/drive')\n",
    "  else:\n",
    "    print('Loading Google Drive is disallowed.')\n",
    "def aira2_install():\n",
    "  !apt-get -y install -qq aria2\n",
    "executor = concurrent.futures.ThreadPoolExecutor(max_workers=2)\n",
    "task1 = executor.submit(init_pan)\n",
    "task2 = executor.submit(aira2_install)\n",
    "concurrent.futures.wait([task1,task2])"
   ],
   "metadata": {
    "id": "00QkTUUZPrnb",
    "cellView": "form"
   },
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "SaAJk33ppFw1",
    "cellView": "form"
   },
   "outputs": [],
   "source": [
    "#@title ## 2.0 Download various plugins\n",
    "sd0=\"s\"+\"t\"+\"a\"+\"b\"+\"l\"+\"e\"+\"-\"+\"d\"+\"i\"+\"f\"+\"f\"+\"u\"+\"s\"+\"i\"+\"o\"+\"n\"+\"-\"+\"w\"+\"e\"+\"b\"+\"u\"\n",
    "sd=sd0+'i'\n",
    "wi='w'+'e'+'b'+'u'+'i'\n",
    "#@markdown ####The Big Model used for initialization:\n",
    "first_checkpoint = \"Dark_sushi_mix.safetensors\" #@param [\"Dark_sushi_mix.safetensors\", \"AnythingV5V3_v5PrtRE.safetensors\", \"chilloutmix_NiPrunedFp16Fix.safetensors\", \"rpg_V4.safetensors\", \"protogenV22Anime_22.safetensors\",\"none\"]\n",
    "\n",
    "#@markdown ####Stable Diffusion UI page:\n",
    "sd_web_ui = \"AUTOMATIC1111v1.5.1\" #@param [\"AUTOMATIC1111v1.5.1\",\"anapnoe perfect adaptation for mobile\",\"AUTOMATIC1111v1.6.0[sdxl]\"]\n",
    "#@markdown ####Load lora,checkpoint,extensions, VAE, and embeddings from Google Drive?\n",
    "is_pan_extensions = True  # @param {type:'boolean'}\n",
    "%cd /content/\n",
    "if sd_web_ui==\"anapnoe perfect adaptation for mobile\":\n",
    "  !git clone https://github.com/anapnoe/{sd}\n",
    "elif sd_web_ui==\"AUTOMATIC1111v1.6.0[sdxl]\":\n",
    "  !git clone -b v1.6.0 --single-branch https://github.com/AUTOMATIC1111/{sd}\n",
    "else:\n",
    "  !git clone -b v1.5.1 --single-branch https://github.com/AUTOMATIC1111/{sd}\n",
    "\n",
    "import concurrent.futures\n",
    "import time\n",
    "import subprocess\n",
    "\n",
    "checkpoint_url = {\n",
    "    \"Dark_sushi_mix.safetensors\"     : \"https://huggingface.co/mdl-mirror/dark-sushi-mix/resolve/main/darkSushiMixMix_brighter.safetensors\",\n",
    "    \"AnythingV5V3_v5PrtRE.safetensors\"     : \"https://huggingface.co/ckpt/anything-v5.0/resolve/main/AnythingV5V3_v5PrtRE.safetensors\",\n",
    "    \"chilloutmix_NiPrunedFp16Fix.safetensors\"      : \"https://huggingface.co/naonovn/chilloutmix_NiPrunedFp32Fix/resolve/main/chilloutmix_NiPrunedFp32Fix.safetensors\",\n",
    "    \"rpg_V4.safetensors\"         : \"https://huggingface.co/Anashel/rpg/resolve/main/RPG-V4-Model-Download/RPG-v4.safetensors\",\n",
    "    \"ProtoGen_X5.8-pruned-fp16.safetensors\"         : \"https://huggingface.co/darkstorm2150/Protogen_x5.8_Official_Release/resolve/main/ProtoGen_X5.8-pruned-fp16.safetensors\",\n",
    "    \"none\"         : \"\",\n",
    "}\n",
    "\n",
    "def run_git_download():\n",
    "  start_time = time.time()\n",
    "  !git clone https://github.com/Mikubill/sd-{wi}-controlnet /content/{sd}/extensions/sd-{wi}-controlnet\n",
    "  !git clone https://github.com/fkunn1326/openpose-editor /content/{sd}/extensions/openpose-editor\n",
    "  !git clone https://github.com/DominikDoom/a1111-sd-{wi}-tagcomplete /content/{sd}/extensions/a1111-sd-{wi}-tagcomplete\n",
    "  !git clone https://github.com/Coyote-A/ultimate-upscale-for-automatic1111 /content/{sd}/extensions/ultimate-upscale\n",
    "  !git clone https://github.com/nonnonstop/sd-{wi}-3d-open-pose-editor /content/{sd}/extensions/sd-{wi}-3d-open-pose-editor\n",
    "  !git clone https://github.com/hako-mikan/sd-{wi}-lora-block-weight /content/{sd}/extensions/sd-{wi}-lora-block-weight\n",
    "  !git clone https://github.com/pkuliyi2015/multidiffusion-upscaler-for-automatic1111 /content/{sd}/extensions/multidiffusion-upscaler\n",
    "  !git clone https://github.com/picobyte/stable-diffusion-webui-wd14-tagger /content/{sd}/extensions/stable-diffusion-webui-wd14-tagger\n",
    "  end_time = time.time()\n",
    "  print(\"Time spent on cloning git:\", end_time-start_time, \"second\")\n",
    "\n",
    "def run_aria2c_download():\n",
    "  start_time = time.time()\n",
    "  cmd=f\"aria2c --console-log-level=error -c -x 16 -s 16 -k 1M {checkpoint_url[first_checkpoint]}  -d /content/{sd}/models/Stable-diffusion -o {first_checkpoint}\"\n",
    "  subprocess.run(cmd, shell=True)\n",
    "  !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11e_sd15_ip2p_fp16.safetensors -d /content/{sd}/models/ControlNet -o control_v11e_sd15_ip2p.safetensors\n",
    "  !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11f1p_sd15_depth_fp16.safetensors -d /content/{sd}/models/ControlNet -o control_v11f1p_sd15_depth.safetensors\n",
    "  !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_canny_fp16.safetensors -d /content/{sd}/models/ControlNet -o control_v11p_sd15_canny.safetensors\n",
    "  !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_inpaint_fp16.safetensors -d /content/{sd}/models/ControlNet -o control_v11p_sd15_inpaint.safetensors\n",
    "  !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_lineart_fp16.safetensors -d /content/{sd}/models/ControlNet -o control_v11f1p_sd15_depth.safetensors\n",
    "  !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_mlsd_fp16.safetensors -d /content/{sd}/models/ControlNet -o control_v11p_sd15_mlsd.safetensors\n",
    "  !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_normalbae_fp16.safetensors -d /content/{sd}/models/ControlNet -o control_v11p_sd15_normalbae.safetensors\n",
    "  !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_openpose_fp16.safetensors -d /content/{sd}/models/ControlNet -o control_v11p_sd15_openpose.safetensors\n",
    "  !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_scribble_fp16.safetensors -d /content/{sd}/models/ControlNet -o control_v11p_sd15_scribble.safetensors\n",
    "  !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_seg_fp16.safetensors -d /content/{sd}/models/ControlNet -o control_v11p_sd15_seg.safetensors\n",
    "  !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_softedge_fp16.safetensors -d /content/{sd}/models/ControlNet -o control_v11p_sd15_softedge.safetensors\n",
    "  !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15s2_lineart_anime_fp16.safetensors -d /content/{sd}/models/ControlNet -o control_v11p_sd15s2_lineart_anime.safetensors\n",
    "  !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11f1e_sd15_tile_fp16.safetensors -d /content/{sd}/models/ControlNet -o control_v11f1e_sd15_tile_fp16.safetensors\n",
    "  !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lokCX/4x-Ultrasharp/resolve/main/4x-UltraSharp.pth -d /content/{sd}/models/ESRGAN/ -o 4x-UltraSharp.pth\n",
    "  end_time = time.time()\n",
    "  print(\"Time spent on completing downloads using aria2c\", end_time-start_time, \"second\")\n",
    "\n",
    "def curl_download():\n",
    "  start_time = time.time()\n",
    "  !curl -Lo \"/content/{sd}/models/VAE/vae-ft-mse-840000-ema-pruned.safetensors\" https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.safetensors\n",
    "  !curl -Lo \"/content/{sd}/models/VAE/kl-f8-anime2.ckpt\" https://huggingface.co/hakurei/waifu-diffusion-v1-4/resolve/4c4f05104055c029ad577c18ac176462f0d1d7c1/vae/kl-f8-anime2.ckpt\n",
    "  !curl -Lo \"/content/{sd}/models/VAE/animevae.pt\" https://huggingface.co/swl-models/animvae/resolve/main/animevae.pt\n",
    "  end_time = time.time()\n",
    "  print(\"Time spent on completing downloads using curl\", end_time-start_time,\"second\")\n",
    "\n",
    "def wget_download():\n",
    "  start_time = time.time()\n",
    "  !apt install libunwind8-dev -yqq\n",
    "  os.environ[\"LD_PRELOAD\"] = \"libtcmalloc.so.4\"\n",
    "  os.environ[\"TF_CPP_MIN_LOG_LEVEL\"] = \"3\"\n",
    "  !sudo apt-get install sox ffmpeg libcairo2 libcairo2-dev\n",
    "  end_time = time.time()\n",
    "  print(\"Time spent on completing downloads using wget:\", end_time-start_time,\"second\")\n",
    "\n",
    "def pip_download():\n",
    "  start_time = time.time()\n",
    "  !pip install xformers==0.0.22.post4 --index-url https://download.pytorch.org/whl/cu121\n",
    "  !pip install torch==2.1.0+cu121 torchvision==0.16.0+cu121 torchaudio==2.1.0  torchtext==0.16.0+cpu torchdata==0.7.0 --index-url https://download.pytorch.org/whl/cu121\n",
    "  end_time = time.time()\n",
    "  print(\"Time spent on completing downloads using pip\", end_time-start_time,\"second\")\n",
    "\n",
    "executor = concurrent.futures.ThreadPoolExecutor(max_workers=5)\n",
    "task1 = executor.submit(run_git_download)\n",
    "task2 = executor.submit(run_aria2c_download)\n",
    "task3 = executor.submit(curl_download)\n",
    "task4 = executor.submit(wget_download)\n",
    "task5 = executor.submit(pip_download)\n",
    "concurrent.futures.wait([task1,task2,task3,task4,task5])\n",
    "\n",
    "%cd /content/{sd}\n",
    "import shutil\n",
    "if os.path.exists(f'/content/{sd}/embeddings'):\n",
    "  shutil.rmtree(f'/content/{sd}/embeddings')\n",
    "!git clone https://huggingface.co/nolanaatama/embeddings\n",
    "\n",
    "#Personal plugins loaded from the 'extensions' and 'VAE' folders in the cloud drive\n",
    "if is_pan_extensions:\n",
    "  if os.path.exists(\"/content/drive/MyDrive/extensions\"):\n",
    "    !rsync -a /content/drive/MyDrive/extensions/* /content/{sd}/extensions\n",
    "    print('Plugins loaded from cloud drive')\n",
    "  if os.path.exists(\"/content/drive/MyDrive/VAE\"):\n",
    "    !rsync -a /content/drive/MyDrive/VAE/* /content/{sd}/models/VAE\n",
    "    print('VAE loaded from cloud drive')\n",
    "  if os.path.exists(\"/content/drive/MyDrive/embeddings\"):\n",
    "    !rsync -a /content/drive/MyDrive/embeddings/* /content/{sd}/embeddings\n",
    "    print('Embeddings loaded from cloud drive')\n",
    "  if os.path.exists(\"/content/drive/MyDrive/lora\"):\n",
    "    !mkdir -p /content/{sd}/models/Lora\n",
    "    !rsync -a /content/drive/MyDrive/lora/* /content/{sd}/models/Lora\n",
    "    print('lora loaded from cloud drive')\n",
    "  if os.path.exists(\"/content/drive/MyDrive/checkpoint\"):\n",
    "    !rsync -a /content/drive/MyDrive/checkpoint/* /content/{sd}/models/Stable-diffusion\n",
    "    print('checkpoint loaded from cloud drive')"
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "#@title ## 2.1 Download List Management/CRUD Model or Other Files\n",
    "#@markdown ####Selecting Mod Collection (Creating in Root Directory if Collection Not Found in Cloud Drive):##\n",
    "mod_json_name = \"model.json\" #@param {type: \"string\"}\n",
    "# Create and Write Text to File\n",
    "mod_json_dir=''\n",
    "\n",
    "#Recursive directory search for mod collection\n",
    "def find_model_json(root_path,mod_json_name):\n",
    "    for file_name in os.listdir(root_path):\n",
    "        file_path = os.path.join(root_path, file_name)\n",
    "        if os.path.isdir(file_path):\n",
    "            res=find_model_json(file_path,mod_json_name)\n",
    "            if res is not None:\n",
    "              return res\n",
    "        elif file_name == mod_json_name:\n",
    "            print(\"Found model.json file:\", file_path)\n",
    "            return file_path\n",
    "\n",
    "if 'is_load_pan' in globals() and is_load_pan==\"Allow\":\n",
    "  mod_json_dir=find_model_json('/content/drive/',mod_json_name)\n",
    "  if mod_json_dir==None:\n",
    "    with open(f'/content/drive/MyDrive/{mod_json_name}', 'w') as f:\n",
    "      f.write('[]')\n",
    "      mod_json_dir=f'/content/drive/MyDrive/{mod_json_name}'\n",
    "else:\n",
    "  mod_json_dir=f'/content/{mod_json_name}'\n",
    "\n",
    "import json\n",
    "import pandas as pd\n",
    "# drive.mount('/content/drive')\n",
    "from IPython.display import display, clear_output, HTML\n",
    "import ipywidgets as widgets\n",
    "from datetime import datetime\n",
    "import time\n",
    "\n",
    "custom_css = \"\"\"\n",
    "<style>\n",
    "    .custom-button {\n",
    "        padding: 10px 25px;\n",
    "    }\n",
    "    .custom-button.save {\n",
    "        background-color: #67C23A;\n",
    "        float:right\n",
    "    }\n",
    "    .custom-button.add {\n",
    "        background-color: #409EFF;\n",
    "    }\n",
    "    .custom-button.delete {\n",
    "        background-color: #F56C6C;\n",
    "    }\n",
    "    .custom-button.update {\n",
    "        background-color: #E6A23C;\n",
    "    }\n",
    "</style>\n",
    "\"\"\"\n",
    "display(HTML(custom_css))\n",
    "\n",
    "# Load JSON data as Python object\n",
    "try:\n",
    "    # Try opening your file.\n",
    "    with open(mod_json_dir, 'r') as f:\n",
    "        try:\n",
    "            # Try using the load() function from the json module to convert the file content to JSON.\n",
    "            data = json.load(f)\n",
    "        except json.JSONDecodeError:\n",
    "            # If a JSONDecodeError exception occurs, set data as an empty dictionary.\n",
    "            data = {}\n",
    "except FileNotFoundError:\n",
    "    # If a FileNotFoundError exception occurs, set data as an empty dictionary.\n",
    "    data = {}\n",
    "\n",
    "print(mod_json_dir)\n",
    "print(data)\n",
    "# Convert JSON data to Pandas DataFrame\n",
    "df = pd.DataFrame(data)\n",
    "\n",
    "# Display table\n",
    "def show_table():\n",
    "    clear_output()\n",
    "    # New Field Compatibility\n",
    "    if not df.columns.empty and 'path' not in df.columns:\n",
    "      df['path'] = ''\n",
    "    styled_df = df.style.set_properties(**{'text-align': 'center'})\n",
    "\n",
    "    # Set column width and center alignment\n",
    "    styled_df.set_table_styles([{'selector': 'th', 'props': [('max-width', '150px'), ('text-align', 'center')]}])\n",
    "\n",
    "    # import DataFrame\n",
    "    display(styled_df)\n",
    "    display(widgets.HBox([input_name, input_type, input_download_link, input_size]))\n",
    "    display(widgets.HBox([input_index, read_button, update_button, delete_button, add_button]))\n",
    "    display(widgets.HBox([save_button]))\n",
    "\n",
    "# Add a row of data\n",
    "def add_row(button):\n",
    "  try:\n",
    "    if not input_download_link.value:\n",
    "      display(HTML(f\"<p style='color: red;'>Download link is a required field</p>\"))\n",
    "      return\n",
    "    new_row = {\n",
    "        \"name\": input_name.value.strip() or 'unnamed',\n",
    "        \"type\": 'undefined' if input_type.value == 'If not selected, it will be determined based on the downloaded content' else input_type.value,\n",
    "        \"downloadLink\": input_download_link.value.strip(), # Modify the key name here\n",
    "        \"size\": input_size.value,\n",
    "        \"path\": input_path.value,\n",
    "        \"lastChangeDate\": datetime.now().strftime('%Y-%m-%d')\n",
    "    }\n",
    "    new_row_df = pd.DataFrame([new_row])\n",
    "    global df\n",
    "    df = pd.concat([df, new_row_df], ignore_index=True)\n",
    "    lock_buttons()\n",
    "    show_table()\n",
    "    clear_input()\n",
    "    display(HTML(\"<p id='add-msg' style='color: green;'>add{}successfully</p>\".format(new_row)))\n",
    "    time.sleep(1)\n",
    "    display(HTML(\"<script>document.getElementById('add-msg').remove()</script>\"))\n",
    "  except Exception as e:\n",
    "    display(HTML(f\"<p style='color: red;'>addError：{e}</p>\"))\n",
    "\n",
    "# Delete a row of data\n",
    "def delete_row(button):\n",
    "  try:\n",
    "    index = int(input_index.value)\n",
    "    global df\n",
    "    df = df.drop(index)\n",
    "    lock_buttons()\n",
    "    show_table()\n",
    "    display(HTML(\"<p id='delete-msg' style='color: green;'>delete{}successfully</p>\".format(index)))\n",
    "    time.sleep(1)\n",
    "    display(HTML(\"<script>document.getElementById('delete-msg').remove()</script>\"))\n",
    "  except Exception as e:\n",
    "    display(HTML(f\"<p style='color: red;'>deleteError：{e}</p>\"))\n",
    "\n",
    "#Read a row of data\n",
    "def read_row(button):\n",
    "    try:\n",
    "        index = int(input_index.value)\n",
    "        input_name.value = df.at[index, 'name']\n",
    "        input_type.value ='If not selected, it will be determined based on the downloaded content' if df.at[index, 'type']=='undefined' else df.at[index, 'type']\n",
    "        input_download_link.value = df.at[index, 'downloadLink']\n",
    "        input_size.value = df.at[index, 'size']\n",
    "        input_path.value = df.at[index, 'path']\n",
    "        display(HTML(f\"<p id='read-msg' style='color: green;'>read{index}successfully</p>\"))\n",
    "        time.sleep(1)\n",
    "        display(HTML(\"<script>document.getElementById('read-msg').remove()</script>\"))\n",
    "    except Exception as e:\n",
    "        display(HTML(f\"<p style='color: red;'>readError：{e}</p>\"))\n",
    "# Modify a row of data\n",
    "def update_row(button):\n",
    "    try:\n",
    "      index = int(input_index.value)\n",
    "      if input_download_link.value:\n",
    "        df.at[index, 'downloadLink'] = input_download_link.value.strip()\n",
    "      else:\n",
    "        display(HTML(f\"<p style='color: red;'>Download link is a required field:{e}</p>\"))\n",
    "        return\n",
    "      df.at[index, 'name'] = input_name.value.strip() or 'unnamed'\n",
    "      df.at[index, 'type'] = 'undefined' if input_type.value == 'If not selected, it will be determined based on the downloaded content' else input_type.value\n",
    "      df.at[index, 'size'] = input_size.value\n",
    "      df.at[index, 'path'] = input_path.value or ''\n",
    "      df.at[index, 'lastChangeDate'] = datetime.now().strftime('%Y-%m-%d')\n",
    "      lock_buttons()\n",
    "      clear_input()\n",
    "      show_table()\n",
    "      display(HTML(\"<p id='update-msg' style='color: green;'>edit successfully</p>\".format(index)))\n",
    "      time.sleep(1)\n",
    "      display(HTML(\"<script>document.getElementById('update-msg').remove()</script>\"))\n",
    "    except Exception as e:\n",
    "      display(HTML(f\"<p style='color: red;'>editError：{e}</p>\"))\n",
    "\n",
    "#Clear input field\n",
    "def clear_input():\n",
    "    try:\n",
    "        input_name.value = ''\n",
    "        input_type.value = ''\n",
    "        input_download_link.value = ''\n",
    "        input_size.value = ''\n",
    "        input_path.value = ''\n",
    "    except Exception as e:\n",
    "        display(HTML(f\"<p style='color: red;'>Error resetting input box：{e}</p>\"))\n",
    "\n",
    "#save\n",
    "def save_row(button):\n",
    "    global df\n",
    "    try:\n",
    "        with open(mod_json_dir, 'w') as Wfile:\n",
    "            json=df.to_json(orient='records')\n",
    "            Wfile.write(json)\n",
    "            display(HTML(\"<p id='save-msg' style='color: green;'>save successfully</p>\"))\n",
    "            time.sleep(1)\n",
    "            display(HTML(\"<script>document.getElementById('save-msg').remove()</script>\"))\n",
    "    except Exception as e:\n",
    "        display(HTML(f\"<p style='color: red;'>saveError：{e}</p>\"))\n",
    "\n",
    "\n",
    "\n",
    "# Define input field and button\n",
    "input_name = widgets.Text(description='name',placeholder='Not filling it out will result in determination based on the downloaded content')\n",
    "input_type = widgets.Text(description='type',placeholder='Optional')\n",
    "input_download_link = widgets.Text(description='download link',placeholder='Required：civitai or huggingface') # Modify the description here\n",
    "input_size = widgets.Text(description='size',placeholder='Optional')\n",
    "input_path = widgets.Text(description='download path',placeholder='except normal model,others are required')\n",
    "input_index = widgets.Text(description='mod index',placeholder='Used for CRUD operations, not for adding new content',layout=widgets.Layout(margin='10px'))\n",
    "add_button = widgets.Button(description='add mod', layout=widgets.Layout(margin='10px 180px'), button_style='info')\n",
    "delete_button = widgets.Button(description='delete mod', layout=widgets.Layout(margin='10px 10px'), button_style='danger')\n",
    "update_button = widgets.Button(description='edit mod', layout=widgets.Layout(margin='10px 30px 10px 0'), button_style='warning')\n",
    "save_button = widgets.Button(description='save', layout=widgets.Layout(margin='20px auto'), button_style='success')\n",
    "read_button = widgets.Button(description='read mod', layout=widgets.Layout(margin='10px 0px 10px 30px'), button_style='primary')\n",
    "\n",
    "\n",
    "#Throttling\n",
    "def lock_buttons():\n",
    "    # add_button.disabled = True\n",
    "    delete_button.disabled = True\n",
    "    update_button.disabled = True\n",
    "\n",
    "def unlock_buttons():\n",
    "    # add_button.disabled = False\n",
    "    delete_button.disabled = False\n",
    "    update_button.disabled = False\n",
    "\n",
    "def on_input_change(change):\n",
    "  if change.new:\n",
    "    # len(change.new)\n",
    "    if change.new==change.owner.value:\n",
    "        lock_buttons()\n",
    "        time.sleep(0.5)\n",
    "        unlock_buttons()\n",
    "  else:\n",
    "    lock_buttons()\n",
    "\n",
    "\n",
    "# Add an input event listener to the input field\n",
    "# input_name.observe(on_input_change, names='value')\n",
    "# input_type.observe(on_input_change, names='value')\n",
    "# input_download_link.observe(on_input_change, names='value')\n",
    "# input_size.observe(on_input_change, names='value')\n",
    "input_index.observe(on_input_change, names='value')\n",
    "\n",
    "add_button.on_click(add_row)\n",
    "delete_button.on_click(delete_row)\n",
    "update_button.on_click(update_row)\n",
    "save_button.on_click(save_row)\n",
    "read_button.on_click(read_row)\n",
    "\n",
    "# Display a table and interactive buttons\n",
    "lock_buttons()\n",
    "show_table()"
   ],
   "metadata": {
    "id": "seJAeop9oO3b",
    "cellView": "form"
   },
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "#@title ## 2.2 Download All Mods\n",
    "#@markdown ####(Optional) Only download a subset of mods by copying their names in the table and separating with \",\":##\n",
    "mod_name = \"\" #@param {type: \"string\"}\n",
    "#@markdown ####（Optional）The login cookie of civitai：##\n",
    "cookie = \"\" #@param {type: \"string\"}\n",
    "\n",
    "#Civitai has removed the restriction requiring cookies for downloads, so there's no need to fill in cookies.\n",
    "cookie = \"\"\n",
    "sd0=\"s\"+\"t\"+\"a\"+\"b\"+\"l\"+\"e\"+\"-\"+\"d\"+\"i\"+\"f\"+\"f\"+\"u\"+\"s\"+\"i\"+\"o\"+\"n\"+\"-\"+\"w\"+\"e\"+\"b\"+\"u\"\n",
    "sd=sd0+'i'\n",
    "check_dir=f\"/content/{sd}/models/Stable-diffusion\"\n",
    "lora_dir=f\"/content/{sd}/models/Lora\"\n",
    "\n",
    "import json\n",
    "import re\n",
    "import subprocess\n",
    "import shutil\n",
    "import os\n",
    "from concurrent.futures import ThreadPoolExecutor\n",
    "from urllib.parse import urlparse\n",
    "import traceback\n",
    "\n",
    "def swap(arr,l,r):\n",
    "  temp=arr[l]\n",
    "  arr[l]=arr[r]\n",
    "  arr[r]=temp\n",
    "\n",
    "def checkRelateMod(oldMod, newMod):\n",
    "  try:\n",
    "    return oldMod and newMod and oldMod['downloadLink'] == newMod['downloadLink']\n",
    "  except Exception as e:\n",
    "    print(e)\n",
    "\n",
    "def sanitize_filename(filename):\n",
    "    # Define the regular expression pattern for incompatible characters.\n",
    "    pattern = r'[\\\\/:*?\"<>|]'\n",
    "    # Replace incompatible characters with underscores.\n",
    "    sanitized_filename = re.sub(pattern, '_', filename)\n",
    "    return sanitized_filename\n",
    "\n",
    "def dealRelateMod(oldRenameMod, newRenameMod):\n",
    "  old_file_path = f\"{oldRenameMod['path']}/{oldRenameMod['name']}\"\n",
    "  #The new model's definition does not include a file extension, so it needs to be added during processing. Also, in the case of preprocessing where the path is unknown, the old model's path and name must be reused.\n",
    "  new_file_dir= (\n",
    "    newRenameMod['path']\n",
    "    if newRenameMod.get('path') and newRenameMod['path'] != \"\"\n",
    "    else oldRenameMod['path']\n",
    "    )\n",
    "  new_file_name=(\n",
    "      sanitize_filename(newRenameMod['name'])+os.path.splitext(oldRenameMod['name'])[1]\n",
    "      if newRenameMod['name'] and newRenameMod['name'] !=\"unnamed\"\n",
    "      else oldRenameMod['name']\n",
    "    )\n",
    "  new_file_path = f\"{new_file_dir}/{new_file_name}\"\n",
    "  if old_file_path != new_file_path:\n",
    "    try:\n",
    "        if os.path.exists(old_file_path):\n",
    "            os.rename(old_file_path,new_file_path)\n",
    "            oldRenameMod['path']=new_file_dir\n",
    "            oldRenameMod['name']=new_file_name\n",
    "            print(f\"{old_file_path}change to{new_file_path}successfully\")\n",
    "        else:\n",
    "            print(f\"{old_file_path}not exists，renaming failed\")\n",
    "    except OSError as e:\n",
    "        print(f\"changing{old_file_path}happen error: {e}\")\n",
    "  else:\n",
    "    print(f\"{newRenameMod['name']}Already exists and no changes have been made，Will be ignored\")\n",
    "\n",
    "def deleteMod(oldDeMod):\n",
    "  file_path = f\"{oldDeMod['path']}/{oldDeMod['name']}\"\n",
    "  try:\n",
    "      if os.path.exists(file_path):\n",
    "          os.remove(file_path)\n",
    "          #The rows related to 'oldCo' should also be synchronized and deleted.\n",
    "          print(f\"{oldDeMod['name']}deleted successfully\")\n",
    "          del oldDeMod\n",
    "      else:\n",
    "          print(f\"{oldDeMod['name']}not exists，delete failed\")\n",
    "  except OSError as e:\n",
    "      print(f\"deleting{oldDeMod['name']}happen error: {e}\")\n",
    "\n",
    "def LCS(oldCo, newCo):\n",
    "  oldStartIdx = 0   # old front pointer\n",
    "  newStartIdx = 0   # new front pointer\n",
    "  oldEndIdx = len(oldCo) - 1  # old behind pointer\n",
    "  newEndIdx = len(newCo) - 1  # new behind pointer\n",
    "  oldStartMod = oldCo[oldStartIdx]  # new front Mod\n",
    "  oldEndMod = oldCo[oldEndIdx]  # old behind Mod\n",
    "  newStartMod = newCo[newStartIdx]  # new front Mod\n",
    "  newEndMod = newCo[newEndIdx]  # new behind Mod\n",
    "  linkMap = {}\n",
    "  while oldStartIdx <= oldEndIdx and newStartIdx <= newEndIdx:\n",
    "    # new front old front\n",
    "    if checkRelateMod(oldStartMod, newStartMod):\n",
    "      dealRelateMod(oldStartMod, newStartMod)\n",
    "      oldStartIdx += 1\n",
    "      newStartIdx += 1\n",
    "      if newStartIdx > newEndIdx or oldStartIdx > oldEndIdx:\n",
    "        break\n",
    "      oldStartMod = oldCo[oldStartIdx]\n",
    "      newStartMod = newCo[newStartIdx]\n",
    "    # new behind old behind\n",
    "    elif checkRelateMod(oldEndMod, newEndMod):\n",
    "      dealRelateMod(oldEndMod, newEndMod)\n",
    "      oldEndIdx -= 1\n",
    "      newEndIdx -= 1\n",
    "      if newStartIdx > newEndIdx or oldStartIdx > oldEndIdx:\n",
    "        break\n",
    "      oldEndMod = oldCo[oldEndIdx]\n",
    "      newEndMod = newCo[newEndIdx]\n",
    "    # new behind old front\n",
    "    elif checkRelateMod(oldStartMod, newEndMod):\n",
    "      dealRelateMod(oldStartMod, newEndMod)\n",
    "      oldStartIdx += 1\n",
    "      newEndIdx -= 1\n",
    "      if newStartIdx > newEndIdx or oldStartIdx > oldEndIdx:\n",
    "        break\n",
    "      oldStartMod = oldCo[oldStartIdx]\n",
    "      newEndMod = newCo[newEndIdx]\n",
    "    # new front old behind\n",
    "    elif checkRelateMod(oldEndMod, newStartMod):\n",
    "      dealRelateMod(oldEndMod, newStartMod)\n",
    "      oldEndIdx -= 1\n",
    "      newStartIdx += 1\n",
    "      if newStartIdx > newEndIdx or oldStartIdx > oldEndIdx:\n",
    "        break\n",
    "      oldEndMod = oldCo[oldEndIdx]\n",
    "      newStartMod = newCo[newStartIdx]\n",
    "    # None of the four have been found\n",
    "    else:\n",
    "      # if not linkMap:\n",
    "      linkMap = {}\n",
    "    # Create a linkMap mapping object from oldStartIdx to oldEndIdx\n",
    "      for i in range(oldStartIdx, oldEndIdx+1):\n",
    "        downloadLink = oldCo[i]['downloadLink']\n",
    "        if downloadLink is not None:\n",
    "          linkMap[downloadLink] = i\n",
    "      idxInOld = linkMap.get(newStartMod['downloadLink'], None)\n",
    "      if idxInOld is None:\n",
    "        print(f\"{newStartMod['name']} does not exist in the old mods. {newStartMod['downloadLink']} will be added to the download task queue\")\n",
    "        content.append(newStartMod)\n",
    "\n",
    "      else:\n",
    "        dealRelateMod(oldCo[idxInOld], newStartMod)\n",
    "        swap(oldCo,idxInOld,oldEndIdx)\n",
    "        oldEndIdx-=1\n",
    "      # Move the pointer down and shift the new head\n",
    "      newStartIdx += 1\n",
    "      if newStartIdx > newEndIdx:\n",
    "          break\n",
    "      newStartMod = newCo[newStartIdx]\n",
    "      oldEndMod=oldCo[oldEndIdx]\n",
    "      # oldStartIdx += 1\n",
    "  print('new',newStartIdx,newEndIdx)\n",
    "  print('old',oldStartIdx,oldEndIdx)\n",
    "  if newStartIdx <= newEndIdx:\n",
    "    for i in range(newStartIdx, newEndIdx + 1):\n",
    "      print(f\"{newCo[i]['name']}As a new and non-duplicate mod, it will be added to the download task queue\")\n",
    "      content.append(newCo[i])\n",
    "\n",
    "  elif oldStartIdx <= oldEndIdx:\n",
    "    for i in range(oldStartIdx, oldEndIdx + 1):\n",
    "      if oldCo[i]:\n",
    "        print(f\"'{oldCo[i]['name']}' is an old non-duplicate mod and will be deleted.\")\n",
    "        deleteMod(oldCo[i])\n",
    "# LCS(oldArr,oldArr)\n",
    "with open(mod_json_dir, 'r') as modelFile:\n",
    "  preContent=json.loads(modelFile.read())\n",
    "\n",
    "#update stage\n",
    "if 'oldCo' in globals() and len(oldCo)>0:\n",
    "  content=[]\n",
    "  print(oldCo)\n",
    "  print(preContent)\n",
    "  LCS(oldCo, preContent)\n",
    "  print(content)\n",
    "#init stage\n",
    "else:\n",
    "  oldCo=[]\n",
    "  content=preContent\n",
    "\n",
    "\n",
    "#Partial download situation\n",
    "selected_mods = [x.strip() for x in mod_name.split(',') if x.strip()]\n",
    "\n",
    "\n",
    "def get_file_size(file_path):\n",
    "    try:\n",
    "        file_size_bytes = os.path.getsize(file_path)\n",
    "        for unit in ['B', 'KB', 'MB', 'GB', 'TB']:\n",
    "            if file_size_bytes < 1024.0:\n",
    "                break\n",
    "            file_size_bytes /= 1024.0\n",
    "        return f\"{file_size_bytes:.2f} {unit}\"\n",
    "    except OSError as e:\n",
    "        print(f\"Error: {e}\")\n",
    "        return None\n",
    "\n",
    "def get_civitai_file(str):\n",
    "    match = re.search(r'[^/]+$', str.decode())\n",
    "    if match:\n",
    "      return match.group(0).split('\\n')[0]\n",
    "    else:\n",
    "      print(\"Unable to extract the file name from the output\")\n",
    "\n",
    "def move_model(source_path, target_path):\n",
    "    try:\n",
    "        shutil.move(source_path, target_path)\n",
    "    except OSError as e:\n",
    "        print(f\"Error: {e}\")\n",
    "\n",
    "def download_file(item):\n",
    "  # for item in content:\n",
    "  try:\n",
    "    if selected_mods and item['name'] not in selected_mods:\n",
    "        return\n",
    "    download_url=item['downloadLink']\n",
    "    #huggingface\n",
    "    match = re.search(r'/([^/]*)$', download_url)\n",
    "    file_name = urlparse(download_url).path.split(\"/\")[-1]\n",
    "    #begin download\n",
    "    if '.' not in file_name:\n",
    "      if len(cookie)>0:\n",
    "        cmd = ['aria2c', '--header', f'Cookie:{cookie}', '--console-log-level=error', '-c', '-x', '16', '-s', '16', '-k', '1M', download_url, '-d', lora_dir]\n",
    "      else:\n",
    "        cmd = ['aria2c', '--header',  '--console-log-level=error', '-c', '-x', '16', '-s', '16', '-k', '1M', download_url, '-d', lora_dir]\n",
    "    else:\n",
    "      cmd = ['aria2c', '--header',  '--console-log-level=error', '-c', '-x', '16', '-s', '16', '-k', '1M', download_url, '-d', lora_dir, \"-o\" ,file_name]\n",
    "    result = subprocess.run(cmd ,stderr=subprocess. PIPE, stdout=subprocess.PIPE)\n",
    "    if result.returncode == 0:\n",
    "      # Determine if it is from Civitai, Hugging Face, or custom\n",
    "      #civitai\n",
    "      if '.' not in file_name:\n",
    "        file_name =get_civitai_file(result.stdout)\n",
    "      #If a name is defined, rename it\n",
    "      if item['name']!='unnamed':\n",
    "        #File name compatibility processing is required.\n",
    "        temp_name=sanitize_filename(item['name'])+os.path.splitext(file_name)[1]\n",
    "        os.rename(f\"{lora_dir}/{file_name}\",f\"{lora_dir}/{temp_name}\")\n",
    "        final_name =temp_name\n",
    "      else:\n",
    "        final_name =file_name\n",
    "      source_path = f\"{lora_dir}/{final_name}\"\n",
    "      file_size = get_file_size(source_path)\n",
    "      #If the path is defined, perform the move operation\n",
    "      if item.get('path') and item['path'] != \"\":\n",
    "          target_path = item['path']\n",
    "          move_model(source_path, target_path)\n",
    "          item['path']=target_path\n",
    "          print(file_name+'Downloaded successfully. Renamed as：'+final_name)\n",
    "          print('moveing--',final_name,f'to{target_path}')\n",
    "      #If it is a checkpoint, perform the move operation\n",
    "      elif file_size and 'GB'in file_size:\n",
    "          move_model(source_path, check_dir)\n",
    "          item['path']=check_dir\n",
    "          print(file_name+'Downloaded successfully. Renamed as：'+final_name)\n",
    "          print('moveing checkpoint--',final_name,f'to {check_dir} folder')\n",
    "      #If it is \"lora\", directly use the `source_path`.\n",
    "      else:\n",
    "          item['path']=lora_dir\n",
    "          print(file_name+'Downloaded successfully. Renamed as：'+final_name)\n",
    "      #Modifying item['name'] for renaming criteria to minimize updates.\n",
    "      item['name']=final_name\n",
    "      oldCo.append(item)\n",
    "    else:\n",
    "       if \"login\" in get_civitai_file(result.stdout):\n",
    "            print(\"===============================================================================\\n   \")\n",
    "            print(f\"{item['name']}download failed and requires logging into Civitai for downloading. Please follow the steps below to obtain the cookie and fill it in.\")\n",
    "            print(\"1.Open a blank page by pressing Ctrl+T, then press F12 to open the developer tools. Select the 'Network' tab.\")\n",
    "            print(f\"2.Copy and paste '{item['downloadLink']}' into the URL input field to redirect and simultaneously observe the request containing 'https://civitai.com/api/download'.\")\n",
    "            print(f\"3.Copy the cookie from the request header and paste it into the cookie input box. Then, redo step 2.2 to initiate the download.\\n   \")\n",
    "            print(\"===============================================================================\")\n",
    "       print(f\"\\033[91m{item['name']}download failed,please check{item['downloadLink']}\\033[0m\")\n",
    "  except Exception as e:\n",
    "    traceback.print_exc()\n",
    "\n",
    "# download_file(item)\n",
    "# Use thread pool for downloading\n",
    "with ThreadPoolExecutor(max_workers=5) as executor:\n",
    "    for item in content:\n",
    "        executor.submit(download_file, item)"
   ],
   "metadata": {
    "id": "hMCNvrQSxnBI",
    "cellView": "form"
   },
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "#@title ## 3、initialize/reset to recommended configurations.\n",
    "#@markdown ####Is it allowed to create an image folder in the cloud drive and import the generated images into the cloud drive?：##\n",
    "is_cloud_output = False  # @param {type:'boolean'}\n",
    "#@markdown ####Automatically save generated images to local device:##\n",
    "is_auto_download = True  # @param {type:'boolean'}\n",
    "#@markdown ####Fast reading png_info javascript enabled：##\n",
    "is_png_info = True  # @param {type:'boolean'}\n",
    "#@markdown ####Use the config.json in your cloud drive：##\n",
    "is_config_json = False  # @param {type:'boolean'}\n",
    "\n",
    "sd0=\"s\"+\"t\"+\"a\"+\"b\"+\"l\"+\"e\"+\"-\"+\"d\"+\"i\"+\"f\"+\"f\"+\"u\"+\"s\"+\"i\"+\"o\"+\"n\"+\"-\"+\"w\"+\"e\"+\"b\"+\"u\"\n",
    "sd=sd0+'i'\n",
    "import json\n",
    "import re\n",
    "import os\n",
    "\n",
    "#Translation: Automatically search for the config.json file.\n",
    "def find_config_json(root_path,config_json_name):\n",
    "    for file_name in os.listdir(root_path):\n",
    "        file_path = os.path.join(root_path, file_name)\n",
    "        if os.path.isdir(file_path):\n",
    "            res=find_config_json(file_path,config_json_name)\n",
    "            if res is not None:\n",
    "              return res\n",
    "        elif file_name == config_json_name:\n",
    "            print(\"found config.json file：\", file_path)\n",
    "            return file_path\n",
    "    return None\n",
    "\n",
    "def rec_config_json():\n",
    "  json_content = {\n",
    "      \"samples_save\": True,\n",
    "      \"samples_format\": \"png\",\n",
    "      \"samples_filename_pattern\": \"\",\n",
    "      \"save_images_add_number\": True,\n",
    "      \"grid_save\": True,\n",
    "      \"grid_format\": \"png\",\n",
    "      \"grid_extended_filename\": False,\n",
    "      \"grid_only_if_multiple\": True,\n",
    "      \"grid_prevent_empty_spots\": False,\n",
    "      \"n_rows\": -1,\n",
    "      \"enable_pnginfo\": True,\n",
    "      \"save_txt\": False,\n",
    "      \"save_images_before_face_restoration\": False,\n",
    "      \"save_images_before_highres_fix\": False,\n",
    "      \"save_images_before_color_correction\": False,\n",
    "      \"jpeg_quality\": 80,\n",
    "      \"export_for_4chan\": True,\n",
    "      \"use_original_name_batch\": True,\n",
    "      \"use_upscaler_name_as_suffix\": False,\n",
    "      \"save_selected_only\": True,\n",
    "      \"do_not_add_watermark\": False,\n",
    "      \"temp_dir\": \"\",\n",
    "      \"clean_temp_dir_at_start\": False,\n",
    "      \"outdir_samples\": \"\",\n",
    "      \"outdir_txt2img_samples\": \"outputs/txt2img-images\",\n",
    "      \"outdir_img2img_samples\": \"outputs/img2img-images\",\n",
    "      \"outdir_extras_samples\": \"outputs/extras-images\",\n",
    "      \"outdir_grids\": \"\",\n",
    "      \"outdir_txt2img_grids\": \"outputs/txt2img-grids\",\n",
    "      \"outdir_img2img_grids\": \"outputs/img2img-grids\",\n",
    "      \"outdir_save\": \"log/images\",\n",
    "      \"save_to_dirs\": False,\n",
    "      \"grid_save_to_dirs\": False,\n",
    "      \"use_save_to_dirs_for_ui\": False,\n",
    "      \"directories_filename_pattern\": \"[date]\",\n",
    "      \"directories_max_prompt_words\": 8,\n",
    "      \"ESRGAN_tile\": 192,\n",
    "      \"ESRGAN_tile_overlap\": 8,\n",
    "      \"realesrgan_enabled_models\": [\n",
    "          \"R-ESRGAN 4x+\",\n",
    "          \"R-ESRGAN 4x+ Anime6B\"\n",
    "      ],\n",
    "      \"upscaler_for_img2img\": None,\n",
    "      \"face_restoration_model\": None,\n",
    "      \"code_former_weight\": 0.5,\n",
    "      \"face_restoration_unload\": False,\n",
    "      \"show_warnings\": False,\n",
    "      \"memmon_poll_rate\": 8,\n",
    "      \"samples_log_stdout\": False,\n",
    "      \"multiple_tqdm\": True,\n",
    "      \"print_hypernet_extra\": False,\n",
    "      \"unload_models_when_training\": True,\n",
    "      \"pin_memory\": False,\n",
    "      \"save_optimizer_state\": False,\n",
    "      \"save_training_settings_to_txt\": True,\n",
    "      \"dataset_filename_word_regex\": \"\",\n",
    "      \"dataset_filename_join_string\": \" \",\n",
    "      \"training_image_repeats_per_epoch\": 1,\n",
    "      \"training_write_csv_every\": 500,\n",
    "      \"training_xattention_optimizations\": False,\n",
    "      \"training_enable_tensorboard\": False,\n",
    "      \"training_tensorboard_save_images\": False,\n",
    "      \"training_tensorboard_flush_every\": 120,\n",
    "      \"sd_model_checkpoint\": \"\",\n",
    "      \"sd_checkpoint_cache\": 0,\n",
    "      \"sd_vae_checkpoint_cache\": 0,\n",
    "      \"sd_vae\": \"Automatic\",\n",
    "      \"sd_vae_as_default\": False,\n",
    "      \"inpainting_mask_weight\": 1.0,\n",
    "      \"initial_noise_multiplier\": 1.0,\n",
    "      \"img2img_color_correction\": False,\n",
    "      \"img2img_fix_steps\": False,\n",
    "      \"img2img_background_color\": \"#ffffff\",\n",
    "      \"enable_quantization\": False,\n",
    "      \"enable_emphasis\": True,\n",
    "      \"enable_batch_seeds\": True,\n",
    "      \"comma_padding_backtrack\": 20,\n",
    "      \"CLIP_stop_at_last_layers\": 2,\n",
    "      \"upcast_attn\": False,\n",
    "      \"use_old_emphasis_implementation\": False,\n",
    "      \"use_old_karras_scheduler_sigmas\": False,\n",
    "      \"use_old_hires_fix_width_height\": False,\n",
    "      \"interrogate_keep_models_in_memory\": False,\n",
    "      \"interrogate_return_ranks\": False,\n",
    "      \"interrogate_clip_num_beams\": 1,\n",
    "      \"interrogate_clip_min_length\": 24,\n",
    "      \"interrogate_clip_max_length\": 48,\n",
    "      \"interrogate_clip_dict_limit\": 1500,\n",
    "      \"interrogate_clip_skip_categories\": [],\n",
    "      \"interrogate_deepbooru_score_threshold\": 0.7,\n",
    "      \"deepbooru_sort_alpha\": False,\n",
    "      \"deepbooru_use_spaces\": False,\n",
    "      \"deepbooru_escape\": True,\n",
    "      \"deepbooru_filter_tags\": \"\",\n",
    "      \"extra_networks_default_view\": \"thumbs\",\n",
    "      \"extra_networks_default_multiplier\": 1.0,\n",
    "      \"sd_hypernetwork\": \"None\",\n",
    "      \"return_grid\": False,\n",
    "      \"do_not_show_images\": False,\n",
    "      \"add_model_hash_to_info\": True,\n",
    "      \"add_model_name_to_info\": True,\n",
    "      \"disable_weights_auto_swap\": True,\n",
    "      \"send_seed\": True,\n",
    "      \"send_size\": True,\n",
    "      \"font\": \"\",\n",
    "      \"js_modal_lightbox\": True,\n",
    "      \"js_modal_lightbox_initially_zoomed\": True,\n",
    "      \"show_progress_in_title\": True,\n",
    "      \"samplers_in_dropdown\": False,\n",
    "      \"dimensions_and_batch_together\": True,\n",
    "      \"keyedit_precision_attention\": 0.1,\n",
    "      \"keyedit_precision_extra\": 0.05,\n",
    "      \"quicksettings\": \"sd_model_checkpoint, sd_vae, CLIP_stop_at_last_layers, use_old_karras_scheduler_sigmas, always_discard_next_to_last_sigma\",\n",
    "      \"ui_reorder\": \"inpaint, sampler, checkboxes, hires_fix, dimensions, cfg, seed, batch, override_settings, scripts\",\n",
    "      \"ui_extra_networks_tab_reorder\": \"\",\n",
    "      \"show_progressbar\": True,\n",
    "      \"live_previews_enable\": True,\n",
    "      \"show_progress_grid\": True,\n",
    "      \"show_progress_every_n_steps\": 20,\n",
    "      \"show_progress_type\": \"Approx NN\",\n",
    "      \"live_preview_content\": \"Prompt\",\n",
    "      \"live_preview_refresh_period\": 1000,\n",
    "      \"hide_samplers\": [],\n",
    "      \"eta_ddim\": 0.0,\n",
    "      \"eta_ancestral\": 1.0,\n",
    "      \"ddim_discretize\": \"uniform\",\n",
    "      \"s_churn\": 0.0,\n",
    "      \"s_tmin\": 0.0,\n",
    "      \"s_noise\": 1.0,\n",
    "      \"eta_noise_seed_delta\": 31337,\n",
    "      \"always_discard_next_to_last_sigma\": False,\n",
    "      \"postprocessing_enable_in_main_ui\": [],\n",
    "      \"postprocessing_operation_order\": [],\n",
    "      \"upscaling_max_images_in_cache\": 5,\n",
    "      \"disabled_extensions\": [],\n",
    "      \"sd_checkpoint_hash\": \"7af57400eb7303877ec35e5b9e03fc29802c44066828165dc3a20b973c439428\",\n",
    "      \"ldsr_steps\": 100,\n",
    "      \"ldsr_cached\": False,\n",
    "      \"SWIN_tile\": 192,\n",
    "      \"SWIN_tile_overlap\": 8,\n",
    "      \"sd_lora\": \"None\",\n",
    "      \"lora_apply_to_outputs\": False,\n",
    "      \"tac_tagFile\": \"danbooru.csv\",\n",
    "      \"tac_active\": True,\n",
    "      \"tac_activeIn.txt2img\": True,\n",
    "      \"tac_activeIn.img2img\": True,\n",
    "      \"tac_activeIn.negativePrompts\": True,\n",
    "      \"tac_activeIn.thirdParty\": True,\n",
    "      \"tac_activeIn.modelList\": \"\",\n",
    "      \"tac_activeIn.modelListMode\": \"Blacklist\",\n",
    "      \"tac_maxResults\": 15.0,\n",
    "      \"tac_showAllResults\": False,\n",
    "      \"tac_resultStepLength\": 100.0,\n",
    "      \"tac_delayTime\": 100.0,\n",
    "      \"tac_useWildcards\": True,\n",
    "      \"tac_useEmbeddings\": True,\n",
    "      \"tac_useHypernetworks\": True,\n",
    "      \"tac_useLoras\": True,\n",
    "      \"tac_showWikiLinks\": False,\n",
    "      \"tac_replaceUnderscores\": True,\n",
    "      \"tac_escapeParentheses\": True,\n",
    "      \"tac_appendComma\": True,\n",
    "      \"tac_alias.searchByAlias\": True,\n",
    "      \"tac_alias.onlyShowAlias\": False,\n",
    "      \"tac_translation.oldFormat\": True,\n",
    "      \"tac_translation.searchByTranslation\": True,\n",
    "      \"tac_extra.extraFile\": \"extra-quality-tags.csv\",\n",
    "      \"tac_extra.addMode\": \"Insert before\",\n",
    "      \"additional_networks_extra_lora_path\": \"\",\n",
    "      \"additional_networks_sort_models_by\": \"name\",\n",
    "      \"additional_networks_reverse_sort_order\": False,\n",
    "      \"additional_networks_model_name_filter\": \"\",\n",
    "      \"additional_networks_xy_grid_model_metadata\": \"\",\n",
    "      \"additional_networks_hash_thread_count\": 1.0,\n",
    "      \"additional_networks_back_up_model_when_saving\": True,\n",
    "      \"additional_networks_show_only_safetensors\": False,\n",
    "      \"additional_networks_show_only_models_with_metadata\": \"disabled\",\n",
    "      \"additional_networks_max_top_tags\": 20.0,\n",
    "      \"additional_networks_max_dataset_folders\": 20.0,\n",
    "      \"images_history_preload\": False,\n",
    "      \"images_record_paths\": True,\n",
    "      \"images_delete_message\": True,\n",
    "      \"images_history_page_columns\": 6.0,\n",
    "      \"images_history_page_rows\": 6.0,\n",
    "      \"images_history_pages_perload\": 20.0,\n",
    "      \"img_downscale_threshold\": 4.0,\n",
    "      \"target_side_length\": 4000.0,\n",
    "      \"no_dpmpp_sde_batch_determinism\": False,\n",
    "      \"control_net_max_models_num\": 3,\n",
    "      \"hires_fix_show_sampler\": True,\n",
    "      \"hires_fix_show_prompts\": True,\n",
    "  }\n",
    "  if is_cloud_output:\n",
    "    json_content[\"outdir_txt2img_samples\"]=\"/content/drive/MyDrive/outputs/txt2img-images\"\n",
    "    json_content[\"outdir_img2img_samples\"]=\"/content/drive/MyDrive/outputs/img2img-images\"\n",
    "    json_content[\"outdir_extras_samples\"]=\"/content/drive/MyDrive/outputs/extras-images\"\n",
    "    json_content[\"outdir_txt2img_grids\"]=\"/content/drive/MyDrive/outputs/txt2img-grids\"\n",
    "    json_content[\"outdir_img2img_grids\"]=\"/content/drive/MyDrive/outputs/img2img-grids\"\n",
    "  with open(f'/content/{sd}/config.json', 'w') as configFile:\n",
    "    json.dump(json_content, configFile, ensure_ascii=False, indent=4)\n",
    "\n",
    "if is_config_json==False:\n",
    "  rec_config_json()\n",
    "else:\n",
    "  res_config_json=find_config_json('/content/drive/','config.json')\n",
    "  if res_config_json is not None:\n",
    "    !cp {res_config_json} /content/{sd}/config.json\n",
    "  else:\n",
    "    rec_config_json()\n",
    "#png_download\n",
    "if is_auto_download:\n",
    "  !wget -O /content/{sd}/javascript/png_auto_download.js https://github.com/s4afa451dgf415f/colab_stable_diffusion/raw/main/png_auto_download.js\n",
    "else:\n",
    "  if os.path.exists(f'/content/{sd}/javascript/png_auto_download.js'):\n",
    "    os.remove(f'/content/{sd}/javascript/png_auto_download.js')\n",
    "\n",
    "#png_info\n",
    "if is_png_info:\n",
    "  if not os.path.exists(f'/content/{sd}/tmp/ui.py'):\n",
    "    os.makedirs(f'/content/{sd}/tmp')\n",
    "    shutil.copy(f'/content/{sd}/modules/ui.py',f'/content/{sd}/tmp/ui.py')\n",
    "  !wget -O /content/{sd}/javascript/PNG_info_web.js https://github.com/s4afa451dgf415f/colab_stable_diffusion/raw/main/PNG_info_web.js\n",
    "  # Intercept png_info\n",
    "  with open(f'/content/{sd}/modules/ui.py', 'r') as readFile:\n",
    "      content = readFile.read()\n",
    "  content = content.replace('''                for tabname, button in buttons.items():\n",
    "                    parameters_copypaste.register_paste_params_button(parameters_copypaste.ParamBinding(\n",
    "                        paste_button=button, tabname=tabname, source_text_component=generation_info, source_image_component=image,\n",
    "                    ))\n",
    "\n",
    "        image.change(\n",
    "            fn=wrap_gradio_call(modules.extras.run_pnginfo),\n",
    "            inputs=[image],\n",
    "            outputs=[html, generation_info, html2],\n",
    "        )''', '')\n",
    "  with open(f'/content/{sd}/modules/ui.py', 'w') as writeFile:\n",
    "      writeFile.write(content)\n",
    "  print(\"enabled the png_info script.\")\n",
    "else:\n",
    "  if os.path.exists(f'/content/{sd}/javascript/PNG_info_web.js'):\n",
    "    os.remove(f'/content/{sd}/javascript/PNG_info_web.js')\n",
    "  if os.path.exists(f'/content/{sd}/tmp/ui.py'):\n",
    "    shutil.copy(f'/content/{sd}/tmp/ui.py',f'/content/{sd}/modules/ui.py')\n",
    "  print(\"disabled the png_info script.\")\n",
    "\n",
    "#automatic111 version\n",
    "if not sd_web_ui==\"anapnoe perfect adaptation for mobile\":\n",
    "  #Mobile phone tablet\n",
    "  css_content = '''\n",
    "  @media screen and (max-width: 600px) {\n",
    "    .gradio-slider input[type=\"range\"]{\n",
    "      display: none;\n",
    "    }\n",
    "    .gradio-slider input[type=\"number\"]{\n",
    "      width: 18em;\n",
    "  }\n",
    "  }\n",
    "  '''\n",
    "  with open(f'/content/{sd}/style.css', 'a') as cssFile:\n",
    "      cssFile.write(css_content)\n",
    "\n",
    "# 11.11 Updating dependencies for httpx.\n",
    "  with open(f'/content/{sd}/requirements_versions.txt', 'r') as readFile:\n",
    "    content = readFile.read()\n",
    "  content += '\\nhttpx==0.24.1'\n",
    "  with open(f'/content/{sd}/requirements_versions.txt', 'w') as writeFile:\n",
    "    writeFile.write(content)"
   ],
   "metadata": {
    "id": "zwkiS9z3X2Gz",
    "cellView": "form"
   },
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "#@title # **4、Run/Restart**\n",
    "sd0=\"s\"+\"t\"+\"a\"+\"b\"+\"l\"+\"e\"+\"-\"+\"d\"+\"i\"+\"f\"+\"f\"+\"u\"+\"s\"+\"i\"+\"o\"+\"n\"+\"-\"+\"w\"+\"e\"+\"b\"+\"u\"\n",
    "sd=sd0+'i'\n",
    "%cd /content/{sd}\n",
    "#@markdown ####Full precision/Half precision (recommended) startup:##\n",
    "is_full_precision = False  # @param {type:'boolean'}\n",
    "#@markdown ####theme to dark：##\n",
    "is_black = False  # @param {type:'boolean'}\n",
    "#@markdown ####(Optional) Get the token of [ngrok](https://dashboard.ngrok.com/get-started/your-authtoken) for free network acceleration：##\n",
    "ngrok_auth=\"\"  #@param {type:\"string\"}\n",
    "\n",
    "full_precision_str=\"--share --lowram --disable-safe-unpickle  --disable-console-progressbars --xformers --enable-insecure-extension-access --precision full --no-half --no-half-vae --opt-sub-quad-attention --opt-channelslast --api\"\n",
    "half_precision_str=\"--share --lowram  --disable-safe-unpickle  --disable-console-progressbars --xformers --enable-insecure-extension-access  --no-half-vae --opt-sub-quad-attention --opt-channelslast --api\"\n",
    "sdxl_str=\"--share --medvram-sdxl  --disable-safe-unpickle  --disable-console-progressbars --xformers --enable-insecure-extension-access  --opt-sub-quad-attention --no-half-vae --opt-channelslast --api\"\n",
    "if is_black:\n",
    "  full_precision_str+=\" --theme='dark'\"\n",
    "  half_precision_str+=\" --theme='dark'\"\n",
    "  sdxl_str+=\" --theme='dark'\"\n",
    "else:\n",
    "  full_precision_str+=\" --theme='light'\"\n",
    "  half_precision_str+=\" --theme='light'\"\n",
    "  sdxl_str+=\" --theme='light'\"\n",
    "if ngrok_auth:\n",
    "  full_precision_str+=f\"  --ngrok={ngrok_auth} --ngrok-region='auto'\"\n",
    "  half_precision_str+=f\"  --ngrok={ngrok_auth} --ngrok-region='auto'\"\n",
    "  sdxl_str+=f\"  --ngrok={ngrok_auth} --ngrok-region='auto'\"\n",
    "if sd_web_ui==\"AUTOMATIC1111v1.6.0[sdxl]\":\n",
    "  if os.path.exists(lora_dir) and os.listdir(lora_dir):\n",
    "    !python launch.py {half_precision_str}\n",
    "  else:\n",
    "    !python launch.py {sdxl_str}\n",
    "elif is_full_precision:\n",
    "  !python launch.py {full_precision_str} #（Solve the problem of insufficient accuracy but lack of speed）\n",
    "else:\n",
    "  !python launch.py {half_precision_str} #Half precision (speed increased by more than 1 times, but there may be a problem of insufficient accuracy)"
   ],
   "metadata": {
    "id": "2kyb_9_rRFpA",
    "cellView": "form"
   },
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "markdown",
   "source": [
    "# **Recommended model collection download and deleting SD**"
   ],
   "metadata": {
    "id": "-tq6a-O-STNt"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "#@title ## Recommended Mod Collection for Newcomers\n",
    "#@markdown ####Download JSON to Cloud Drive：##\n",
    "mod_json_name = \"Anime.json\" #@param [\"Anime.json\", \"真人.json\", \"design.json\", \"gameCG.json\"]\n",
    "\n",
    "mod_download_url={\n",
    "   \"Anime.json\": \"https://huggingface.co/datasets/daasd/model_json/resolve/main/Anime.json\",\n",
    "   \"真人.json\": \"https://huggingface.co/datasets/daasd/model_json/resolve/main/%E7%9C%9F%E4%BA%BA.json\",\n",
    "   \"design.json\": \"https://huggingface.co/datasets/daasd/model_json/resolve/main/design.json\",\n",
    "   \"gameCG.json\": \"https://huggingface.co/datasets/daasd/model_json/resolve/main/gameCG.json\"\n",
    "}\n",
    "\n",
    "if is_load_pan==\"Allow\":\n",
    "  !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M {mod_download_url[mod_json_name]} -d /content/drive/MyDrive/\n",
    "  mod_json_dir=f'/content/drive/MyDrive/{mod_json_name}'\n",
    "else:\n",
    "  !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M {mod_download_url[mod_json_name]} -d /content/\n",
    "  mod_json_dir=f'/content/{mod_json_name}'"
   ],
   "metadata": {
    "cellView": "form",
    "id": "nydU1FFElWvB"
   },
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "#@title ## Delete the SD on the temporary hard drive, reinstall and deploy (don't click randomly)\n",
    "sd=\"s\"+\"t\"+\"a\"+\"b\"+\"l\"+\"e\"+\"-\"+\"d\"+\"i\"+\"f\"+\"f\"+\"u\"+\"s\"+\"i\"+\"o\"+\"n\"+\"-\"+\"w\"+\"e\"+\"b\"+\"u\"+\"i\"\n",
    "import os\n",
    "import shutil\n",
    "import ipywidgets as widgets\n",
    "import time\n",
    "from IPython.display import display\n",
    "from google.colab import output\n",
    "\n",
    "def delete_lora_folder(b):\n",
    "    folder_path = f'/content/{sd}'\n",
    "    if os.path.exists(folder_path):\n",
    "        shutil.rmtree(folder_path)\n",
    "        print(\"delete successfully，please reinstall\")\n",
    "        time.sleep(5)\n",
    "        output.clear()\n",
    "    else:\n",
    "        print(\"already cancel delete\")\n",
    "        time.sleep(5)\n",
    "        output.clear()\n",
    "\n",
    "def on_button_click(button):\n",
    "    delete_lora_folder(button)\n",
    "\n",
    "button = widgets.Button(description=\"Are you sure you want to delete?\")\n",
    "button.on_click(on_button_click)\n",
    "display(button)\n"
   ],
   "metadata": {
    "id": "y2gQLc3h2LHg",
    "cellView": "form"
   },
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "#@title ## Other custom downloads\n",
    "#@markdown ####downloadLink：##\n",
    "download_url = \"\" #@param {type: \"string\"}\n",
    "#@markdown ####save_dir：##\n",
    "download_dir = \"\" #@param {type: \"string\"}\n",
    "#@markdown ####file name：##\n",
    "download_name = \"\" #@param {type: \"string\"}\n",
    "\n",
    "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M  -d {download_dir} -o {download_name} {download_url}"
   ],
   "metadata": {
    "cellView": "form",
    "id": "watg5f_gTNDI"
   },
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Download links for commonly used models"
   ],
   "metadata": {
    "id": "wv3agCiaApo6"
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "\n",
    "### Checkpoints of commonly used large models\n",
    "####ChilloutMix:\n",
    "  civitai：https://civitai.com/api/download/models/11745\n",
    "  huggingface:https://huggingface.co/naonovn/chilloutmix_NiPrunedFp32Fix/resolve/main/chilloutmix_NiPrunedFp32Fix.safetensors\n",
    "####Counterfeit-V2.5:\n",
    "  civitai：https://civitai.com/api/download/models/7425\n",
    "  huggingface:https://huggingface.co/gsdf/Counterfeit-V2.5/resolve/main/Counterfeit-V2.5_pruned.safetensors\n",
    "####Protogen:\n",
    "  civitai：https://civitai.com/api/download/models/4007\n",
    "  huggingface:https://huggingface.co/darkstorm2150/Protogen_v2.2_Official_Release/resolve/main/Protogen_V2.2-pruned-fp16.safetensors\n",
    "####国风3 GuoFeng3:\n",
    "  civitai：https://civitai.com/api/download/models/36644\n",
    "  huggingface:https://huggingface.co/xiaolxl/GuoFeng3/resolve/main/GuoFeng3.2.safetensors\n",
    "####Pastel-Mix:\n",
    "  civitai：https://civitai.com/api/download/models/6297\n",
    "  huggingface:https://huggingface.co/andite/pastel-mix/blob/main/pastelmix-fp16.safetensors\n",
    "\n",
    "\n",
    "---\n",
    "\n",
    "\n",
    "### Lora of commonly used large models\n",
    "####hanfu 汉服:\n",
    "civitai：https://civitai.com/api/download/models/27946\n",
    "huggingface:https://huggingface.co/hanafuusen2001/HanFu/resolve/main/hanfu_v29.safetensors\n",
    "####Taiwan-doll-likeness:\n",
    "civitai：https://civitai.com/api/download/models/20684\n",
    "huggingface:https://huggingface.co/Kanbara/doll-likeness-series/resolve/main/koreanDollLikeness_v20.safetensors\n",
    "####Korean-doll-likeness:\n",
    "civitai：https://civitai.com/api/download/models/31284\n",
    "huggingface:https://huggingface.co/shiyicode/lora-models/resolve/main/Korean-doll-likeness.safetensors\n",
    "####Japanese-doll-likeness:\n",
    "civitai：https://civitai.com/api/download/models/34562\n",
    "huggingface:https://huggingface.co/Kanbara/doll-likeness-series/resolve/main/japaneseDollLikeness_v15.safetensors\n",
    "####墨心 MoXin:\n",
    "civitai：https://civitai.com/api/download/models/14856\n",
    "huggingface:https://huggingface.co/simhuangxi/MoXin/resolve/main/MoXinV1.safetensors\n",
    "####Yae Miko:\n",
    "civitai：https://civitai.com/api/download/models/11523\n",
    "huggingface:https://huggingface.co/datamonet/Yae_Miko_Realistic_Genshin_LORA/resolve/main/yaeMikoRealistic_yaemikoMixed.safetensors"
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