StableDiffusionUI_Colab_old.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6jOorUsRpv3z"
      },
      "source": [
        "# AUTOMATIC1111 Stable Diffusion WebUI for Google Colab\n",
        "\n",
        "* With models 1.5, 1.5-inpainting, waifu division and VAE, Anything V3, Gigachad\n",
        "* Optionally download your model from Google Drive or MEGA\n",
        "* Optional Dreambooth extension (beta)\n",
        "\n",
        "Github: https://github.com/Miraculix200/StableDiffusionUI_Colab"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "T3LJsNi5rAe8"
      },
      "source": [
        "# Check GPU availability\n",
        "\n",
        "Don't try to run anything below this cell if this cell shows an error"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "eAy6wA49rCga"
      },
      "outputs": [],
      "source": [
        "!nvidia-smi --query-gpu=name,memory.total,memory.free --format=csv,noheader"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "I72bK2eRpZbe"
      },
      "source": [
        "# Clone AUTOMATIC1111 webui repository"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "v9mbG1L-pPUy"
      },
      "outputs": [],
      "source": [
        "#@markdown Install image browser extension, Dataset Tag Editor extension and default settings?\n",
        "install_default_settings = True #@param {type:\"boolean\"}\n",
        "install_image_browser = True #@param {type:\"boolean\"}\n",
        "install_tag_editor = False #@param {type:\"boolean\"}\n",
        "\n",
        "%cd /content/\n",
        "!git clone --depth 1 https://github.com/AUTOMATIC1111/stable-diffusion-webui\n",
        "\n",
        "# change default settings (not necessary) \n",
        "if install_default_settings:\n",
        "    %cd /content/stable-diffusion-webui\n",
        "    !wget https://raw.githubusercontent.com/Miraculix200/StableDiffusionUI_Colab/main/config.json\n",
        "    !wget https://raw.githubusercontent.com/Miraculix200/StableDiffusionUI_Colab/main/ui-config.json\n",
        "\n",
        "# install image browser extension (not necessary)\n",
        "if install_image_browser:\n",
        "    %cd /content/stable-diffusion-webui/extensions\n",
        "    !git clone --depth 1 https://github.com/yfszzx/stable-diffusion-webui-images-browser\n",
        "\n",
        "# install Dataset Tag Editor extension (not necessary)\n",
        "if install_tag_editor:\n",
        "    !git clone --depth 1 https://github.com/toshiaki1729/stable-diffusion-webui-dataset-tag-editor.git"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZNR8PcjvildL"
      },
      "source": [
        "# Optional: Mount folders on Google Drive to reduce startup time next session"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sjFoA1MlildM"
      },
      "source": [
        "Mount folders on Google Drive to keep embeddings, hypernetworks, generated images, models permanently\n",
        "\n",
        "Doing so will decrease startup time the next time a session is started. This cell needs to be run once every session to be effective."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "CCT2ilF7XcGs"
      },
      "outputs": [],
      "source": [
        "#@markdown ### Mount folders on Google Drive\n",
        "#@markdown This cell will create/copy selected folders to Google Drive and create symlinks to these folders in this sessions file system\n",
        "\n",
        "mv_outputs = False #@param {type:\"boolean\"}\n",
        "mv_embeddings = True #@param {type:\"boolean\"}\n",
        "mv_textual_inversion = True #@param {type:\"boolean\"}\n",
        "mv_repositories = True #@param {type:\"boolean\"}\n",
        "mv_models = True #@param {type:\"boolean\"}\n",
        "mv_hypernetworks = False #@param {type:\"boolean\"}\n",
        "mv_sd_models = False #@param {type:\"boolean\"}\n",
        "\n",
        "import os\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')\n",
        "\n",
        "webui_folder = \"/content/stable-diffusion-webui/\"\n",
        "webui_drive_folder = \"/content/drive/MyDrive/SD_webui_Colab/\"\n",
        "\n",
        "!mkdir -p {webui_drive_folder}\n",
        "\n",
        "def mvToGdrive(path_from_webui_root):\n",
        "  if not os.path.exists(webui_drive_folder + path_from_webui_root):\n",
        "    print(\"Creating folder: \" + webui_drive_folder + path_from_webui_root)\n",
        "    !mkdir -p {webui_drive_folder}{path_from_webui_root}\n",
        "\n",
        "  if os.path.exists(webui_folder + path_from_webui_root):\n",
        "    print(\"Copying folder: \" + webui_folder + path_from_webui_root)\n",
        "    !cp -r {webui_folder}{path_from_webui_root} {webui_drive_folder}\n",
        "    print(\"Deleting folder: \" + webui_folder + path_from_webui_root)\n",
        "    !rm -rf {webui_folder}{path_from_webui_root}\n",
        "\n",
        "  !ln -sv {webui_drive_folder}{path_from_webui_root} {webui_folder}{path_from_webui_root}\n",
        "\n",
        "\n",
        "if mv_outputs:\n",
        "  mvToGdrive(\"outputs\")\n",
        "\n",
        "if mv_embeddings:\n",
        "  mvToGdrive(\"embeddings\")\n",
        "\n",
        "if mv_textual_inversion:\n",
        "  mvToGdrive(\"textual_inversion\")\n",
        "\n",
        "if mv_repositories:\n",
        "  mvToGdrive(\"repositories\")\n",
        "\n",
        "if mv_models:\n",
        "  mvToGdrive(\"models\")\n",
        "\n",
        "if mv_hypernetworks:\n",
        "  if mv_models:\n",
        "    print(\"Not moving hypernetworks because models folder is already moved\")\n",
        "  else:\n",
        "    mvToGdrive(\"models/hypernetworks\")\n",
        "\n",
        "if mv_sd_models:\n",
        "  if mv_models:\n",
        "    print(\"Not moving models/Stable-diffusion because models folder is already moved\")\n",
        "  else:\n",
        "    mvToGdrive(\"models/Stable-diffusion\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "qzbzEyhsj8Y6"
      },
      "outputs": [],
      "source": [
        "#@markdown ### Mount custom folder on Google Drive\n",
        "#@markdown The default settings will create a softlink named `gdrive_dataset` inside the `/content` folder and link that to the `SD_webui_Colab/dataset` folder on Google Drive\n",
        "\n",
        "#@markdown Path to paste in the webui: `/content/gdrive_dataset`\n",
        "\n",
        "#@markdown Colab folder to create the softlink in\n",
        "local_folder = \"/content\" #@param {type:\"string\"}\n",
        "#@markdown Colab folder to create the softlink in\n",
        "softlink_name = \"gdrive_dataset\" #@param {type:\"string\"}\n",
        "#@markdown Colab folder to create the softlink in\n",
        "gdrive_target_folder = \"SD_webui_Colab/dataset\" #@param {type:\"string\"}\n",
        "\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')\n",
        "\n",
        "!mkdir -p /content/drive/MyDrive/{gdrive_target_folder}\n",
        "!mkdir -p {local_folder}\n",
        "\n",
        "!ln -sv /content/drive/MyDrive/{gdrive_target_folder} {local_folder}/{softlink_name}\n",
        "print(\"done\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8LHoV1E3FqrL"
      },
      "source": [
        "# Optional (beta): Install Dreambooth extension\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "i3dI7wnNVvvI"
      },
      "source": [
        "## WARNING\n",
        "\n",
        "The Dreambooth extension doesn't work properly on free Google Colab (but it would on Google Colab Pro).\n",
        "\n",
        "It will crash when\n",
        "* you create a new model from a .ckpt using the webui (conversion from .ckpt to diffusers uses too much system RAM)\n",
        "* the training is complete and it starts the conversion of the diffusers to a Stable Diffusion checkpoint\n",
        "\n",
        "To make it work on free Google Colab, use the `Import Model from Huggingface Hub` in the Dreambooth extension to clone a model from Huggingface to start training with.\n",
        "\n",
        "After the training, when the webui crashes or becomes unresponsive, you have to run the cell at the end of this notebook which converts the diffusers into a Stable Diffusion checkpoint.\n",
        "\n",
        "When the Dreambooth extension is installed, there may also be some errors while starting the webui. Dreambooth training will work anyway, so you can ignore them.\n",
        "\n",
        "## Recommended settings in the Dreambooth extension tab in the webui:\n",
        "\n",
        "#### Create Model tab:\n",
        "\n",
        "If you don't have Google Colab Pro, check `Import Model from Huggingface Hub` and enter `runwayml/stable-diffusion-v1-5` into the `Model Path` textbox\n",
        "\n",
        "#### Train Model tab:\n",
        "\n",
        "`Total number of classification images`: Number of (optional) class images you uploaded  \n",
        "`Training steps`: 1200 for faces, 400 for objects (see [here](https://huggingface.co/blog/dreambooth#summary-of-initial-results))  \n",
        "`Learning rate`: 0.000001 or 0.000002  \n",
        "`Save a checkpoint every N steps`: 9000 (doesn't work properly right now)  \n",
        "`Generate a preview image every N steps`: 9000  \n",
        "\n",
        "Advanced:\n",
        "\n",
        "These 2 options are mandatory, otherwise the webui will crash because of low VRAM\n",
        "\n",
        "`Use 8bit Adam`: True  \n",
        "`Mixed Precision`: fp16  \n",
        "\n",
        "As of now (November 10th, 2022), you can leave the default values for most other options\n",
        "\n",
        "See https://www.youtube.com/watch?v=HahKXY7AQ8c for a turorial how to use the extension"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "G_lzX6ZBLMA0"
      },
      "source": [
        "## Install Dreambooth extension and xformers"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "IIhLWFS8JNFI"
      },
      "outputs": [],
      "source": [
        "%cd /content/stable-diffusion-webui/extensions\n",
        "!git clone --depth 1 https://github.com/d8ahazard/sd_dreambooth_extension.git\n",
        "\n",
        "%pip install -qq git+https://github.com/ShivamShrirao/diffusers\n",
        "\n",
        "%pip install torch==1.12.1+cu116 torchvision==0.13.1+cu116 --extra-index-url https://download.pytorch.org/whl/cu116\n",
        "%pip install -q -U --pre triton\n",
        "%pip install -q accelerate==0.12.0 bitsandbytes\n",
        "\n",
        "%pip install -q https://github.com/metrolobo/xformers_wheels/releases/download/1d31a3ac_various_6/xformers-0.0.14.dev0-cp37-cp37m-linux_x86_64.whl\n",
        "# These were compiled on Tesla T4, should also work on P100, thanks to https://github.com/metrolobo"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kp4vbKL8LmeU"
      },
      "source": [
        "## Create Dreambooth dataset/class image folders and optionally mount Google Drive\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "igebS8EILr0F"
      },
      "source": [
        "This cell will create dataset and class folders and display the paths for pasting in the Dreambooth extension tab in the webui"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "-ajqhXNOL8Dy"
      },
      "outputs": [],
      "source": [
        "#@markdown Choose between using Google Drive or Colab filesystem for uploading the images\n",
        "from IPython.display import Markdown\n",
        "\n",
        "use_google_drive = False #@param {type:\"boolean\"}\n",
        "\n",
        "folder_prefix = \"/content/\"\n",
        "\n",
        "if use_google_drive:\n",
        "  from google.colab import drive\n",
        "  drive.mount('/content/gdrive')\n",
        "  folder_prefix = \"/content/gdrive/MyDrive/\"\n",
        "\n",
        "ds_img_dir = folder_prefix + \"dreambooth_ext/dataset_images\"\n",
        "cl_img_dir = folder_prefix + \"dreambooth_ext/class_images\"  \n",
        "\n",
        "!mkdir -p $ds_img_dir\n",
        "!mkdir -p $cl_img_dir\n",
        "\n",
        "display(Markdown(\"## Folders\"))\n",
        "\n",
        "if use_google_drive:\n",
        "  display(Markdown(\"#### Open Google Drive and upload your images to these folders\"))\n",
        "  display(Markdown(f'Dataset images: `dreambooth_ext/dataset_images`'))\n",
        "  display(Markdown(f'Optional class images: `dreambooth_ext/class_images`'))\n",
        "  !mkdir -p \"/content/gdrive/MyDrive/dreambooth_ext/model\"\n",
        "else:\n",
        "  display(Markdown(\"#### Open the file browser on the left and upload your images to these folders\"))\n",
        "  display(Markdown(f'Dataset images: `{ds_img_dir}`'))\n",
        "  display(Markdown(f'Optional class images: `{cl_img_dir}`'))\n",
        "\n",
        "print(\" \")\n",
        "display(Markdown(f'#### Paste these paths in the Dreambooth extension tab in the webui:'))\n",
        "display(Markdown(f'Dataset directory: `{ds_img_dir}`'))\n",
        "display(Markdown(f'Classification dataset directory (optional): `{cl_img_dir}`'))\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "tHqspCZClRn7"
      },
      "outputs": [],
      "source": [
        "#@markdown ### Optional: Download class images\n",
        "\n",
        "#@markdown Run this cell if you want to download 1500 class images for the class \"person\" to the Classification dataset directory  \n",
        "\n",
        "#@markdown Image source: https://github.com/aitrepreneur/REGULARIZATION-IMAGES-SD\n",
        "\n",
        "#@markdown If you do, paste this path into the `Classification dataset directory` text field in the webui:\n",
        "\n",
        "#@markdown `/content/gdrive/MyDrive/dreambooth_ext/class_images/person`\n",
        "\n",
        "!echo $cl_img_dir\n",
        "%cd $cl_img_dir\n",
        "\n",
        "!git clone --depth 1 https://github.com/aitrepreneur/REGULARIZATION-IMAGES-SD\n",
        "!mv REGULARIZATION-IMAGES-SD/person .\n",
        "!rm -rf REGULARIZATION-IMAGES-SD\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5B4E1TNy6dsK"
      },
      "source": [
        "## Convert existing .ckpt to diffusers (optional)\n",
        "### Run this cell if you don't have Google Colab Pro and don't want to/can't clone a model from Huggingface"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "b9lLgwCe5Xw6"
      },
      "outputs": [],
      "source": [
        "#@markdown Enter .ckpt path of the model you want to convert\n",
        "sd_ckpt_path = \"/content/stable-diffusion-webui/models/Stable-diffusion/gigachad_2000.ckpt\" #@param {type:\"string\"}\n",
        "#@markdown The name of the created model (select this in the webui Dreambooth tab)\n",
        "my_model_name = \"MyNewModel\" #@param {type:\"string\"}\n",
        "#@markdown Scheduler (don't change unless you know what you're doing)\n",
        "scheduler = \"ddim\" #@param {type:\"string\"}\n",
        "\n",
        "# test\n",
        "#%cd /content/stable-diffusion-webui/models/Stable-diffusion/\n",
        "#!wget https://huggingface.co/SpiteAnon/gigachad-diffusion/resolve/main/gigachad_2000.ckpt\n",
        "\n",
        "import os\n",
        "\n",
        "if os.path.exists(sd_ckpt_path):\n",
        "\n",
        "  dump_path = \"/content/stable-diffusion-webui/models/dreambooth/\" + my_model_name + \"/working\"\n",
        "  !mkdir -p {dump_path}\n",
        "\n",
        "\n",
        "  # install necessary packages\n",
        "  %pip install -qq omegaconf pytorch-lightning transformers ftfy\n",
        "\n",
        "  # get conversion script and start conversion\n",
        "  %cd /content/dreambooth_ext/\n",
        "  !wget https://raw.githubusercontent.com/ShivamShrirao/diffusers/main/scripts/convert_original_stable_diffusion_to_diffusers.py\n",
        "  !python convert_original_stable_diffusion_to_diffusers.py --checkpoint_path {sd_ckpt_path} --dump_path {dump_path}\n",
        "\n",
        "  # get v1-inference.yaml\n",
        "  %cd {dump_path}\n",
        "  !wget \"https://raw.githubusercontent.com/CompVis/stable-diffusion/main/configs/stable-diffusion/v1-inference.yaml\" -O v1-inference.yaml\n",
        "\n",
        "  # create db_config.json\n",
        "  json_content = '{\"model_name\": \"' + my_model_name + '\", \"scheduler\": \"' + scheduler + '\", \"src\": \"hax\", \"total_steps\": 0}'\n",
        "  #json_content = '{\"model_name\": \"' + my_model_name + '\", \"scheduler\": \"ddim\", \"src\": \"v1-5-pruned-emaonly.ckpt [81761151]\", \"total_steps\": 0}'\n",
        "\n",
        "  %cd ..\n",
        "  with open('db_config.json', 'w') as f:\n",
        "      f.write(json_content)\n",
        "\n",
        "else:\n",
        "  print('\u001b[1;31mFile not found:')\n",
        "  print(sd_ckpt_path)\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4QhT_CspclF5"
      },
      "source": [
        "# Install requirements\n",
        "\n",
        "This is not strictly necessary but doesn't hurt"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Cv_164UeciUJ"
      },
      "outputs": [],
      "source": [
        "%cd /content/stable-diffusion-webui/\n",
        "!COMMANDLINE_ARGS=\"--exit\" REQS_FILE=\"requirements.txt\" python launch.py"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CpB43kKWohN8"
      },
      "source": [
        "# Download models and variational autoencoders (VAE)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KK1QKbo9rc3e"
      },
      "source": [
        "### For the following 4 models you need a free Huggingface account. If you don't want to create an account, skip this cell.\n",
        "\n",
        "* RunwayML model v1.5 can be used for image generation, textual inversion training and hypernetwork training\n",
        "\n",
        "* Stability AI VAE for improved quality in combination with model 1.5 (needs to be selected in webui settings)\n",
        "\n",
        "* RunwayML inpainting model for significantly improved inpainting results\n",
        "\n",
        "* Hakurei Waifu Division for anime characters, including VAE\n",
        "\n",
        "### **Accept these licenses** before running the next cell\n",
        "\n",
        "https://huggingface.co/stabilityai/sd-vae-ft-mse-original\n",
        "\n",
        "https://huggingface.co/runwayml/stable-diffusion-v1-5\n",
        "\n",
        "https://huggingface.co/runwayml/stable-diffusion-inpainting"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "ShfDjBbBPoU7"
      },
      "outputs": [],
      "source": [
        "#@markdown ## Enter Huggingface token\n",
        "#@markdown Get your (read only) token here: https://huggingface.co/settings/tokens\n",
        "huggingface_user_token = \"hf_omgwtfbbq1337SUGRIUkPTDOkbaQYkjjVQ\" #@param {type:\"string\"}\n",
        "\n",
        "#@markdown ## Select one or more models here, then run the cell\n",
        "\n",
        "#@markdown ### RunwayML Stable Diffusion Model 1.5\n",
        "model_1_5 = True #@param {type:\"boolean\"}\n",
        "#@markdown ### RunwayML Stable Diffusion Inpainting Model 1.5\n",
        "inpaint_1_5 = False #@param {type:\"boolean\"}\n",
        "#@markdown ### Stability AI VAE (improves quality of model 1.5)\n",
        "stability_ai_vae = True #@param {type:\"boolean\"}\n",
        "#@markdown ### Automatically select VAE when using model_1_5 (no need to change webui settings)\n",
        "#@markdown This will rename the VAE .ckpt to v1-5-pruned-ema.vae.pt and copy it into the models folder, not the VAE folder\n",
        "autoselect_vae = True #@param {type:\"boolean\"}\n",
        "\n",
        "user_header = f\"\\\"Authorization: Bearer {huggingface_user_token}\\\"\"\n",
        "\n",
        "%cd /content/stable-diffusion-webui/models/Stable-diffusion/\n",
        "\n",
        "if model_1_5:\n",
        "  !wget --header={user_header} https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.ckpt \n",
        "\n",
        "if inpaint_1_5:\n",
        "  !wget --header={user_header} https://huggingface.co/runwayml/stable-diffusion-inpainting/resolve/main/sd-v1-5-inpainting.ckpt\n",
        "\n",
        "if stability_ai_vae:\n",
        "  if autoselect_vae:\n",
        "    %cd /content/stable-diffusion-webui/models/Stable-diffusion/\n",
        "    !wget --header={user_header} https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.ckpt -O v1-5-pruned-emaonly.vae.pt \n",
        "  else:\n",
        "    %cd /content/stable-diffusion-webui/models/VAE/\n",
        "    !wget --header={user_header} https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.ckpt\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "t3MZ1J0GpxgW"
      },
      "source": [
        "## Optional: Select one or more models to download\n",
        "\n",
        "No account is required for these models"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "fspIE5x7psty"
      },
      "outputs": [],
      "source": [
        "#@markdown ### Anything V3 model with VAE\n",
        "anything_v3 = True #@param {type:\"boolean\"}\n",
        "\n",
        "#@markdown ### AnythingXtron model\n",
        "anything_xtron = False #@param {type:\"boolean\"}\n",
        "\n",
        "#@markdown ### Gigachad model\n",
        "gigachad = False #@param {type:\"boolean\"}\n",
        "\n",
        "#@markdown ### Midjourney V4 Diffusion\n",
        "midjourney_v4 = False #@param {type:\"boolean\"}\n",
        "\n",
        "#@markdown ### Waifu Division with Anime VAE\n",
        "waifu = False #@param {type:\"boolean\"}\n",
        "\n",
        "#@markdown ### Modern Disney Diffusion\n",
        "modidi = False #@param {type:\"boolean\"}\n",
        "\n",
        "#@markdown ### Multi-Style Model trained from scratch\n",
        "nitrodiffusion = False #@param {type:\"boolean\"}\n",
        "\n",
        "#@markdown ### Cloned version of model 1.5 (not token necessary)\n",
        "sd15_cloned = False #@param {type:\"boolean\"}\n",
        "\n",
        "#@markdown ### Anime/furry model with VAE and hypernetworks\n",
        "secret_ai = False #@param {type:\"boolean\"}\n",
        "\n",
        "%cd /content/stable-diffusion-webui/models/Stable-diffusion/\n",
        "\n",
        "if anything_v3:\n",
        "  !wget https://huggingface.co/Linaqruf/anything-v3.0/resolve/main/Anything-V3.0-pruned.ckpt\n",
        "  !wget https://huggingface.co/Linaqruf/anything-v3.0/resolve/main/Anything-V3.0.vae.pt -O Anything-V3.0-pruned.vae.pt\n",
        "\n",
        "if anything_xtron:\n",
        "  !wget https://huggingface.co/CrasHthe2nd2/anything-tron/resolve/main/anythingXtron.ckpt\n",
        "  !wget https://huggingface.co/CrasHthe2nd2/anything-tron/resolve/main/Anything-V3.0.vae.pt -O anythingXtron.vae.pt\n",
        "\n",
        "if gigachad:\n",
        "  !wget https://huggingface.co/SpiteAnon/gigachad-diffusion/resolve/main/gigachad_2000.ckpt\n",
        "\n",
        "if midjourney_v4:\n",
        "  !wget https://huggingface.co/prompthero/midjourney-v4-diffusion/resolve/main/mdjrny-v4.ckpt\n",
        "\n",
        "if modidi:\n",
        "  !wget https://huggingface.co/nitrosocke/mo-di-diffusion/resolve/main/moDi-v1-pruned.ckpt\n",
        "\n",
        "if nitrodiffusion:\n",
        "    !wget https://huggingface.co/nitrosocke/Nitro-Diffusion/resolve/main/nitroDiffusion-v1.ckpt\n",
        "\n",
        "if sd15_cloned:\n",
        "    !wget https://huggingface.co/acheong08/SD-V1-5-cloned/resolve/main/v1-5-pruned-emaonly.ckpt\n",
        "\n",
        "if secret_ai:\n",
        "    !wget https://huggingface.co/acheong08/secretAI/resolve/main/stableckpt/animefull-final-pruned/model.ckpt -O secret_ai.ckpt\n",
        "    %cd /content/stable-diffusion-webui/models/VAE/\n",
        "    !wget https://huggingface.co/acheong08/secretAI/resolve/main/stableckpt/animevae.pt\n",
        "    !mkdir -p /content/stable-diffusion-webui/models/hypernetworks/\n",
        "    %cd /content/stable-diffusion-webui/models/hypernetworks/\n",
        "    !wget https://huggingface.co/acheong08/secretAI/resolve/main/stableckpt/modules/modules/aini.pt\n",
        "    !wget https://huggingface.co/acheong08/secretAI/resolve/main/stableckpt/modules/modules/anime.pt\n",
        "    !wget https://huggingface.co/acheong08/secretAI/resolve/main/stableckpt/modules/modules/anime_2.pt\n",
        "    !wget https://huggingface.co/acheong08/secretAI/resolve/main/stableckpt/modules/modules/anime_3.pt\n",
        "    !wget https://huggingface.co/acheong08/secretAI/resolve/main/stableckpt/modules/modules/furry.pt\n",
        "    !wget https://huggingface.co/acheong08/secretAI/resolve/main/stableckpt/modules/modules/furry_2.pt\n",
        "    !wget https://huggingface.co/acheong08/secretAI/resolve/main/stableckpt/modules/modules/furry_3.pt\n",
        "    !wget https://huggingface.co/acheong08/secretAI/resolve/main/stableckpt/modules/modules/furry_kemono.pt\n",
        "    !wget https://huggingface.co/acheong08/secretAI/resolve/main/stableckpt/modules/modules/furry_protogen.pt\n",
        "    !wget https://huggingface.co/acheong08/secretAI/resolve/main/stableckpt/modules/modules/furry_scalie.pt\n",
        "    !wget https://huggingface.co/acheong08/secretAI/resolve/main/stableckpt/modules/modules/furry_transformation.pt\n",
        "    !wget https://huggingface.co/acheong08/secretAI/resolve/main/stableckpt/modules/modules/pony.pt\n",
        "\n",
        "if waifu:\n",
        "  %cd /content/stable-diffusion-webui/models/Stable-diffusion/\n",
        "  !wget https://huggingface.co/hakurei/waifu-diffusion-v1-4/resolve/main/models/wd-1-3-penultimate-ucg-cont.ckpt\n",
        "  %cd /content/stable-diffusion-webui/models/VAE/\n",
        "  !wget https://huggingface.co/hakurei/waifu-diffusion-v1-4/resolve/main/vae/kl-f8-anime.ckpt\n",
        "  !wget https://huggingface.co/hakurei/waifu-diffusion-v1-4/resolve/main/vae/kl-f8-anime2.ckpt"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Z6d5E-3Lilda"
      },
      "source": [
        "Sources: \n",
        "\n",
        "https://huggingface.co/SpiteAnon/gigachad-diffusion\n",
        "\n",
        "https://huggingface.co/CrasHthe2nd2/anything-tron\n",
        "\n",
        "https://huggingface.co/Linaqruf/anything-v3.0\n",
        "\n",
        "https://huggingface.co/prompthero/midjourney-v4-diffusion\n",
        "\n",
        "https://huggingface.co/hakurei/waifu-diffusion-v1-4\n",
        "\n",
        "https://huggingface.co/nitrosocke/mo-di-diffusion\n",
        "\n",
        "https://huggingface.co/nitrosocke/Nitro-Diffusion\n",
        "\n",
        "https://huggingface.co/acheong08"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3ZF7L8VaN0cl"
      },
      "source": [
        "## Optional: Download a model from Google Drive"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yVLP6ogHOFd0"
      },
      "source": [
        "Copy the file ID from your url and paste it into the GOOGLE_FILE_ID text field below, before running this cell"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "G93BUqQyNYdA"
      },
      "outputs": [],
      "source": [
        "###########################################################\n",
        "GOOGLE_FILE_ID = \"1wHFgl0ivCmIZv88hVZXkb8oy9qCuaBGA\" #@param {type:\"string\"}\n",
        "###########################################################\n",
        "\n",
        "# above file ID is Stable Diffusion model 1.4. Replace it with the file ID of the model you want to download from Google Drive\n",
        "\n",
        "%cd /content/stable-diffusion-webui/models/Stable-diffusion/\n",
        "url = \"https://drive.google.com/u/0/uc?id=\" + GOOGLE_FILE_ID + \"&export=download&confirm=t\"\n",
        "!gdown $url"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AmLUWv3o5x_7"
      },
      "source": [
        "## Optional: Download a model from MEGA"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rbkIyF6yf8dR"
      },
      "source": [
        "\n",
        "Change MEGA_DOWNLOAD_URL to the URL of the model, then run the cell\n",
        "\n",
        "Download can be very slow (>30 minutes for a 4GB model)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "GjOjF2AU5xV7"
      },
      "outputs": [],
      "source": [
        "##########################################################\n",
        "MEGA_DOWNLOAD_URL = \"https://mega.nz/file/mdcVARhL#FUq5TL2xp7FuzzgMS4B20sOYYnPZsyPMw93sPMHeQ78\" #@param {type:\"string\"}\n",
        "##########################################################\n",
        "\n",
        "%cd /content/stable-diffusion-webui/models/Stable-diffusion/\n",
        "\n",
        "%pip install mega.py\n",
        "from mega import Mega\n",
        "\n",
        "mega = Mega()\n",
        "print(\"Connecting to MEGA\")\n",
        "m = mega.login()\n",
        "print(\"Downloading file (no progress display available)\")\n",
        "m.download_url(MEGA_DOWNLOAD_URL)\n",
        "print(\"Download complete\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Jl2HWPWQdtAe"
      },
      "source": [
        "# Optional: Stable Diffusion Pickle Scanner (scan models for malware)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tIXVICnqd2C-"
      },
      "source": [
        "Scan .pt, .ckpt and .bin files for potentially malicious code\n",
        "\n",
        "Source: https://github.com/zxix/stable-diffusion-pickle-scanner\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ERHoiA07d_-Q"
      },
      "outputs": [],
      "source": [
        "%cd /content/stable-diffusion-webui\n",
        "!wget https://raw.githubusercontent.com/zxix/stable-diffusion-pickle-scanner/main/pickle_scan.py\n",
        "!wget https://raw.githubusercontent.com/zxix/stable-diffusion-pickle-scanner/main/pickle_inspector.py\n",
        "\n",
        "!python pickle_scan.py /content/stable-diffusion-webui/models"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QzpiXpFseCBN"
      },
      "source": [
        "# AUTOMATIC1111 Stable Diffusion Web UI "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "R-xAdMA5wxXd"
      },
      "outputs": [],
      "source": [
        "#@markdown # Launch web ui\n",
        "#@markdown You will get a link to nnn.gradio.app, follow it.\n",
        "\n",
        "#@markdown It can take a while until it installed the requirements\n",
        "\n",
        "#@markdown ### Change username and password\n",
        "\n",
        "#@markdown Or someone who is extremely bored and doesn't have a life may find your gradio link and login to your webui\n",
        "\n",
        "webui_username = \"genius\" #@param {type:\"string\"}\n",
        "webui_password = \"artist\" #@param {type:\"string\"}\n",
        "\n",
        "#@markdown ### ngrok (optional)\n",
        "#@markdown If you have connection issues with gradio, enter a ngrok auth token here\n",
        "\n",
        "ngrok_token = \"\" #@param {type:\"string\"}\n",
        "\n",
        "#@markdown ### localtunnel (optional)\n",
        "#@markdown If you have connection issues with gradio, and don't want to use ngrok, check this box to start a [localtunnel](https://theboroer.github.io/localtunnel-www/) reverse proxy (no account required)\n",
        "\n",
        "use_lt = True #@param {type:\"boolean\"}\n",
        "\n",
        "#@markdown ### Additional commandline arguments\n",
        "#@markdown Leave this as it is, unless you know what you're doing\n",
        "\n",
        "import os\n",
        "import time\n",
        "\n",
        "custom_args = \"--gradio-debug\" #@param {type:\"string\"}\n",
        "\n",
        "if ngrok_token != \"\":\n",
        "  c_args = custom_args + \" --ngrok \" + ngrok_token\n",
        "elif use_lt:\n",
        "  if not os.path.exists('/tools/node/bin/lt'):\n",
        "    print(\"Installing localtunnel\")\n",
        "    !npm install -g localtunnel\n",
        "  %cd /content/\n",
        "  !nohup lt --port 7860 > srv.txt 2>&1 &\n",
        "  time.sleep(2)\n",
        "  print(\"The webui will run on this URL:\")\n",
        "  !grep -o 'https[^ ]*' /content/srv.txt \n",
        "  c_args = custom_args\n",
        "else:\n",
        "  c_args = custom_args + \" --share\"\n",
        "\n",
        "cmd_line_args = c_args + \" --gradio-auth \" + webui_username + \":\" + webui_password\n",
        "%cd /content/stable-diffusion-webui\n",
        "!sed -i -e 's/numpy==1.23.3/numpy==1.21.6/g' requirements_versions.txt\n",
        "!sed -i -e 's/fairscale==0.4.9/fairscale==0.4.6/g' requirements_versions.txt\n",
        "!COMMANDLINE_ARGS=\"$cmd_line_args\" REQS_FILE=\"requirements.txt\" python launch.py"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xt8lbdmC04ox"
      },
      "source": [
        "\n",
        "\n",
        "Commandline arguments are:\n",
        "  - `--gradio-debug` - print outputs to console\n",
        "  - `--ui-debug-mode` - don't load model at startup (faster startup)\n",
        "  - `--disable-console-progressbars` - avoid mess in console output\n",
        "\n",
        "  - see [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Command-Line-Arguments-and-Settings) for more options"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9qrpRUJpno7L"
      },
      "source": [
        "# commands for ***after*** you're done with a session\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "gBt5g_Dn0NFo"
      },
      "outputs": [],
      "source": [
        "#@markdown ### Zip images for downloading on local drive\n",
        "#@markdown After running the cell, click the folder icon on the left, the one below {x}, search for **outputs.zip** in the /content folder\n",
        "!zip -r /content/outputs.zip /content/stable-diffusion-webui/outputs "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "hfbngzvdozyY"
      },
      "outputs": [],
      "source": [
        "#@markdown ### Delete all generated images\n",
        "#@markdown This isn't necessary, as all files will be deleted when you terminate this session\n",
        "!rm -rf /content/stable-diffusion-webui/outputs/*"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "j5_IGbmKPQhu"
      },
      "outputs": [],
      "source": [
        "#@markdown ### (beta) Convert diffusers model to Stable Diffusion checkpoint\n",
        "#@markdown If you did a Dreambooth training on free Google Colab, the webui will crash when the training is complete, because there is not enough system RAM to convert the diffusers to a Stable Diffusion checkpoint\n",
        "\n",
        "#@markdown Use Google Colab Pro to prevent this\n",
        "\n",
        "#@markdown Run this cell to start the conversion\n",
        "\n",
        "#@markdown #### Select this option to copy the .ckpt file to your Google Drive\n",
        "\n",
        "copy_ckpt_to_gdrive = True #@param {type:\"boolean\"}\n",
        "\n",
        "#@markdown #### Enter the name of the model you created in Dreambooth extension\n",
        "\n",
        "my_model_name = \"MyNewModel\" #@param {type:\"string\"}\n",
        "\n",
        "if copy_ckpt_to_gdrive:\n",
        "    print(\"Give permission to access Google Drive\")\n",
        "    from google.colab import drive\n",
        "    drive.mount('/content/drive')\n",
        "\n",
        "%cd /content/dreambooth_ext/\n",
        "!wget https://raw.githubusercontent.com/ShivamShrirao/diffusers/main/scripts/convert_diffusers_to_original_stable_diffusion.py\n",
        "\n",
        "model_p = \"/content/stable-diffusion-webui/models/dreambooth/\" + my_model_name + \"/working\"\n",
        "ckpt_p = \"/content/stable-diffusion-webui/models/Stable-diffusion/\" + my_model_name + \".ckpt\"\n",
        "\n",
        "print(\"Converting diffusers to original Stable Diffusion checkpoint\")\n",
        "\n",
        "!python convert_diffusers_to_original_stable_diffusion.py --model_path {model_p} --checkpoint_path {ckpt_p}\n",
        "\n",
        "print(\"Saved checkpoint to \" + ckpt_p)\n",
        "\n",
        "if copy_ckpt_to_gdrive:\n",
        "  print(\"Copying \" + my_model_name + \".ckpt to Google Drive\")\n",
        "  !cp {ckpt_p} /content/drive/MyDrive/\n",
        "  print(\"Done\")\n"
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "collapsed_sections": [
        "ZNR8PcjvildL",
        "8LHoV1E3FqrL",
        "Asdl3SetXcGu",
        "Jl2HWPWQdtAe",
        "3ZF7L8VaN0cl",
        "AmLUWv3o5x_7"
      ],
      "provenance": []
    },
    "gpuClass": "standard",
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}