Vladmandic_A1111.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "machine_shape": "hm",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU",
    "gpuClass": "standard"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/wordbrew/vladcolab/blob/main/Vladmandic_A1111.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Important links:\n",
        "- [Vladmandic A1111](https://github.com/vladmandic/automatic),"
      ],
      "metadata": {
        "id": "yefSKwKEry3f"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#@markdown # Connect Google Drive\n",
        "from google.colab import drive\n",
        "from IPython.display import clear_output\n",
        "import ipywidgets as widgets\n",
        "import os\n",
        "\n",
        "def inf(msg, style, wdth): inf = widgets.Button(description=msg, disabled=True, button_style=style, layout=widgets.Layout(min_width=wdth));display(inf)\n",
        "\n",
        "print(\"\u001b[0;33mConnecting...\")\n",
        "drive.mount('/content/gdrive')\n",
        "\n",
        "mainpth=\"MyDrive\"\n",
        "\n",
        "clear_output()\n",
        "inf('\\u2714 Done','success', '50px')"
      ],
      "metadata": {
        "cellView": "form",
        "id": "Vl7RIJkCMyXd"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@markdown # Install/Update Vladmandic AUTOMATIC1111 repo\n",
        "from IPython.utils import capture\n",
        "from IPython.display import clear_output\n",
        "from subprocess import getoutput\n",
        "import ipywidgets as widgets\n",
        "import os\n",
        "import time\n",
        "\n",
        "if not os.path.exists(\"/content/gdrive\"):\n",
        "  print('\u001b[1;31mGdrive not connected, using colab storage ...')\n",
        "  time.sleep(4)\n",
        "  mainpth=\"MyDrive\"\n",
        "  !mkdir -p /content/gdrive/$mainpth\n",
        "\n",
        "with capture.capture_output() as cap:\n",
        "  def inf(msg, style, wdth): inf = widgets.Button(description=msg, disabled=True, button_style=style, layout=widgets.Layout(min_width=wdth));display(inf)\n",
        "  fgitclone = \"git clone --depth 1\"\n",
        "  %mkdir -p /content/gdrive/$mainpth/vlad\n",
        "  %cd /content/gdrive/$mainpth/vlad\n",
        "  !git clone -q --branch master https://github.com/vladmandic/automatic\n",
        "\n",
        "clear_output()\n",
        "inf('\\u2714 Done','success', '50px')"
      ],
      "metadata": {
        "cellView": "form",
        "id": "2UE0_DokNXuo"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@markdown # ControlNet\n",
        "from torch.hub import download_url_to_file\n",
        "from urllib.parse import urlparse\n",
        "import re\n",
        "from subprocess import run\n",
        "\n",
        "Model = \"All (21GB)\" #@param [ \"None\", \"All (21GB)\", \"Canny\", \"Depth\", \"Lineart\", \"MLSD\", \"Normal\", \"OpenPose\", \"Scribble\", \"Seg\", \"ip2p\", \"Shuffle\", \"Inpaint\", \"Softedge\", \"Lineart_Anime\", \"Tile\", \"T2iadapter_Models\"]\n",
        "\n",
        "#@markdown - Download/update ControlNet extension and its models\n",
        "\n",
        "def download(url, model_dir):\n",
        "\n",
        "    filename = os.path.basename(urlparse(url).path)\n",
        "    pth = os.path.abspath(os.path.join(model_dir, filename))\n",
        "    if not os.path.exists(pth):\n",
        "        print('Downloading: '+os.path.basename(url))\n",
        "        download_url_to_file(url, pth, hash_prefix=None, progress=True)\n",
        "    else:\n",
        "      print(f\"\u001b[1;32mThe model {filename} already exists\u001b[0m\")\n",
        "\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",
        "\n",
        "with capture.capture_output() as cap:\n",
        "  %cd /content/gdrive/$mainpth/vlad/automatic/extensions-builtin\n",
        "  if not os.path.exists(\"sd-webui-controlnet\"):\n",
        "    !git clone https://github.com/Mikubill/sd-webui-controlnet.git\n",
        "    %cd /content\n",
        "  else:\n",
        "    %cd sd-webui-controlnet\n",
        "    !git reset --hard\n",
        "    !git pull\n",
        "    %cd /content\n",
        "\n",
        "mdldir='/content/gdrive/'+mainpth+'/vlad/automatic/extensions-builtin/sd-webui-controlnet/models'\n",
        "for filename in os.listdir(mdldir):\n",
        "  if \"_sd14v1\" in filename:\n",
        "    renamed = re.sub(\"_sd14v1\", \"-fp16\", filename)\n",
        "    os.rename(os.path.join(mdldir, filename), os.path.join(mdldir, renamed))\n",
        "\n",
        "!wget -q -O CN_models.txt https://github.com/TheLastBen/fast-stable-diffusion/raw/main/AUTOMATIC1111_files/CN_models.txt\n",
        "\n",
        "with open(\"CN_models.txt\", 'r') as f:\n",
        "  mdllnk = f.read().splitlines()\n",
        "\n",
        "!rm CN_models.txt\n",
        "\n",
        "with capture.capture_output() as cap:\n",
        "  cfgnames=[os.path.basename(url).split('.')[0]+'.yaml' for url in mdllnk_v2]\n",
        "  %cd /content/gdrive/$mainpth/vlad/automatic/extensions-builtin/sd-webui-controlnet/models\n",
        "  for name in cfgnames:\n",
        "      run(['cp', 'cldm_v21.yaml', name])\n",
        "  %cd /content\n",
        "\n",
        "if Model == \"All (21GB)\": \n",
        "  for lnk in mdllnk:\n",
        "      download(lnk, mdldir)\n",
        "  clear_output()\n",
        "\n",
        "elif Model == \"T2iadapter_Models\":\n",
        "  mdllnk=list(filter(lambda x: 't2i' in x, mdllnk))\n",
        "  for lnk in mdllnk:\n",
        "      download(lnk, mdldir)\n",
        "  clear_output()\n",
        "\n",
        "elif Model == \"None\":\n",
        "    pass\n",
        "    clear_output()\n",
        "\n",
        "else:\n",
        "  download(globals()[Model], mdldir)\n",
        "  clear_output()\n",
        "  inf('\\u2714 Done','success', '50px')"
      ],
      "metadata": {
        "id": "PNHgUjn3h963",
        "cellView": "form"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "NPtEBB6r18yU",
        "cellView": "form"
      },
      "outputs": [],
      "source": [
        "#@markdown #Run Vladmandic A1111\n",
        "import os\n",
        "\n",
        "#Launch:\n",
        "%cd /content/gdrive/$mainpth/vlad/automatic\n",
        "\n",
        "model_path = \"/content/gdrive/MyDrive/Models/\" #@param {type:\"string\"}\n",
        "\n",
        "#@markdown Insert the full path of your trained model or to a folder containing multiple models\n",
        "\n",
        "!COMMANDLINE_ARGS=\"--no-hashing --share --models-dir {model_path}\" REQS_FILE=\"requirements.txt\" python launch.py"
      ]
    }
  ]
}