Vladmandic_SD_A1111.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/YKefasu/Vlad-SD-Google-Colab/blob/master/Vladmandic_SD_A1111.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CrdNfALDl_Q8"
      },
      "source": [
        "<center>\n",
        "<font color=\"#CC3E3E\" size=\"6\">⚠️ <u><b>PERHATIAN</b></u> ⚠️</font></center>\n",
        "\n",
        "> <font color=\"#00CED1\">**INFORMASI**:</font>\n",
        "\n",
        "1. Pastikan Subscribe ke 👉 [youtube.com/@yosiakefas](https://www.youtube.com/@yosiakefas) dan Join [Discord Server](https://discord.gg/j8qmYPAGQh) untuk mendapatkan UPDATE Terbaru.\n",
        "2. GOOGLE SECARA BRUTAL MELARANG PENGGUNAAN STABLE DIFFUSION\n",
        "\n",
        "<center>\n",
        "\n",
        "![image.png](data:image/png;base64,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)\n",
        "\n",
        "![image.png](data:image/png;base64,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)\n",
        "\n",
        "</center>\n",
        "\n",
        "<center><font color=\"#CC3E3E\" size=\"6\">⚠️ <u><b>!! <font color=\"#00CED1\" size=\"6\">WAJIB GPU MODE</font> !!</b></u> ⚠️</font></center>\n",
        "\n",
        "\n",
        "</br>\n",
        "\n",
        "<center><font color=\"#00CED1\" size=\"6\">👇 <u><b>PENJELASAN</b></u> 👇</font></br>\n",
        "\n",
        " <a href=\"https://youtu.be/q8XO6defTy0\"><img src=\"https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgv7nV8kvVm_FL7k0EZUjoyBD2rS4wj_pA4uqBh8A5B_kbvHUZ2uAbsUNLLo4cCbyNsp9M4EBhqt4RY7ZaQQDWkhwlBuFM0FOhTTf92IFz0jdldbUmcvkD5T454-7HEw2OP3hsJozUggq7H8d8-BIUcidZN72tW551eyTPUs7MVoLcHcH62PSSpIOthMk0/s640/DeffGCSDXLa.png\" width=\"512\"/></a></a>\n",
        "</center>\n",
        "</br></br>\n",
        "\n",
        "## **<center>Subscribe Youtube Channel & Join Server Discord Kita 😅</center>**\n",
        "<center><font size=\"12\">👉</font> <a href=\"https://trakteer.id/yosiakefas/tip\" target=\"_blank\"><img id=\"wse-buttons-preview\" src=\"https://cdn.trakteer.id/images/embed/trbtn-blue-5.png\" height=\"60\" style=\"border: 0px; height: 60px;\" alt=\"Trakteer Saya\"></a><font size=\"14\">🙏</font></center>\n",
        "</br>\n",
        "<div align=\"center\">\n",
        " <a href=\"https://www.youtube.com/channel/UCsqTcFMsAlegRsUyfyKe_5A\"><img src=\"https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiZxKLHX32VYBBOvxvKUDka6uX0wKYYg46EurNzQBUHjaxd2dSJ82paUaJ1OTzpMMt4R7KUuvsbcOLuAg_9NJ1WaRJev8vmRhWea4xfg0AhjSaX2sp3ZFZGD490AArNICVDqzYvrjTqWbKFHxFLE2AYBVaIrGvkwPTqJCroDTvEb43sNuM5wHHCecd6/s350/subscribe-5408999_640.png\" width=\"310\"/></a>ㅤㅤ\n",
        " <a href=\"https://discord.gg/j8qmYPAGQh\"><img src=\"https://cdn.shopify.com/s/files/1/0562/9329/4253/files/Discord_button_480x480.png\" width=\"350\"/></a></div>\n",
        "\n",
        " ___"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "6og06gzPygrO",
        "cellView": "form"
      },
      "outputs": [],
      "source": [
        "#@markdown #STEP 1️⃣: Persiapan\n",
        "\n",
        "#@markdown Keterangan: Clone Vladmandic SD.Next, and Connect to Google Drive\n",
        "from IPython.display import clear_output, display, HTML\n",
        "import os\n",
        "import time\n",
        "import subprocess\n",
        "import shutil\n",
        "from datetime import timedelta\n",
        "from google.colab import drive\n",
        "from IPython.utils import capture\n",
        "from subprocess import getoutput\n",
        "from urllib.parse import unquote\n",
        "from google.colab.output import eval_js\n",
        "\n",
        "def check_gpu():\n",
        "    print(\"\\033[96m\")  # Cyan text\n",
        "    print('⌚ Checking GPU...', end='')\n",
        "    output = getoutput('nvidia-smi --query-gpu=gpu_name --format=csv')\n",
        "    if \"name\" in output:\n",
        "        gpu_name = output[5:]\n",
        "        print('\\r✅ Current GPU:', gpu_name, flush=True)\n",
        "    else:\n",
        "        print('\\r\\033[91m❎ ERROR: No GPU detected. Lakukan Step dibawah ini.\\n', flush=True)\n",
        "        # Additional code for displaying an image and message\n",
        "        display(HTML(\"<img src='https://i.ibb.co/HC9KH17/NVIDIA-Share-23-01-02-173037.png' width='800px'/>\"))\n",
        "        print('\\033[91m\\nJika tertulis \"Cannot connect to GPU backend\", berarti telah mencapai batas pemakaian. Silahakn istirahat untuk hari ini...')\n",
        "        display(HTML(\"<center><img src='https://media.tenor.com/RY9NX67klacAAAAi/sad-cute.gif' width='272px'/></center>\"))\n",
        "        time.sleep(5)\n",
        "        from google.colab import runtime\n",
        "        runtime.unassign()\n",
        "\n",
        "def clone_repositories():\n",
        "    SD_Next_Commit_hash = \"last commit\"  # @param {'type': 'string'}\n",
        "    if SD_Next_Commit_hash == \"last commit\":\n",
        "        subprocess.run([\"git\", \"clone\", \"--depth=1\", \"https://github.com/vladmandic/automatic.git\"])\n",
        "    else:\n",
        "        subprocess.run([\"git\", \"clone\", \"https://github.com/vladmandic/automatic.git\"])\n",
        "        subprocess.run([\"git\", \"checkout\", SD_Next_Commit_hash], cwd=\"automatic\")\n",
        "\n",
        "    !git clone https://github.com/YKefasu/Vlad-SD-Google-Colab.git\n",
        "    clear_output()\n",
        "\n",
        "def install_requirements():\n",
        "    %cd /content/automatic\n",
        "    !pip install --use-feature=fast-deps -r requirements.txt\n",
        "    !pip install timm==0.6.13 --upgrade\n",
        "    !pip install onnxruntime==1.15.1\n",
        "    !pip install --upgrade huggingface_hub\n",
        "    !pip install wget\n",
        "    !pip install tqdm\n",
        "    !pip install pyngrok\n",
        "    !apt -y install -qq aria2 libcairo2-dev pkg-config python3-dev\n",
        "    clear_output()\n",
        "\n",
        "def install_extensions():\n",
        "    %cd /content/automatic/extensions-builtin/\n",
        "    !git clone https://github.com/YKefasu/sd-artists-ui-tweak sd-artists-ui-tweak\n",
        "    !git clone https://github.com/Iyashinouta/sd-model-downloader sd-model-downloader\n",
        "\n",
        "    remove_ext = '/content/Vlad-SD-Google-Colab/DataFiles/RM ControlNet.txt'\n",
        "    base_directory = '/content/automatic/extensions-builtin/'\n",
        "    with open(remove_ext, 'r') as file:\n",
        "        folder_names = file.read().splitlines()\n",
        "    for folder_name in folder_names:\n",
        "        folder_path = os.path.join(base_directory, folder_name)\n",
        "        try:\n",
        "            shutil.rmtree(folder_path, ignore_errors=True)\n",
        "            print(f\"Folder '{folder_name}' removed successfully.\")\n",
        "        except Exception as e:\n",
        "            print(f\"Error occurred while removing folder '{folder_name}': {e}\")\n",
        "\n",
        "    with open('/content/Vlad-SD-Google-Colab/DataFiles/Extension.txt', 'r') as file:\n",
        "        for line in file:\n",
        "            repo_url = line.strip()\n",
        "            !git clone $repo_url\n",
        "    clear_output()\n",
        "\n",
        "def clone_MiDaS():\n",
        "    %cd /content/automatic/repositories\n",
        "    !git clone https://github.com/isl-org/MiDaS MiDaS\n",
        "    clear_output()\n",
        "\n",
        "def update_style_css():\n",
        "    file_style_css = '/content/automatic/extensions-builtin/sd-artists-ui-tweak/style.css'\n",
        "    os.remove(file_style_css)\n",
        "    shutil.move(\"/content/Vlad-SD-Google-Colab/DataFiles/style.css\", \"/content/automatic/extensions-builtin/sd-artists-ui-tweak/\")\n",
        "\n",
        "def move_config_files():\n",
        "    Start_with_ControlNet = \"No\"  # @param [\"No\", \"Yes\"]\n",
        "\n",
        "    # Check if \"/content/automatic/ui-config.json\" exists and remove it if it does\n",
        "    if os.path.exists(\"/content/automatic/config.json\"):\n",
        "        os.remove(\"/content/automatic/config.json\")\n",
        "\n",
        "    if Start_with_ControlNet == \"No\":\n",
        "        # Copy the file \"/content/Vlad-SD-Google-Colab/SD Original/No CNet/config.json\" to \"/content/automatic\"\n",
        "        source_file = \"/content/Vlad-SD-Google-Colab/SD Original/No CNet/config.json\"\n",
        "        destination_file = \"/content/automatic/config.json\"\n",
        "        shutil.copy(source_file, destination_file)\n",
        "    elif Start_with_ControlNet == \"Yes\":\n",
        "        # Copy the file \"/content/Vlad-SD-Google-Colab/SD Original/config.json\" to \"/content/automatic\"\n",
        "        source_file = \"/content/Vlad-SD-Google-Colab/SD Original/config.json\"\n",
        "        destination_file = \"/content/automatic/config.json\"\n",
        "        shutil.copy(source_file, destination_file)\n",
        "    else:\n",
        "        print(\"Invalid value for Start_with_ControlNet. Please choose either 'No' or 'Yes'.\")\n",
        "\n",
        "    # Move \"/content/Vlad-SD-Google-Colab/SD Original/ui-config.json\" to \"/content/automatic\"\n",
        "    shutil.move(\"/content/Vlad-SD-Google-Colab/SD Original/ui-config.json\", \"/content/automatic\")\n",
        "    clear_output()\n",
        "\n",
        "def install_jemalloc():\n",
        "    %cd /content/automatic/\n",
        "    !apt -y update -qq\n",
        "    !apt -y install libjemalloc-dev\n",
        "    %env LD_PRELOAD=/usr/lib/x86_64-linux-gnu/libjemalloc.so.2\n",
        "    clear_output()\n",
        "\n",
        "def download_model():\n",
        "    %cd /content/automatic/models/\n",
        "    !mkdir -p Stable-diffusion\n",
        "    !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/Lykon/DreamShaper/resolve/main/DreamShaper_7_pruned.safetensors  -d /content/automatic/models/Stable-diffusion/ -o DreamShaper_7_pruned.safetensors\n",
        "    clear_output()\n",
        "\n",
        "def connect_to_drive():\n",
        "    %cd /content\n",
        "    drive.mount('/content/drive')\n",
        "    clear_output()\n",
        "\n",
        "# Check GPU\n",
        "start_colab = int(time.time()) - 5\n",
        "check_gpu()\n",
        "\n",
        "# Clone repositories\n",
        "clone_repositories()\n",
        "\n",
        "# Pip Install Req\n",
        "install_requirements()\n",
        "\n",
        "# Install jemalloc and its development package\n",
        "install_jemalloc()\n",
        "\n",
        "# Ekstension Install\n",
        "install_extensions()\n",
        "\n",
        "# Clone MiDaS\n",
        "clone_MiDaS()\n",
        "\n",
        "# Update sd-artists style css\n",
        "update_style_css()\n",
        "\n",
        "# Move config files\n",
        "move_config_files()\n",
        "\n",
        "# Download Model\n",
        "download_model()\n",
        "\n",
        "# Connect to Google Drive\n",
        "connect_to_drive()\n",
        "\n",
        "%cd /content/automatic\n",
        "!git show --oneline -s\n",
        "print(\"✅ Done\", \"success\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "H3jfcR6sXfuq"
      },
      "source": [
        "___\n",
        "___"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# STEP 2️⃣.1️⃣: Perlengkapan ControlNet Models, VAE, dan UPSCALERs + Install Extensions\n"
      ],
      "metadata": {
        "id": "uLkmpa1_99LX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#@markdown #Optional🎲: Pre-Install Extensions\n",
        "#@markdown >**Note: <font color=\"red\">Tanggung sendiri jika terjadi ERROR setelah install Extensions</font> 👈\n",
        "\n",
        "from IPython.display import clear_output\n",
        "import os\n",
        "import urllib.request\n",
        "\n",
        "Extensions = \"None\" #@param [\"None\", \"3d-open-pose-editor\", \"deforum\", \"SAG\", \"depth-lib\", \"huggingface\", \"additional-networks\", \"infinite-image-browsing\", \"roop\", \"civitai-browser\", \"TemporalKit\", \"All Extensions\"]\n",
        "\n",
        "def git_clone_from_file(extension):\n",
        "    file_path = f\"/content/Vlad-SD-Google-Colab/DataFiles/Extensions/{extension}.txt\"\n",
        "    if os.path.exists(file_path):\n",
        "        with open(file_path) as f:\n",
        "            repo_url = f.read().strip()\n",
        "        destination = f\"/content/automatic/extensions/{extension}\"\n",
        "        !git clone --quiet $repo_url $destination\n",
        "        print(f\"Success install '{extension}'\")\n",
        "    else:\n",
        "        print(f\"Error: '{extension}.txt' file not found.\")\n",
        "\n",
        "def install_roop():\n",
        "    git_clone_from_file(\"roop\")\n",
        "    print(\"Success install 'roop'\")\n",
        "\n",
        "def install_temporal_kit():\n",
        "    git_clone_from_file(\"TemporalKit\")\n",
        "    !sudo curl -L --silent https://github.com/BtbN/FFmpeg-Builds/releases/download/latest/ffmpeg-master-latest-linux64-gpl.tar.xz -o /usr/local/bin/ffmpeg.tar.xz\n",
        "    clear_output()\n",
        "    %cd /usr/local/bin/\n",
        "    clear_output()\n",
        "    !7z e /usr/local/bin/ffmpeg.tar.xz\n",
        "    clear_output()\n",
        "    !7z e /usr/local/bin/ffmpeg.tar\n",
        "    clear_output()\n",
        "    !sudo chmod a+rx /usr/local/bin/ffmpeg\n",
        "    clear_output()\n",
        "    %cd /content/\n",
        "    !sudo curl -L --silent https://mkvtoolnix.download/appimage/MKVToolNix_GUI-70.0.0-x86_64.AppImage -o /usr/local/bin/MKVToolNix_GUI-70.0.0-x86_64.AppImage\n",
        "    !sudo chmod u+rx /usr/local/bin/MKVToolNix_GUI-70.0.0-x86_64.AppImage\n",
        "    !sudo ln -s /usr/local/bin/MKVToolNix_GUI-70.0.0-x86_64.AppImage /usr/local/bin/mkvmerge\n",
        "    !sudo chmod a+rx /usr/local/bin/mkvmerge\n",
        "    clear_output()\n",
        "\n",
        "    # Download latest FFmpeg static build.\n",
        "    exist = !which ffmpeg\n",
        "    if not exist:\n",
        "        !curl --silent https://johnvansickle.com/ffmpeg/releases/ffmpeg-release-amd64-static.tar.xz -o ffmpeg.tar.xz \\\n",
        "        && tar -xf ffmpeg.tar.xz && rm ffmpeg.tar.xz\n",
        "        ffmdir = !find . -iname ffmpeg-*-static\n",
        "        path = os.environ['PATH']\n",
        "        path = path + ':' + ffmdir[0]\n",
        "        os.environ['PATH'] = path\n",
        "\n",
        "    !which ffmpeg\n",
        "    !pip install --quiet ffmpy\n",
        "    print(\"Success install 'TemporalKit'\")\n",
        "\n",
        "# Download the model file if \"roop\" is selected\n",
        "if Extensions == \"roop\":\n",
        "    roop_path = '/content/automatic/models/insightface'\n",
        "\n",
        "    # Ensure the folder exists\n",
        "    if not os.path.exists(roop_path):\n",
        "        os.makedirs(roop_path)\n",
        "\n",
        "    # Change to the download directory\n",
        "    os.chdir(roop_path)\n",
        "\n",
        "    inswapper128model_url = 'https://github.com/facefusion/facefusion-assets/releases/download/models/inswapper_128.onnx'\n",
        "    inswapper128model_filename = os.path.basename(inswapper128model_url)\n",
        "\n",
        "    # Use urllib.request to download the model with content disposition\n",
        "    urllib.request.urlretrieve(inswapper128model_url, os.path.join(roop_path, inswapper128model_filename))\n",
        "\n",
        "    # Check if the model file was downloaded successfully\n",
        "    if os.path.exists(os.path.join(roop_path, inswapper128model_filename)):\n",
        "        print(f\"Downloaded '{inswapper128model_filename}' to '{roop_path}'\")\n",
        "    else:\n",
        "        print(f\"Failed to download '{inswapper128model_filename}'\")\n",
        "\n",
        "    # Change back to the original working directory\n",
        "    os.chdir('/content')\n",
        "\n",
        "# Extra code to download and extract zip file after git clone\n",
        "if Extensions == \"depth-lib\":\n",
        "    zip_url = \"https://civitai.com/api/download/models/71811\"\n",
        "    destination = f\"/content/automatic/extensions/{Extensions}/maps/\"\n",
        "\n",
        "    # Download the zip file using wget with content-disposition\n",
        "    !wget --content-disposition $zip_url -P /content/\n",
        "\n",
        "    # Extract the zip file\n",
        "    import zipfile\n",
        "\n",
        "    zip_file_path = \"/content/900HandsLibraryForDepth_v10.zip\"\n",
        "    with zipfile.ZipFile(zip_file_path, 'r') as zip_ref:\n",
        "        zip_ref.extractall(destination)\n",
        "\n",
        "    # Delete the zip file\n",
        "    os.remove(zip_file_path)\n",
        "\n",
        "    print(f\"Success downloading and extracting files for '{Extensions}'\")\n",
        "\n",
        "if Extensions == \"None\":\n",
        "    # Skip all code and exit\n",
        "    pass\n",
        "\n",
        "elif Extensions == \"All Extensions\":\n",
        "    %cd /content/automatic/extensions/\n",
        "    extensions_list = [\"3d-open-pose-editor\", \"deforum\", \"SAG\", \"depth-lib\", \"huggingface\", \"additional-networks\", \"infinite-image-browsing\", \"roop\", \"civitai-browser\", \"TemporalKit\"]\n",
        "    for extension in extensions_list:\n",
        "        if extension == \"civitai-browser\":\n",
        "            !git clone --quiet https://github.com/Vetchems/sd-civitai-browser\n",
        "            print(\"Success install 'civitai-browser'\")\n",
        "        else:\n",
        "            git_clone_from_file(extension)\n",
        "\n",
        "else:\n",
        "    %cd /content/automatic/extensions/\n",
        "    if Extensions == \"civitai-browser\":\n",
        "        !git clone --quiet https://github.com/Vetchems/sd-civitai-browser\n",
        "        print(\"Success install 'civitai-browser'\")\n",
        "    else:\n",
        "        git_clone_from_file(Extensions)\n",
        "\n",
        "clear_output()\n",
        "print(\"✅ Done\", \"success\")"
      ],
      "metadata": {
        "cellView": "form",
        "id": "41nGRTen2fSG"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "9b9F3vRe3VzE",
        "cellView": "form"
      },
      "outputs": [],
      "source": [
        "#@markdown #Optional🎲: Controlnet 1.1 SD1.5 Models install\n",
        "#@markdown **Note: Pilih Model ControlNet Seperlunya atau Download \"All Models (21GB)\".\n",
        "\n",
        "import os\n",
        "import subprocess\n",
        "import shutil\n",
        "from tqdm.auto import tqdm\n",
        "\n",
        "# Define paths as variables\n",
        "controlnet_rename_path = \"/content/Vlad-SD-Google-Colab/DataFiles/CNet Rename/controlnet-rename.txt\"\n",
        "extensions_builtin_folder_path = \"/content/automatic/extensions-builtin\"\n",
        "\n",
        "# Function to check if the folder name is the same as the new folder name and rename if needed\n",
        "def rename_folder_if_needed(folder_path, new_folder_name):\n",
        "    folder_name = os.path.basename(folder_path)\n",
        "    if folder_name == new_folder_name:\n",
        "        print(\"Folder name is already the same. Skipping the renaming process.\")\n",
        "    else:\n",
        "        old_folder_path = os.path.join(folder_path, new_folder_name)\n",
        "        new_folder_path = os.path.join(folder_path, \"sd-controlnet\")\n",
        "        try:\n",
        "            shutil.move(old_folder_path, new_folder_path)\n",
        "            print(f\"Folder renamed from '{new_folder_name}' to 'sd-controlnet'.\")\n",
        "        except OSError as e:\n",
        "            if e.errno == 39:\n",
        "                print(\"Destination folder is not empty. Skipping the renaming process.\")\n",
        "            else:\n",
        "                print(f\"An error occurred: {e}\")\n",
        "        except Exception as e:\n",
        "            print(f\"An error occurred: {e}\")\n",
        "\n",
        "# Read the contents of the txt file and construct the new folder name\n",
        "with open(controlnet_rename_path, 'r') as file:\n",
        "    new_folder_name = file.read().strip()\n",
        "\n",
        "# Rename the folder if needed\n",
        "rename_folder_if_needed(extensions_builtin_folder_path, new_folder_name)\n",
        "\n",
        "clear_output()\n",
        "\n",
        "# Download The models\n",
        "Model = \"None\" #@param [\"None\", \"Canny\", \"Depth\", \"Lineart\", \"MLSD\", \"Normal\", \"OpenPose\", \"Scribble\", \"Seg\", \"ip2p\", \"Shuffle\", \"Inpaint\", \"Softedge\", \"Lineart_Anime\", \"Tile\", \"All Models (21GB)\"]\n",
        "\n",
        "model_urls = {\n",
        "    \"Canny\": 'https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11p_sd15_canny.pth',\n",
        "    \"Depth\": 'https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11f1p_sd15_depth.pth',\n",
        "    \"Lineart\": 'https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11p_sd15_lineart.pth',\n",
        "    \"MLSD\": 'https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11p_sd15_mlsd.pth',\n",
        "    \"Normal\": 'https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11p_sd15_normalbae.pth',\n",
        "    \"OpenPose\": 'https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11p_sd15_openpose.pth',\n",
        "    \"Scribble\": 'https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11p_sd15_scribble.pth',\n",
        "    \"Seg\": 'https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11p_sd15_seg.pth',\n",
        "    \"ip2p\": 'https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11e_sd15_ip2p.pth',\n",
        "    \"Shuffle\": 'https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11e_sd15_shuffle.pth',\n",
        "    \"Inpaint\": 'https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11p_sd15_inpaint.pth',\n",
        "    \"Softedge\": 'https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11p_sd15_softedge.pth',\n",
        "    \"Lineart_Anime\": 'https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11p_sd15s2_lineart_anime.pth',\n",
        "    \"Tile\": 'https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11f1e_sd15_tile.pth',\n",
        "    # Add other model URLs here...\n",
        "}\n",
        "\n",
        "output_path = \"/content/automatic/extensions-builtin/sd-controlnet/models/\"\n",
        "os.makedirs(output_path, exist_ok=True)  # Create the output directory if it doesn't exist\n",
        "\n",
        "def download_model(model_url, output_path):\n",
        "    filename = os.path.basename(model_url)\n",
        "    output_file = os.path.join(output_path, filename)\n",
        "    subprocess.run(['aria2c', '-x', '16', '-s', '16', '-o', filename, '-d', output_path, model_url]) # Download with aria2c\n",
        "    return filename\n",
        "\n",
        "if Model == \"All Models (21GB)\":\n",
        "    for model in model_urls:\n",
        "        model_url = model_urls[model]\n",
        "        download_model(model_url, output_path)\n",
        "    print(\"✓ Done\", \"success\")\n",
        "elif Model != \"None\":\n",
        "    model_url = model_urls.get(Model)\n",
        "    if model_url:\n",
        "        download_model(model_url, output_path)\n",
        "        print(\"✓ Done\", \"success\")\n",
        "    else:\n",
        "        print(\"Invalid model selected.\")\n",
        "else:\n",
        "    clear_output()\n",
        "    print(\"No Model selected. Finish...\")\n",
        "\n",
        "# Read the contents of the txt file and construct the new folder path\n",
        "with open(controlnet_rename_path, 'r') as file:\n",
        "    new_folder_name = file.read().strip()\n",
        "new_folder_path = os.path.join(extensions_builtin_folder_path, new_folder_name)\n",
        "\n",
        "# Check if the old folder exists and if the folder names are different, then rename\n",
        "old_folder_path = os.path.join(extensions_builtin_folder_path, \"sd-controlnet\")\n",
        "if os.path.exists(old_folder_path) and os.path.basename(old_folder_path) != new_folder_name:\n",
        "    shutil.move(old_folder_path, new_folder_path)\n",
        "    print(f\"Folder renamed from 'sd-controlnet' to '{new_folder_name}'.\")\n",
        "elif os.path.basename(old_folder_path) == new_folder_name:\n",
        "    print(\"Folder name is already the same. No need to rename.\")\n",
        "else:\n",
        "    print(\"The folder does not exist.\")\n",
        "\n",
        "clear_output()\n",
        "print(\"✅ Done\", \"success\")\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "nEnR3xY-9Ily",
        "cellView": "form"
      },
      "outputs": [],
      "source": [
        "#@markdown #Optional🎲: Download VAE Collection (+Negtive Embedings)\n",
        "#@markdown  **Note: Pilih Model ControlNet Seperlunya atau Download \"All VAE (6,1GB) + Negtive Embedings\"\n",
        "\n",
        "%cd /content/automatic/models\n",
        "!mkdir -p embeddings/negative\n",
        "%cd /content/automatic/models/embeddings/negative/\n",
        "!git clone --quiet https://huggingface.co/embed/negative\n",
        "\n",
        "import os\n",
        "import urllib.request\n",
        "from IPython.display import clear_output\n",
        "\n",
        "VAE = \"All VAE (6,1GB)\" #@param [\"None\", \"WD-v2.vae.pt\", \"blessed-fix.vae.pt\", \"blessed.vae.pt\", \"blessed2.vae.pt\", \"clearvae_main.safetensors\", \"cute_vae.safetensors\", \"grapefruitVAE_v1.pt\", \"kl-f8-anime.ckpt\", \"kl-f8-anime2.ckpt\", \"nai.vae.pt\", \"orangemix.vae.pt\", \"pastel-waifu-diffusion.vae.pt\", \"rmada-cold-vae.ckpt\", \"vae-ft-mse-840000-ema-pruned.ckpt\", \"vaeextremecolors_v10.pt\", \"All VAE (6,1GB)\"]\n",
        "\n",
        "VAE_urls = {\n",
        "    \"WD-v2.vae.pt\": 'https://huggingface.co/Kefasu/sd-vae-collection/resolve/main/WD-v2.vae.pt',\n",
        "    \"blessed-fix.vae.pt\": 'https://huggingface.co/Kefasu/sd-vae-collection/resolve/main/blessed-fix.vae.pt',\n",
        "    \"blessed.vae.pt\": 'https://huggingface.co/Kefasu/sd-vae-collection/resolve/main/blessed.vae.pt',\n",
        "    \"blessed2.vae.pt\": 'https://huggingface.co/Kefasu/sd-vae-collection/resolve/main/blessed2.vae.pt',\n",
        "    \"clearvae_main.safetensors\": 'https://huggingface.co/Kefasu/sd-vae-collection/resolve/main/clearvae_main.safetensors',\n",
        "    \"cute_vae.safetensors\": 'https://huggingface.co/Kefasu/sd-vae-collection/resolve/main/cute%20vae.safetensors',\n",
        "    \"grapefruitVAE_v1.pt\": 'https://huggingface.co/Kefasu/sd-vae-collection/resolve/main/grapefruitVAE_v1.pt',\n",
        "    \"kl-f8-anime.ckpt\": 'https://huggingface.co/Kefasu/sd-vae-collection/resolve/main/kl-f8-anime.ckpt',\n",
        "    \"kl-f8-anime2.ckpt\": 'https://huggingface.co/Kefasu/sd-vae-collection/resolve/main/kl-f8-anime2.ckpt',\n",
        "    \"nai.vae.pt\": 'https://huggingface.co/Kefasu/sd-vae-collection/resolve/main/nai.vae.pt',\n",
        "    \"orangemix.vae.pt\": 'https://huggingface.co/Kefasu/sd-vae-collection/resolve/main/orangemix.vae.pt',\n",
        "    \"pastel-waifu-diffusion.vae.pt\": 'https://huggingface.co/Kefasu/sd-vae-collection/resolve/main/pastel-waifu-diffusion.vae.pt',\n",
        "    \"rmada-cold-vae.ckpt\": 'https://huggingface.co/Kefasu/sd-vae-collection/resolve/main/rmada-cold-vae.ckpt',\n",
        "    \"vae-ft-mse-840000-ema-pruned.ckpt\": 'https://huggingface.co/Kefasu/sd-vae-collection/resolve/main/vae-ft-mse-840000-ema-pruned.ckpt',\n",
        "    \"vaeextremecolors_v10.pt\": 'https://huggingface.co/Kefasu/sd-vae-collection/resolve/main/vaeextremecolors_v10.pt'\n",
        "}\n",
        "\n",
        "output_path = \"/content/automatic/models/VAE/\"\n",
        "\n",
        "os.makedirs(output_path, exist_ok=True)  # Create the output directory if it doesn't exist\n",
        "\n",
        "def download_model(model_url, output_path):\n",
        "    filename = os.path.basename(model_url)\n",
        "    output_file = os.path.join(output_path, filename)\n",
        "    urllib.request.urlretrieve(model_url, output_file)\n",
        "    return filename\n",
        "\n",
        "if VAE == \"All VAE (6,1GB)\":\n",
        "    for model in VAE_urls:\n",
        "        model_url = VAE_urls[model]\n",
        "        download_model(model_url, output_path)\n",
        "    print(\"✓ Done\", \"success\")\n",
        "elif VAE != \"None\":\n",
        "    model_url = VAE_urls.get(VAE)\n",
        "    download_model(model_url, output_path)\n",
        "    print(\"✓ Done\", \"success\")\n",
        "else:\n",
        "    clear_output()\n",
        "    print(\"No VAE selected. Finish...\")\n",
        "\n",
        "# Clear the output to keep the notebook clean\n",
        "clear_output()\n",
        "print(\"✅ Done\", \"success\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@markdown #Optional🎲: Download UPSCALERs\n",
        "\n",
        "import os\n",
        "import urllib.request\n",
        "from IPython.display import clear_output\n",
        "\n",
        "Upscalers = \"All Upscalers (2,3GB)\" #@param [\"None\", \"4x-UltraSharp.pth\", \"4x_CountryRoads_377000_G.pth\", \"4x_Fatality_Comix_260000_G.pth\", \"4x_RealisticRescaler_100000_G.pth\", \"4x_Valar_v1.pth\", \"4x_fatal_Anime_500000_G.pth\", \"4x_foolhardy_Remacri.pth\", \"A_ESRGAN_Single.pth\", \"LADDIER1_282500_G.pth\", \"WaifuGAN_v3_30000.pth\", \"lollypop.pth\", \"sudo_rife4_269.662_testV1_scale1.pth\", \"Nickelback [Upscaler Pack]\", \"NMKD [Upscaler Pack]\", \"NoiseToner [Upscaler Pack]\", \"PSNR [Upscaler Pack]\", \"UniversalUpscalerV2 [Upscaler Pack]\", \"All Upscalers (2,3GB)\"]\n",
        "\n",
        "upscalers_urls = {\n",
        "    \"4x-UltraSharp.pth\": 'https://huggingface.co/uwg/upscaler/resolve/main/ESRGAN/4x-UltraSharp.pth',\n",
        "    \"4x_CountryRoads_377000_G.pth\": 'https://huggingface.co/uwg/upscaler/resolve/main/ESRGAN/4x_CountryRoads_377000_G.pth',\n",
        "    \"4x_Fatality_Comix_260000_G.pth\": 'https://huggingface.co/uwg/upscaler/resolve/main/ESRGAN/4x_Fatality_Comix_260000_G.pth',\n",
        "    \"4x_RealisticRescaler_100000_G.pth\": 'https://huggingface.co/uwg/upscaler/resolve/main/ESRGAN/4x_RealisticRescaler_100000_G.pth',\n",
        "    \"4x_Valar_v1.pth\": 'https://huggingface.co/uwg/upscaler/resolve/main/ESRGAN/4x_Valar_v1.pth',\n",
        "    \"4x_fatal_Anime_500000_G.pth\": 'https://huggingface.co/uwg/upscaler/resolve/main/ESRGAN/4x_fatal_Anime_500000_G.pth',\n",
        "    \"4x_foolhardy_Remacri.pth\": 'https://huggingface.co/uwg/upscaler/resolve/main/ESRGAN/4x_foolhardy_Remacri.pth',\n",
        "    \"A_ESRGAN_Single.pth\": 'https://huggingface.co/uwg/upscaler/resolve/main/ESRGAN/A_ESRGAN_Single.pth',\n",
        "    \"LADDIER1_282500_G.pth\": 'https://huggingface.co/uwg/upscaler/resolve/main/ESRGAN/LADDIER1_282500_G.pth',\n",
        "    \"WaifuGAN_v3_30000.pth\": 'https://huggingface.co/uwg/upscaler/resolve/main/ESRGAN/WaifuGAN_v3_30000.pth',\n",
        "    \"lollypop.pth\": 'https://huggingface.co/uwg/upscaler/resolve/main/ESRGAN/lollypop.pth',\n",
        "    \"sudo_rife4_269.662_testV1_scale1.pth\": 'https://huggingface.co/uwg/upscaler/resolve/main/ESRGAN/sudo_rife4_269.662_testV1_scale1.pth',\n",
        "}\n",
        "\n",
        "upscalers_pack_urls = {\n",
        "    \"Nickelback [Upscaler Pack]\": '/content/Vlad-SD-Google-Colab/Upscaler Pack/Nickelback [Upscaler Pack].txt',\n",
        "    \"NMKD [Upscaler Pack]\": '/content/Vlad-SD-Google-Colab/Upscaler Pack/NMKD [Upscaler Pack].txt',\n",
        "    \"NoiseToner [Upscaler Pack]\": '/content/Vlad-SD-Google-Colab/Upscaler Pack/NoiseToner [Upscaler Pack].txt',\n",
        "    \"PSNR [Upscaler Pack]\": '/content/Vlad-SD-Google-Colab/Upscaler Pack/PSNR [Upscaler Pack].txt',\n",
        "    \"UniversalUpscalerV2 [Upscaler Pack]\": '/content/Vlad-SD-Google-Colab/Upscaler Pack/UniversalUpscalerV2 [Upscaler Pack].txt',\n",
        "}\n",
        "\n",
        "output_path = \"/content/automatic/models/ESRGAN/\"\n",
        "\n",
        "os.makedirs(output_path, exist_ok=True)  # Create the output directory if it doesn't exist\n",
        "\n",
        "def download_model(model_url, output_path):\n",
        "    if model_url is None:\n",
        "        return None\n",
        "\n",
        "    filename = os.path.basename(model_url)\n",
        "    output_file = os.path.join(output_path, filename)\n",
        "    urllib.request.urlretrieve(model_url, output_file)\n",
        "    return filename\n",
        "\n",
        "if Upscalers == \"All Upscalers (2,3GB)\":\n",
        "    for model in upscalers_urls:\n",
        "        model_url = upscalers_urls[model]\n",
        "        download_model(model_url, output_path)\n",
        "\n",
        "    for model in upscalers_pack_urls:\n",
        "        txt_file_path = upscalers_pack_urls[model]\n",
        "        with open(txt_file_path, 'r') as file:\n",
        "            urls = file.read().splitlines()\n",
        "        for url in urls:\n",
        "            download_model(url, output_path)\n",
        "\n",
        "    print(\"✓ Done\", \"success\")\n",
        "elif Upscalers != \"None\":\n",
        "    if Upscalers in upscalers_pack_urls:\n",
        "        txt_file_path = upscalers_pack_urls[Upscalers]\n",
        "        with open(txt_file_path, 'r') as file:\n",
        "            urls = file.read().splitlines()\n",
        "        for url in urls:\n",
        "            download_model(url, output_path)\n",
        "        print(\"✓ Done\", \"success\")\n",
        "    else:\n",
        "        model_url = upscalers_urls.get(Upscalers)\n",
        "        download_model(model_url, output_path)\n",
        "        print(\"✓ Done\", \"success\")\n",
        "else:\n",
        "    clear_output()\n",
        "    print(\"No Upscaler selected. Finish...\")\n",
        "\n",
        "clear_output()\n",
        "print(\"✅ Done\", \"success\")"
      ],
      "metadata": {
        "cellView": "form",
        "id": "Z0ecLKkVpQYu"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "<details>\n",
        "<summary><font size=\"5\"><font color=\"#00CED1\"> <b>Info UPSCALERs PACK List :</b></font> ( Klik diSini untuk Lihat )</font></summary>\n",
        "\n",
        "- Nickelback [Upscaler Pack]:\n",
        "  - 4x_Nickelback_70000G.pth\n",
        "  - 4x_NickelbackFS_72000_G.pth\n",
        "\n",
        "- NMKD [Upscaler Pack]:\n",
        "  - 1x_NMKD-BrightenRedux_200k.pth\n",
        "  - 1x_NMKD-YandereInpaint_375000_G.pth\n",
        "  - 2x_NMKD-DeGIF_210000_G.pth\n",
        "  - 4x_NMKD-Siax_200k.pth\n",
        "  - 4x_NMKD-Superscale-Artisoftject_210000_G.pth\n",
        "  - 4x_NMKD-Superscale-SP_178000_G.pth\n",
        "  - 4x_NMKD-UltraYandere-Lite_280k.pth\n",
        "  - 4x_NMKD-UltraYandere_300k.pth\n",
        "  - 4x_NMKD-UpgifLiteV2_210k.pth\n",
        "  - 4x_NMKD-YandereNeoXL_200k.pth\n",
        "  - 4x_NMKDSuperscale_Artisoft_120000_G.pth\n",
        "  - 8x_NMKD-Superscale_150000_G.pth\n",
        "  - 8x_NMKD-Typescale_175k.pth\n",
        "  - 8x_NMKD-Faces_160000_G.pth\n",
        "\n",
        "- NoiseToner [Upscaler Pack]:\n",
        "  - 1x_NoiseToner-Uniform-Detailed_100000_G.pth\n",
        "  - 1x_NoiseToner-Poisson-Detailed_108000_G.pth\n",
        "\n",
        "- PSNR [Upscaler Pack]:\n",
        "  - 4xPSNR.pth\n",
        "  - 8xPSNR.pth\n",
        "  - 16xPSNR.pth\n",
        "\n",
        "- UniversalUpscalerV2 [Upscaler Pack]:\n",
        "  - 4x_UniversalUpscalerV2-Sharper_103000_G.pth\n",
        "  - 4x_UniversalUpscalerV2-Sharp_101000_G.pth\n",
        "  - 4x_UniversalUpscalerV2-Neutral_115000_swaG.pth\n",
        "\n",
        "- LAINNYA:\n",
        "  - 4x-UltraSharp.pth\n",
        "  - 4x_CountryRoads_377000_G.pth\n",
        "  - 4x_Fatality_Comix_260000_G.pth\n",
        "  - 4x_RealisticRescaler_100000_G.pth\n",
        "  - 4x_Valar_v1.pth\n",
        "  - 4x_fatal_Anime_500000_G.pth\n",
        "  - 4x_foolhardy_Remacri.pth\n",
        "  - A_ESRGAN_Single.pth\n",
        "  - LADDIER1_282500_G.pth\n",
        "  - WaifuGAN_v3_30000.pth\n",
        "  - lollypop.pth\n",
        "  - sudo_rife4_269.662_testV1_scale1.pth\n",
        "\n",
        "</details>\n"
      ],
      "metadata": {
        "id": "QkFCit8_zYeF"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "---"
      ],
      "metadata": {
        "id": "il4nFMAfu72r"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nfB4Pe9p8xL6"
      },
      "source": [
        "# STEP 2️⃣.2️⃣: Perlengkapan Chekpoint, LoRA/LyCORIS, dan Embeddings TI\n",
        "> <font color=\"#00CED1\" size=\"5\">**Informasi**:</font>\n",
        "\n",
        "Untuk menghindari <font color=\"#CC3E3E\">**ERROR**</font> harap gunakan Tools dibwah untuk mendownload Models/Checkpoint, Sandard LoRA, LoCon/LyCORIS, ataupun Textual Inversion. Atau bisa coba gunakan \"Model Downloader\" di WebUI.\n",
        "\n",
        "# <font color=\"#ECED0C\">**Untuk Lebih dari 1 Download Pisahkan Link dengan KOMA \",\" contoh: 👇**</font>\n",
        "\n",
        "![Image in a markdown cell](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgmx1QC1QnND4x7d8erlHZzOUTxyvIZXpfoKlOL-lPwXkGYVj5RNuhyCD8lWJrSzTWJ0DXxdrywE1VFz3uMkyaHevMUUBn9CR1Zq1LAd5hX8-4rwg2o5l2Pb08kD1zsZVpLoMfwq-ERRzX2AEBxR4WEzUA0uZP2ShrQicJl4sECKQ07FGZKHZ5n_6V7E9k/s981/画像_2023-07-12_114732788.png)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "BMHP0FZ0yyu2",
        "cellView": "form"
      },
      "outputs": [],
      "source": [
        "#@markdown #Optional🧩: Models Downloader\n",
        "from IPython.display import clear_output\n",
        "import os\n",
        "import requests\n",
        "from urllib.parse import unquote\n",
        "\n",
        "def download_model(Type, DirectLink_URL):\n",
        "    if Type == \"None\" or not DirectLink_URL:\n",
        "        print(\"Skipping download as no valid Type or DirectLink_URL provided.\")\n",
        "        return\n",
        "\n",
        "    output_path = \"/content/automatic/models/\"\n",
        "\n",
        "    if Type == \"Checkpoint\":\n",
        "        output_path += \"Stable-diffusion/\"\n",
        "    elif Type == \"LoRA\":\n",
        "        output_path += \"Lora/\"\n",
        "    elif Type == \"LoCon/LyCORIS\":\n",
        "        output_path += \"LyCORIS/\"\n",
        "    elif Type == \"Textual Inversion\":\n",
        "        output_path += \"embeddings/\"\n",
        "    else:\n",
        "        print(\"Invalid type specified.\")\n",
        "        return\n",
        "\n",
        "    # Create the directories if they don't exist\n",
        "    os.makedirs(output_path, exist_ok=True)\n",
        "\n",
        "    urls = [url.strip() for url in DirectLink_URL.split(\",\")]\n",
        "\n",
        "    for url in urls:\n",
        "        response = requests.get(url, stream=True)\n",
        "\n",
        "        if response.status_code == 200:\n",
        "            content_disposition = response.headers.get('content-disposition')\n",
        "            if content_disposition:\n",
        "                filename = unquote(content_disposition.split('filename=')[1])\n",
        "            else:\n",
        "                filename = unquote(url.split(\"/\")[-1])  # Extracting the filename from the URL\n",
        "\n",
        "            # Remove double quotes and semicolons from the filename\n",
        "            filename = filename.replace('\"', '').replace(';', '')\n",
        "\n",
        "            filename = os.path.join(output_path, filename)  # Modify the filename to include the output path\n",
        "\n",
        "            if not os.path.exists(filename):\n",
        "                print(\"Downloading file:\", filename)\n",
        "                chunk_size = 5242880  # 5 MB\n",
        "                with open(filename, 'wb') as f:\n",
        "                    for chunk in response.iter_content(chunk_size=chunk_size):\n",
        "                        if chunk:\n",
        "                            f.write(chunk)\n",
        "                print(\"File downloaded successfully.\")\n",
        "            else:\n",
        "                print(\"File already exists:\", filename)\n",
        "        else:\n",
        "            print(\"Failed to download the file:\", url)\n",
        "\n",
        "    # Clear the output to keep the notebook clean\n",
        "    clear_output()\n",
        "\n",
        "    # Print the success message\n",
        "    print(\"✅ Done\", \"success\")\n",
        "\n",
        "# Call the function with the first set of parameters\n",
        "Type1 = \"Checkpoint\"  # @param [\"None\", \"Checkpoint\", \"LoRA\", \"LoCon/LyCORIS\", \"Textual Inversion\"]\n",
        "DirectLink_URL1 = \"\"  # @param {'type': 'string'}\n",
        "download_model(Type1, DirectLink_URL1)\n",
        "\n",
        "# Call the function with the second set of parameters\n",
        "Type2 = \"None\"  # @param [\"None\", \"Checkpoint\", \"LoRA\", \"LoCon/LyCORIS\", \"Textual Inversion\"]\n",
        "DirectLink_URL2 = \"\"  # @param {'type': 'string'}\n",
        "download_model(Type2, DirectLink_URL2)\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mOHgoH3xFBTt"
      },
      "source": [
        "---\n",
        "---\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# STEP 3️⃣: START\n",
        "\n",
        "> <font color=\"#ECED0C\" size=\"5\">**Informasi diBACA dulu👇**:</font>\n",
        "\n",
        "1. LoRA sudah MENJADI SATU dengan LyCORIS.\n",
        "2. Hiresfix = Second pass (+beberapa tambahan)\n",
        "3. <font color=\"#CC3E3E\">**INSTALL EKSTENSI SENDIRI**</font> di dalam WebUI untuk MENCEGAH SALAH PAHAM.\n",
        "4. Pake NGROK!!\n",
        "---"
      ],
      "metadata": {
        "id": "VOpdAUhT-LlE"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Js9xySvP334q",
        "cellView": "form"
      },
      "outputs": [],
      "source": [
        "#@markdown #Step 3️⃣🅰️ (Original SD): Launch SD.Next [`Colab UPDATE: 05 September 2023 08:06 AM (GMT+7)`]\n",
        "#@markdown ______\n",
        "import os\n",
        "import threading\n",
        "import requests\n",
        "import logging\n",
        "import urllib.request\n",
        "from pyngrok import ngrok\n",
        "from IPython.display import display, HTML\n",
        "from huggingface_hub import cached_assets_path\n",
        "from IPython.display import clear_output\n",
        "\n",
        "# --Function AntiDissconnect\n",
        "%cd /content/automatic\n",
        "clear_output()\n",
        "audio_url = \"https://raw.githubusercontent.com/KoboldAI/KoboldAI-Client/main/colab/silence.m4a\"\n",
        "# Function AntiDissconnect in the background\n",
        "def play_audio(url):\n",
        "    display(HTML(f'<audio src=\"{url}\" controls autoplay style=\"display:none\"></audio>'))\n",
        "# Create a separate thread for AntiDissconnect\n",
        "audio_thread = threading.Thread(target=play_audio, args=(audio_url,))\n",
        "audio_thread.start()\n",
        "\n",
        "# Continue with your code execution here\n",
        "# Disable logging for the pyngrok module to suppress the warnings\n",
        "logging.getLogger(\"pyngrok\").setLevel(logging.ERROR)\n",
        "\n",
        "#@markdown Copy AuthToken dari https://dashboard.ngrok.com/get-started/your-authtoken ke 👇  ( WAJIB DI ISI 👇)\n",
        "ngrok_token = \"\"  # @param {'type': 'string'}\n",
        "\n",
        "# Move the ngrok configuration file from the XDG-compliant location to the legacy location\n",
        "os.system(\"mv /root/.config/ngrok/ngrok.yml /root/.ngrok2/ngrok.yml\")\n",
        "\n",
        "# Set the ngrok configuration directory to the legacy location\n",
        "os.environ[\"NGROK_CONFIG_PATH\"] = \"/root/.ngrok2/ngrok.yml\"\n",
        "\n",
        "# Create an Event object to signal when ngrok is ready\n",
        "ngrok_ready_event = threading.Event()\n",
        "\n",
        "# Function to install ngrok via TGZ file\n",
        "def install_ngrok():\n",
        "    os.system(\"wget https://bin.equinox.io/c/4VmDzA7iaHb/ngrok-stable-linux-amd64.tgz\")\n",
        "    os.system(\"sudo tar xvzf ngrok-stable-linux-amd64.tgz -C /usr/local/bin\")\n",
        "    os.remove(\"ngrok-stable-linux-amd64.tgz\")  # Remove the TGZ file after installation\n",
        "    ngrok_ready_event.set()  # Signal that ngrok installation is complete\n",
        "\n",
        "# Function to start ngrok and print the ngrok URL when the local URL is accessible\n",
        "def start_ngrok():\n",
        "    ngrok.set_auth_token(ngrok_token)\n",
        "    public_url = ngrok.connect(7860, \"http\").public_url\n",
        "    # Convert to HTTPS by replacing \"http://\" with \"https://\"\n",
        "    public_url_https = public_url.replace(\"http://\", \"https://\", 1)  # Use count=1 to replace only the first occurrence\n",
        "\n",
        "    # Print the ngrok URL once the local URL is accessible\n",
        "    url_printed = False\n",
        "    while True:\n",
        "        try:\n",
        "            response = requests.get(\"http://127.0.0.1:7860\")\n",
        "            if response.status_code == 200 and not url_printed:\n",
        "                print(\"+++ Subscribe to: https://youtube.com/@yosiakefas\")\n",
        "                print(\"Ngrok URL:\", public_url_https)\n",
        "                print(\"+++\")\n",
        "                url_printed = True  # Set the flag to indicate that the URL has been printed\n",
        "                break\n",
        "        except requests.ConnectionError:\n",
        "            pass\n",
        "\n",
        "    ngrok_ready_event.set()  # Signal that ngrok tunnel is ready\n",
        "\n",
        "# Install ngrok via TGZ file in a separate thread\n",
        "install_thread = threading.Thread(target=install_ngrok)\n",
        "install_thread.start()\n",
        "\n",
        "# Wait for ngrok installation to complete\n",
        "ngrok_ready_event.wait()\n",
        "\n",
        "# Create a Timer to allow the main thread to continue after 5 seconds\n",
        "timer = threading.Timer(1, lambda: None)  # A dummy timer function to unblock the main thread after 5 seconds\n",
        "\n",
        "# Start ngrok in a separate thread\n",
        "start_thread = threading.Thread(target=start_ngrok)\n",
        "start_thread.start()\n",
        "\n",
        "# Start the timer to unblock the main thread after 5 seconds\n",
        "timer.start()\n",
        "\n",
        "# Wait for the main thread to unblock after the timer expires\n",
        "timer.join()\n",
        "\n",
        "# Continue with the next code here\n",
        "# Your next code here...\n",
        "#@markdown ______\n",
        "#@markdown Silahkan Ganti Jika punya Config Sendiri 👇\n",
        "config = \"/content/automatic/config.json\"  # @param {'type': 'string'}\n",
        "uiconfig = \"/content/automatic/ui-config.json\"  # @param {'type': 'string'}\n",
        "\n",
        "%env LD_PRELOAD=/usr/lib/x86_64-linux-gnu/libjemalloc.so.2\n",
        "!COMMANDLINE_ARGS=\"--share --no-hashing --insecure --config $config --ui-config $uiconfig\" REQS_FILE=\"requirements.txt\" python launch.py\n",
        "\n",
        "# Terminate ngrok and release any running tunnels\n",
        "ngrok.kill()"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "---"
      ],
      "metadata": {
        "id": "k-RMefOX3t7t"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "m7ur_ckUKK4o"
      },
      "source": [
        "</br>\n",
        "\n",
        "</br>\n",
        "\n",
        "## **<center>DiBuat dengan<font color=\"#FF4BD4\"> *SEPENUH HATI* ❤️</font> by [youtube.com/@yosiakefas](https://youtube.com/@yosiakefa)**\n",
        "<center><a href=\"https://trakteer.id/yosiakefas/tip\" target=\"_blank\"><img id=\"wse-buttons-preview\" src=\"https://cdn.trakteer.id/images/embed/trbtn-blue-5.png\" height=\"60\" style=\"border: 0px; height: 60px;\" alt=\"Trakteer Saya\"></a></center>\n",
        "\n",
        "<div align=\"center\">\n",
        " <a href=\"https://www.youtube.com/channel/UCsqTcFMsAlegRsUyfyKe_5A\"><img src=\"https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiZxKLHX32VYBBOvxvKUDka6uX0wKYYg46EurNzQBUHjaxd2dSJ82paUaJ1OTzpMMt4R7KUuvsbcOLuAg_9NJ1WaRJev8vmRhWea4xfg0AhjSaX2sp3ZFZGD490AArNICVDqzYvrjTqWbKFHxFLE2AYBVaIrGvkwPTqJCroDTvEb43sNuM5wHHCecd6/s350/subscribe-5408999_640.png\" width=\"310\"/></a>ㅤㅤ\n",
        " <a href=\"https://discord.gg/j8qmYPAGQh\"><img src=\"https://cdn.shopify.com/s/files/1/0562/9329/4253/files/Discord_button_480x480.png\" width=\"350\"/></a></div>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Advance Tools 🔧"
      ],
      "metadata": {
        "id": "UWJd3wjf32ar"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#@markdown #Tools🔧: Remove Images MetaData【 UNTESTED! 】\n",
        "#@markdown Support Batch Process or Single Image. If Batch Process input Folder Path!\n",
        "from PIL import Image\n",
        "import os\n",
        "\n",
        "def remove_metadata(image_path):\n",
        "    try:\n",
        "        img = Image.open(image_path)\n",
        "        img_without_metadata = Image.new(img.mode, img.size)\n",
        "        img_without_metadata.putdata(list(img.getdata()))\n",
        "\n",
        "        output_filename = os.path.splitext(os.path.basename(image_path))[0] + \" - Removed MetaData\"\n",
        "        output_path = os.path.join(os.path.dirname(image_path), output_filename)\n",
        "\n",
        "        img_without_metadata.save(output_path + os.path.splitext(image_path)[1])\n",
        "\n",
        "        print(f\"Successfully processed: {image_path}\")\n",
        "    except Exception as e:\n",
        "        print(f\"Failed to process: {image_path}. Error: {e}\")\n",
        "\n",
        "def process_images(input_path):\n",
        "    if os.path.isfile(input_path):\n",
        "        remove_metadata(input_path)\n",
        "    elif os.path.isdir(input_path):\n",
        "        for root, _, files in os.walk(input_path):\n",
        "            for file in files:\n",
        "                if file.lower().endswith(('.jpg', '.png', '.tiff', '.jp2', '.webp')):\n",
        "                    image_path = os.path.join(root, file)\n",
        "                    remove_metadata(image_path)\n",
        "    else:\n",
        "        print(\"Invalid input. Please provide a valid file or folder path.\")\n",
        "\n",
        "# Set the input path here: # Set the path to your image file or folder containing images\n",
        "Input_Path =  \"\"  # @param {'type': 'string'}\n",
        "\n",
        "process_images(Input_Path)\n"
      ],
      "metadata": {
        "cellView": "form",
        "id": "8S30U2w_34wd"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@markdown #Tools🔧: Copy Model From Google Drive【 UNTESTED! 】\n",
        "#@markdown \"Copy Path\" Model yg mau diCopy ke \"File_PATH\"\n",
        "\n",
        "import shutil\n",
        "import os\n",
        "\n",
        "# Parameters\n",
        "Type = \"Checkpoint\"  # @param [\"None\", \"Checkpoint\", \"LoRA\", \"LoCon/LyCORIS\", \"Textual Inversion\"]\n",
        "File_PATH = \"\"  # @param {'type': 'string'}\n",
        "\n",
        "output_path = \"/content/automatic/models/\"\n",
        "\n",
        "if Type == \"Checkpoint\":\n",
        "    output_path += \"Stable-diffusion/\"\n",
        "elif Type == \"LoRA\":\n",
        "    output_path += \"Lora/\"\n",
        "elif Type == \"LoCon/LyCORIS\":\n",
        "    output_path += \"LyCORIS/\"\n",
        "elif Type == \"Textual Inversion\":\n",
        "    output_path += \"embeddings/\"\n",
        "else:\n",
        "    print(\"Invalid type specified.\")\n",
        "\n",
        "# Check if the source file exists\n",
        "if os.path.isfile(File_PATH):\n",
        "    # Check if the destination folder exists, create it if not\n",
        "    if not os.path.exists(output_path):\n",
        "        os.makedirs(output_path)\n",
        "\n",
        "    # Copy the file to the destination folder\n",
        "    shutil.copy(File_PATH, output_path)\n",
        "    print(f\"File copied to {output_path}\")\n",
        "else:\n",
        "    print(f\"Source file {File_PATH} does not exist.\")\n"
      ],
      "metadata": {
        "cellView": "form",
        "id": "DCV2rQ-fuFvj"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "---"
      ],
      "metadata": {
        "id": "u7MjUzV-6EyX"
      }
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "gpuType": "T4",
      "private_outputs": true,
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}