FULLY_WORKING_STABLE_DIFFUSION.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/pokewizardSAM/Stable-Diffusion-portable/blob/main/FULLY_WORKING_STABLE_DIFFUSION.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wqmMAaHcIleh"
      },
      "source": [
        "# **INTRODUCTION**\n",
        "\n",
        "<h1><center><b>🔥🔥Stable-Diffusion-Portable🔥🔥<b></center></h1>\n",
        "<h5><center>script made by: <b>sameer sahu<b><center><h5>\n",
        "\n",
        "<justify>This project was a hobby project to run stable diffusion in collab, there might be some bugs here and there, but i have tried my best to make this as good as possible.\n",
        "\n",
        "Description: This ipynb basically deploys/manages copies of premade stable-diffusion installation images on Google-collab. I have provided a pretty small and lightweight image with this project which loads quick enough(~10min for startup). custom images can be saved easily by backing up your entire installations as a zip file. By default in the basic-img your outputs will be stored in your google drive instead of your regular output folder</justify>\n",
        "<br><br>\n",
        "These bugs have been verified and work is undergoing on fixing these and will be fixed in upcoming releases\n",
        "```\n",
        "# known bugs: 1. memory leak and buffer overflow [Temporary fix available]\n",
        "              2. inconsistency due to unstable connection\n",
        "              3. Alsa lib card [0 ] not found\n",
        "```\n",
        "\n",
        "Additional credits: Automatic1111/stable-diffusion-webui\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jPTjODEHD3o0",
        "outputId": "f0fe023b-d315-4489-f806-067021fb2bab"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Thu Jul 13 07:48:17 2023       \n",
            "+-----------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 525.105.17   Driver Version: 525.105.17   CUDA Version: 12.0     |\n",
            "|-------------------------------+----------------------+----------------------+\n",
            "| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
            "| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n",
            "|                               |                      |               MIG M. |\n",
            "|===============================+======================+======================|\n",
            "|   0  Tesla T4            Off  | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   70C    P8    11W /  70W |      0MiB / 15360MiB |      0%      Default |\n",
            "|                               |                      |                  N/A |\n",
            "+-------------------------------+----------------------+----------------------+\n",
            "                                                                               \n",
            "+-----------------------------------------------------------------------------+\n",
            "| Processes:                                                                  |\n",
            "|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\n",
            "|        ID   ID                                                   Usage      |\n",
            "|=============================================================================|\n",
            "|  No running processes found                                                 |\n",
            "+-----------------------------------------------------------------------------+\n"
          ]
        }
      ],
      "source": [
        "#@title Step0: this makes sure gpu is enabled, if not then select GPU runtime in change runtime option in upper left menu under view resources\n",
        "!nvidia-smi"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Pe1ZxTgiUw0F"
      },
      "source": [
        "#<h3>Step1: This enables the fastapi required for proper functioning<h3>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "_g2SfJroUhWs",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2c98a017-07fb-448a-ff40-084e40542d6e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content\n",
            "Collecting fastapi==0.90\n",
            "  Downloading fastapi-0.90.0-py3-none-any.whl (56 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m56.0/56.0 kB\u001b[0m \u001b[31m6.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: pydantic!=1.7,!=1.7.1,!=1.7.2,!=1.7.3,!=1.8,!=1.8.1,<2.0.0,>=1.6.2 in /usr/local/lib/python3.10/dist-packages (from fastapi==0.90) (1.10.11)\n",
            "Collecting starlette<=0.23.0,>=0.22.0 (from fastapi==0.90)\n",
            "  Downloading starlette-0.23.0-py3-none-any.whl (64 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m64.5/64.5 kB\u001b[0m \u001b[31m9.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: typing-extensions>=4.2.0 in /usr/local/lib/python3.10/dist-packages (from pydantic!=1.7,!=1.7.1,!=1.7.2,!=1.7.3,!=1.8,!=1.8.1,<2.0.0,>=1.6.2->fastapi==0.90) (4.7.1)\n",
            "Requirement already satisfied: anyio<5,>=3.4.0 in /usr/local/lib/python3.10/dist-packages (from starlette<=0.23.0,>=0.22.0->fastapi==0.90) (3.7.1)\n",
            "Requirement already satisfied: idna>=2.8 in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.4.0->starlette<=0.23.0,>=0.22.0->fastapi==0.90) (3.4)\n",
            "Requirement already satisfied: sniffio>=1.1 in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.4.0->starlette<=0.23.0,>=0.22.0->fastapi==0.90) (1.3.0)\n",
            "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.4.0->starlette<=0.23.0,>=0.22.0->fastapi==0.90) (1.1.2)\n",
            "Installing collected packages: starlette, fastapi\n",
            "Successfully installed fastapi-0.90.0 starlette-0.23.0\n"
          ]
        }
      ],
      "source": [
        "%cd /content\n",
        "!pip install fastapi==0.90"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uGuLigLdRSRt"
      },
      "source": [
        "\n",
        "#<h2>Step2: Restore (MUST RUN)<h2>\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "LqyEeN0bRIsJ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a18259d4-4f30-4586-8fd4-b9ada3871eb9"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/gdrive; to attempt to forcibly remount, call drive.mount(\"/content/gdrive\", force_remount=True).\n",
            "Creating new Directory.........\n",
            "Cloning into 'Sd-my-fork'...\n",
            "remote: Enumerating objects: 22401, done.\u001b[K\n",
            "remote: Total 22401 (delta 0), reused 0 (delta 0), pack-reused 22401\u001b[K\n",
            "Receiving objects: 100% (22401/22401), 30.45 MiB | 14.28 MiB/s, done.\n",
            "Resolving deltas: 100% (15621/15621), done.\n",
            "\n",
            "  >>> Please wait for the model to download <<<\n",
            "rm: cannot remove '/content/Sd-my-fork/models/Stable-diffusion/v2-1_768-ema-pruned.safetensors': No such file or directory\n",
            "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
            "                                 Dload  Upload   Total   Spent    Left  Speed\n",
            " 36 2033M   36  741M    0     0  16.2M      0  0:02:05  0:00:45  0:01:20 16.6M"
          ]
        }
      ],
      "source": [
        "#@title ##Importing and extracting:\n",
        "#@markdown --> If you have backup of img in you gdrive and want to load from there select \"*load_from_gdrive*\" option, otherwise you can just leave it as it <br><br>--> You can use \"load_from_gdrive\" function after you have backed up the installation once to your own gdrive\n",
        "installation_type  = \"Fresh install\" #@param [\"Fresh install\" ,\"load_from_gdrive\",\"load_basic_img\" ]\n",
        "\n",
        "\n",
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')\n",
        "\n",
        "import zipfile\n",
        "import shutil\n",
        "!rm -rf \"/content/Sd-my-fork\"\n",
        "\n",
        "if installation_type == \"load_from_gdrive\":\n",
        "  print(\"Restoring Files from G-drive......\", end=\"\")\n",
        "  shutil.copy2(\"/content/gdrive/MyDrive/Sd-my-fork.zip\", \"/content/\")\n",
        "  print(\"completed\")\n",
        "  zip_path = \"/content/Sd-my-fork.zip\"\n",
        "  sd_fork_folder = \"/content/Sd-my-fork\"\n",
        "\n",
        "  print('Starting extraction......', end=\"\")\n",
        "  def extract_zip(zip_path, extract_path):\n",
        "      with zipfile.ZipFile(zip_path, 'r') as zipf:\n",
        "          zipf.extractall(extract_path)\n",
        "\n",
        "  extract_zip(zip_path, sd_fork_folder)\n",
        "  print(\"completed\")\n",
        "  !rm -rf \"/content/Sd-my-fork.zip\"\n",
        "\n",
        "elif installation_type == \"load_basic_img\":\n",
        "  %pip install gdown\n",
        "  !gdown \"https://drive.google.com/u/0/uc?id=1-CTD1JQxH1HR-HgqwFS8cRKdelviPKZx&export=download\"\n",
        "  zip_path = \"/content/Sd-my-fork.zip\"\n",
        "  sd_fork_folder = \"/content/Sd-my-fork\"\n",
        "\n",
        "  def extract_zip(zip_path, extract_path):\n",
        "      with zipfile.ZipFile(zip_path, 'r') as zipf:\n",
        "          print(\"Extracting IMG.......\")\n",
        "          zipf.extractall(extract_path)\n",
        "\n",
        "  extract_zip(zip_path, sd_fork_folder)\n",
        "  print(\"Extraction Finshed\")\n",
        "  !rm -rf \"/content/Sd-my-fork.zip\"\n",
        "elif installation_type == \"Fresh install\":\n",
        "  print(\"Creating new Directory.........\")\n",
        "  !rm -rf \"/content/Sd-my-fork\"\n",
        "  !git clone https://github.com/pokewizardSAM/Sd-my-fork.git\n",
        "  print(\"\"\"\n",
        "  >>> Please wait for the model to download <<<\"\"\")\n",
        "  !rm \"/content/Sd-my-fork/models/Stable-diffusion/v2-1_768-ema-pruned.safetensors\"\n",
        "  !curl -l \"https://cdn-lfs.huggingface.co/repos/ba/4b/ba4bf0af96689e1dfe4cef764ec2265769a9c360efe9b8d439d05dd13c0b12de/ed989d673dbf0153d1cd16994c1bfa27a0f13de1e60665aabcb99334ca5b78e9?response-content-disposition=attachment%3B+filename*%3DUTF-8%27%27DreamShaper_7_pruned.safetensors%3B+filename%3D%22DreamShaper_7_pruned.safetensors%22%3B&Expires=1689493890&Policy=eyJTdGF0ZW1lbnQiOlt7IkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTY4OTQ5Mzg5MH19LCJSZXNvdXJjZSI6Imh0dHBzOi8vY2RuLWxmcy5odWdnaW5nZmFjZS5jby9yZXBvcy9iYS80Yi9iYTRiZjBhZjk2Njg5ZTFkZmU0Y2VmNzY0ZWMyMjY1NzY5YTljMzYwZWZlOWI4ZDQzOWQwNWRkMTNjMGIxMmRlL2VkOTg5ZDY3M2RiZjAxNTNkMWNkMTY5OTRjMWJmYTI3YTBmMTNkZTFlNjA2NjVhYWJjYjk5MzM0Y2E1Yjc4ZTk%7EcmVzcG9uc2UtY29udGVudC1kaXNwb3NpdGlvbj0qIn1dfQ__&Signature=ZHjBoN0%7E2md8IBMKjijGXobbEgEq1iMXCJMGGSUA4Cr7-sac9xVNXWjnE1ne3XdV5u5dYbx2lh0v1iG0BkGv545YoJfXaBkgVS4XAxgtpPyGzQYKrVpTY58f54H4%7E5YKD3xE-2RmcRiWFJH-ABHAWzZmoMIzNSPSlQZJ4Nag2He60Y2sl66f6LuQhd8no75tkVfTsNRJpfdz50okvbg7A5SCcWp-iDjBmtEI23JuoyPzRRYZVNAQZvVoK46euGFGbOP0V-vQKakLmL-MRLuWt73Qu20vnrDXBzTj%7E4J-UigrCcAdpE8Un0GdmmI1ryrwsREFVp7fS1JOija4UZbZiQ__&Key-Pair-Id=KVTP0A1DKRTAX\" --output \"/content/Sd-my-fork/models/Stable-diffusion/Dreamshaper.safetensors\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "E7njXO5bRrIE"
      },
      "outputs": [],
      "source": [
        "#@title Here are some model links for easy accessibility (Don't run this)\n",
        "# # Add your models here ..... hue hue\n",
        "# !curl -l \"https://civitai-delivery-worker-prod-2023-06-01.5ac0637cfd0766c97916cefa3764fbdf.r2.cloudflarestorage.com/53515/model/dreamshaper631.SOCX.safetensors?X-Amz-Expires=86400&response-content-disposition=attachment%3B%20filename%3D%22dreamshaper_631BakedVae.safetensors%22&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=2fea663d76bd24a496545da373d610fc/20230615/us-east-1/s3/aws4_request&X-Amz-Date=20230615T094101Z&X-Amz-SignedHeaders=host&X-Amz-Signature=84704e994611131a3d28d37a3a0c4271a1c1f14b7a372ff94a1d805f1bf6cdcd\" --output \"/content/Sd-my-fork/models/Stable-diffusion/Dreamshaper.safetensors\"\n",
        "# !curl -l \"https://civitai-delivery-worker-prod-2023-06-01.5ac0637cfd0766c97916cefa3764fbdf.r2.cloudflarestorage.com/747825/model/majicmixRealv6Fp16.rEwl.safetensors?X-Amz-Expires=86400&response-content-disposition=attachment%3B%20filename%3D%22majicmixRealistic_v6.safetensors%22&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=2fea663d76bd24a496545da373d610fc/20230614/us-east-1/s3/aws4_request&X-Amz-Date=20230614T110839Z&X-Amz-SignedHeaders=host&X-Amz-Signature=6c52e5169a51e86447625cf80032e15c2385672535e13762aef4a0dffbee575f\" --output \"/content/Sd-my-fork/models/Stable-diffusion/MajicMixRealisticV6.safetensors\"\n",
        "# !curl -l \"https://civitai-delivery-worker-prod-2023-06-01.5ac0637cfd0766c97916cefa3764fbdf.r2.cloudflarestorage.com/318995/model/ghostmixV20Fp16.FmfH.safetensors?X-Amz-Expires=86400&response-content-disposition=attachment%3B%20filename%3D%22ghostmix_v20Bakedvae.safetensors%22&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=2fea663d76bd24a496545da373d610fc/20230614/us-east-1/s3/aws4_request&X-Amz-Date=20230614T111134Z&X-Amz-SignedHeaders=host&X-Amz-Signature=6f3a257235d58a46d7c895bed49d0a5f72a6141ec3a49d6f248b9f9bfdaf853f\" --output \"/content/Sd-my-fork/models/Stable-diffusion/GhostMIXv20.safetensors\"\n",
        "\n",
        "\n",
        "# downloading additional models\n",
        "\n",
        "options=[\n",
        "        ('Dreamshaper', \"https://civitai-delivery-worker-prod-2023-06-01.5ac0637cfd0766c97916cefa3764fbdf.r2.cloudflarestorage.com/53515/model/dreamshaper631.SOCX.safetensors?X-Amz-Expires=86400&response-content-disposition=attachment%3B%20filename%3D%22dreamshaper_631BakedVae.safetensors%22&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=2fea663d76bd24a496545da373d610fc/20230615/us-east-1/s3/aws4_request&X-Amz-Date=20230615T094101Z&X-Amz-SignedHeaders=host&X-Amz-Signature=84704e994611131a3d28d37a3a0c4271a1c1f14b7a372ff94a1d805f1bf6cdcd\"),\n",
        "        ('MajicMixRealisticV6', \"https://civitai-delivery-worker-prod-2023-06-01.5ac0637cfd0766c97916cefa3764fbdf.r2.cloudflarestorage.com/747825/model/majicmixRealv6Fp16.rEwl.safetensors?X-Amz-Expires=86400&response-content-disposition=attachment%3B%20filename%3D%22majicmixRealistic_v6.safetensors%22&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=2fea663d76bd24a496545da373d610fc/20230614/us-east-1/s3/aws4_request&X-Amz-Date=20230614T110839Z&X-Amz-SignedHeaders=host&X-Amz-Signature=6c52e5169a51e86447625cf80032e15c2385672535e13762aef4a0dffbee575f\"),\n",
        "        ('GhostMIXv20', \"https://civitai-delivery-worker-prod-2023-06-01.5ac0637cfd0766c97916cefa3764fbdf.r2.cloudflarestorage.com/318995/model/ghostmixV20Fp16.FmfH.safetensors?X-Amz-Expires=86400&response-content-disposition=attachment%3B%20filename%3D%22ghostmix_v20Bakedvae.safetensors%22&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=2fea663d76bd24a496545da373d610fc/20230614/us-east-1/s3/aws4_request&X-Amz-Date=20230614T111134Z&X-Amz-SignedHeaders=host&X-Amz-Signature=6f3a257235d58a46d7c895bed49d0a5f72a6141ec3a49d6f248b9f9bfdaf853f\"),\n",
        "        ('Rev-animated ', \"https://civitai.com/api/download/models/46846\"),\n",
        "        ('Dark-sushi ', \"https://civitai.com/api/download/models/56009\"),\n",
        "        ('realisic vision ', \"https://civitai.com/api/download/models/29460\"),\n",
        "        ('Delibrate v2 ', \"https://huggingface.co/XpucT/Deliberate/raw/main/Deliberate_v2.safetensors\"),\n",
        "        ('ControlNet-v1-1 (control_v11p_sd15_openpose)', \"https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11p_sd15_openpose.pth\"),\n",
        "        ('ControlNet-v1-1 (control_v11e_sd15_ip2p)', \"https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11e_sd15_ip2p.pth\"),\n",
        "        ('ControlNet-v1-1 (control_v11e_sd15_shuffle)', \"https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11e_sd15_shuffle.pth\"),\n",
        "        ('ControlNet-v1-1 (control_v11f1e_sd15_tile)', \"https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11f1e_sd15_tile.pth\"),\n",
        "        ('ControlNet-v1-1 (control_v11f1p_sd15_depth)', \"https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11f1p_sd15_depth.pth\"),\n",
        "        ('ControlNet-v1-1 (control_v11p_sd15_canny)', \"https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11p_sd15_canny.pth\"),\n",
        "        ('ControlNet-v1-1 (control_v11p_sd15_inpaint)', \"https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11p_sd15_inpaint.pth\"),\n",
        "        ('ControlNet-v1-1 (control_v11p_sd15_lineart)', \"https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11p_sd15_lineart.pth\"),\n",
        "        ('ControlNet-v1-1 (control_v11p_sd15_scribble)', \"https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11p_sd15_scribble.pth\"),\n",
        "        ('ControlNet-v1-1 (control_v11p_sd15_softedge)', \"https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11p_sd15_softedge.pth\"),\n",
        "    ]\n",
        "\n",
        "\n",
        "output_paths = [ #this is not so usefull now\n",
        "    \"/content/Sd-my-fork/extensions/sd-webui-controlnet/models/control_v11p_sd15_openpose.pth\",\n",
        "    \"/content/Sd-my-fork/extensions/sd-webui-controlnet/models/control_v11e_sd15_ip2p.pth\",\n",
        "    \"/content/Sd-my-fork/extensions/sd-webui-controlnet/models/control_v11e_sd15_shuffle.pth\",\n",
        "    \"/content/Sd-my-fork/extensions/sd-webui-controlnet/models/control_v11f1e_sd15_tile.pth\",\n",
        "    \"/content/Sd-my-fork/extensions/sd-webui-controlnet/models/control_v11f1p_sd15_depth.pth\",\n",
        "    \"/content/Sd-my-fork/extensions/sd-webui-controlnet/models/control_v11p_sd15_canny.pth\",\n",
        "    \"/content/Sd-my-fork/extensions/sd-webui-controlnet/models/control_v11p_sd15_inpaint.pth\",\n",
        "    \"/content/Sd-my-fork/extensions/sd-webui-controlnet/models/control_v11p_sd15_lineart.pth\",\n",
        "    \"/content/Sd-my-fork/extensions/sd-webui-controlnet/models/control_v11p_sd15_scribble.pth\",\n",
        "    \"/content/Sd-my-fork/extensions/sd-webui-controlnet/models/control_v11p_sd15_softedge.pth\"\n",
        "]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "PQFIBH91pTIS"
      },
      "outputs": [],
      "source": [
        "#@title Terminal window here (optional)\n",
        "!pip install colab-xterm\n",
        "%load_ext colabxterm\n",
        "%xterm\n",
        "%reload_ext colabxterm"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "r501-8w2aLgr"
      },
      "source": [
        "#<h2>Step3: Launching SD-WEBUI<h2>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fHtkVbvrEaWN",
        "outputId": "ed1123a2-ba1d-4e4a-832f-3aaf720b1e99"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/Sd-my-fork\n",
            "fatal: No names found, cannot describe anything.\n",
            "Python 3.10.12 (main, Jun  7 2023, 12:45:35) [GCC 9.4.0]\n",
            "Version: <none>\n",
            "Commit hash: baf6946e06249c5af9851c60171692c44ef633e0\n",
            "Installing requirements\n",
            "\n",
            "\n",
            "Checking roop requirements\n",
            "Install insightface==0.7.3\n",
            "Installing sd-webui-roop requirement: insightface==0.7.3\n",
            "Install onnx==1.14.0\n",
            "Installing sd-webui-roop requirement: onnx==1.14.0\n",
            "Install onnxruntime==1.15.0\n",
            "Installing sd-webui-roop requirement: onnxruntime==1.15.0\n",
            "Install opencv-python==4.7.0.72\n",
            "Installing sd-webui-roop requirement: opencv-python==4.7.0.72\n",
            "\n",
            "\n",
            "\n",
            "Installing requirements for TemporalKit extension\n",
            "\n",
            "\n",
            "Launching Web UI with arguments: --xformers --lowram --medvram --force-enable-xformers --disable-safe-unpickle --disable-nan-check --skip-python-version-check --skip-version-check --share --listen --enable-insecure-extension-access\n",
            "2023-07-10 14:47:43.480572: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
            "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
            "2023-07-10 14:47:45.297258: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
            "ALSA lib confmisc.c:767:(parse_card) cannot find card '0'\n",
            "ALSA lib conf.c:4732:(_snd_config_evaluate) function snd_func_card_driver returned error: No such file or directory\n",
            "ALSA lib confmisc.c:392:(snd_func_concat) error evaluating strings\n",
            "ALSA lib conf.c:4732:(_snd_config_evaluate) function snd_func_concat returned error: No such file or directory\n",
            "ALSA lib confmisc.c:1246:(snd_func_refer) error evaluating name\n",
            "ALSA lib conf.c:4732:(_snd_config_evaluate) function snd_func_refer returned error: No such file or directory\n",
            "ALSA lib conf.c:5220:(snd_config_expand) Evaluate error: No such file or directory\n",
            "ALSA lib pcm.c:2642:(snd_pcm_open_noupdate) Unknown PCM default\n",
            "ALSA lib confmisc.c:767:(parse_card) cannot find card '0'\n",
            "ALSA lib conf.c:4732:(_snd_config_evaluate) function snd_func_card_driver returned error: No such file or directory\n",
            "ALSA lib confmisc.c:392:(snd_func_concat) error evaluating strings\n",
            "ALSA lib conf.c:4732:(_snd_config_evaluate) function snd_func_concat returned error: No such file or directory\n",
            "ALSA lib confmisc.c:1246:(snd_func_refer) error evaluating name\n",
            "ALSA lib conf.c:4732:(_snd_config_evaluate) function snd_func_refer returned error: No such file or directory\n",
            "ALSA lib conf.c:5220:(snd_config_expand) Evaluate error: No such file or directory\n",
            "ALSA lib pcm.c:2642:(snd_pcm_open_noupdate) Unknown PCM default\n",
            "Model Downloader v1.0.6 fixed\n",
            "Checking Directories...\n",
            "all Directories already Created.\n",
            "2023-07-10 14:47:58,413 - ControlNet - \u001b[0;32mINFO\u001b[0m - ControlNet v1.1.231\n",
            "ControlNet preprocessor location: /content/Sd-my-fork/extensions/sd-webui-controlnet/annotator/downloads\n",
            "2023-07-10 14:47:58,688 - ControlNet - \u001b[0;32mINFO\u001b[0m - ControlNet v1.1.231\n",
            "2023-07-10 14:48:00,224 - roop - \u001b[0;32mINFO\u001b[0m - roop v0.0.2\n",
            "2023-07-10 14:48:00,225 - roop - \u001b[0;32mINFO\u001b[0m - roop v0.0.2\n",
            "Loading weights [2d0010aca5] from /content/Sd-my-fork/models/Stable-diffusion/darkSushi25D25D_v20/darkSushi25D25D_v20.safetensors\n",
            "\u001b[0;32m*Deforum ControlNet support: enabled*\u001b[0m\n",
            "Running on local URL:  http://0.0.0.0:7860\n",
            "Running on public URL: https://7c10831a04501db8e5.gradio.live\n",
            "\n",
            "This share link expires in 72 hours. For free permanent hosting and GPU upgrades (NEW!), check out Spaces: https://huggingface.co/spaces\n",
            "Startup time: 29.7s (import torch: 10.7s, import gradio: 1.0s, import ldm: 2.1s, other imports: 2.1s, setup codeformer: 0.2s, load scripts: 5.7s, create ui: 0.9s, gradio launch: 6.9s).\n",
            "Creating model from config: /content/Sd-my-fork/configs/v1-inference.yaml\n",
            "LatentDiffusion: Running in eps-prediction mode\n",
            "DiffusionWrapper has 859.52 M params.\n",
            "Applying optimization: xformers... done.\n",
            "Textual inversion embeddings loaded(0): \n",
            "Model loaded in 15.1s (load weights from disk: 9.2s, create model: 0.9s, apply weights to model: 3.5s, apply half(): 1.4s).\n",
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            "\n",
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            "Interrupted with signal 2 in <frame at 0x7f43a968c580, file '/usr/lib/python3.10/threading.py', line 324, code wait>\n"
          ]
        }
      ],
      "source": [
        "#@title Stable-Diffusion Takes off here\n",
        "%cd /content/Sd-my-fork\n",
        "\n",
        "secure_login = False #@param {type: \"boolean\"}\n",
        "username = \"Sameer\"  #@param {type: \"string\"}\n",
        "password = \"i23u2e8un8e2umzez83ue2n3u4m0e9wudniomumx\"  #@param {type: \"string\"}\n",
        "\n",
        "if secure_login:\n",
        "  !python launch.py --xformers --force-enable-xformers --disable-safe-unpickle --disable-nan-check --skip-python-version-check --skip-version-check --share --listen --enable-insecure-extension-access --gradio-auth {username}:{password}\n",
        "else:\n",
        "  !python launch.py --xformers --lowram --medvram --force-enable-xformers --disable-safe-unpickle --disable-nan-check --skip-python-version-check --skip-version-check --share --listen --enable-insecure-extension-access"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "T9vo8zrdrXj2"
      },
      "outputs": [],
      "source": [
        "#@title FIX: If it crashes too much try running this\n",
        "%cd \"/content/Sd-my-fork\"\n",
        "!git stash\n",
        "!git checkout baf6946e06249c5af9851c60171692c44ef633e0\n",
        "# !git --no-pager log --decorate > log.txt"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3T279tUzbObR"
      },
      "source": [
        "#Some basic utilities"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wTuS04O2v8x3",
        "outputId": "558a574d-5e60-4cfb-90ae-73faef9efd4c"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Target directory: /usr\n",
            "Directory size is 24.19 GB\n"
          ]
        }
      ],
      "source": [
        "#@title Input directory and unit of measurement\n",
        "\n",
        "# import os\n",
        "# import sys\n",
        "# # from google.colab import drive\n",
        "\n",
        "# # drive.mount('/content/gdrive')\n",
        "# gdrive_path = r'/content/gdrive/My Drive'\n",
        "# drive_path = r'/content/My_Drive'\n",
        "# os.symlink(gdrive_path, drive_path)\n",
        "# sys.path.insert(0, drive_path)\n",
        "# print('Working Google Drive Path:', drive_path)\n",
        "\n",
        "# Credit:\n",
        "# https://stackoverflow.com/a/1392549\n",
        "\n",
        "def get_size(start_path = '.', unit='MB'):\n",
        "    total_size = 0\n",
        "    for dirpath, dirnames, filenames in os.walk(start_path):\n",
        "        for f in filenames:\n",
        "            fp = os.path.join(dirpath, f)\n",
        "            # skip if it is symbolic link\n",
        "            if not os.path.islink(fp):\n",
        "                total_size += os.path.getsize(fp)\n",
        "\n",
        "    if unit == 'MB':\n",
        "      total_size *= 1e-6\n",
        "    elif unit == 'GB':\n",
        "      total_size *= 1e-9\n",
        "    elif unit == 'TB':\n",
        "      total_size *= 1e-12\n",
        "\n",
        "    return total_size\n",
        "\n",
        "target_dir = '/usr' #@param {type: 'string'}\n",
        "output_unit = 'GB' #@param ['MB', 'GB', 'TB']\n",
        "\n",
        "dir_size = round(get_size(target_dir, output_unit), 2)\n",
        "print('Target directory:', target_dir)\n",
        "print('Directory size is', dir_size, output_unit)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "mQw8wOyc4s4A",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8fe08b87-051b-4ca7-ab12-aa21338d6479"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Already up to date.\n",
            "error: Your local changes to the following files would be overwritten by merge:\n",
            "\twebui.sh\n",
            "Please commit your changes or stash them before you merge.\n",
            "Aborting\n"
          ]
        }
      ],
      "source": [
        "#@title updating the current install with latest git commmits\n",
        "\n",
        "#@markdown ---> This only updates your version in the current colab runtime, if you want to make the changes permanent take a backup of the image somewhere.\n",
        "!cd \"/content/Sd-my-fork\"\n",
        "!git fetch\n",
        "# !git stash\n",
        "!git merge origin/master\n",
        "!git stash apply"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "egaiFVmEL93g"
      },
      "outputs": [],
      "source": [
        "\n",
        "#@title Backup (save to drive)\n",
        "#-----------------------------------------------------\n",
        "#  this part is customisable for your own needs\n",
        "#-----------------------------------------------------\n",
        "\n",
        "#--> making the zip file\n",
        "import shutil\n",
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive',force_remount=True)\n",
        "\n",
        "only_create_img = False #@param {type: \"boolean\"}\n",
        "Sd_Folder = \"/content/Sd-my-fork\"\n",
        "zip_path = \"/content/Sd-my-fork\"\n",
        "def zip_folder(folder_path, zip_path):\n",
        "    shutil.make_archive(zip_path, 'zip', folder_path)\n",
        "\n",
        "if only_create_img:\n",
        "  zip_folder(Sd_Folder,zip_path)\n",
        "else:\n",
        "  zip_folder(Sd_Folder,zip_path)\n",
        "  # -->for backup\n",
        "  folder_path = \"/content/gdrive/MyDrive/\"\n",
        "  print(\"Copying files..........\")\n",
        "  shutil.copy2(\"/content/Sd-my-fork.zip\", folder_path)\n",
        "  print(\"Copy successful..........\")\n",
        "\n",
        "\n",
        "\n",
        "#--> alternate method for moving\n",
        "# %mv \"/content/Sd-my-fork.zip\" \"/content/gdrive/MyDrive\""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "biBsWw96f8w2"
      },
      "source": [
        "#Mega Backup (upload/download)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "zS5ZN1BFq-jn"
      },
      "outputs": [],
      "source": [
        "# @markdown <center><h2>Input your Mega Id and Password</h2></center><br>\n",
        "\n",
        "# Credits : https://github.com/surajbahadur591\n",
        "\n",
        "from functools import wraps\n",
        "import errno\n",
        "import os\n",
        "import signal\n",
        "import subprocess\n",
        "import shlex\n",
        "\n",
        "\n",
        "class TimeoutError(Exception):\n",
        "    pass\n",
        "\n",
        "\n",
        "def timeout(seconds=10, error_message=os.strerror(errno.ETIME)):\n",
        "    def decorator(func):\n",
        "        def _handle_timeout(signum, frame):\n",
        "            raise TimeoutError(error_message)\n",
        "\n",
        "        def wrapper(*args, **kwargs):\n",
        "            signal.signal(signal.SIGALRM, _handle_timeout)\n",
        "            signal.alarm(seconds)\n",
        "            try:\n",
        "                result = func(*args, **kwargs)\n",
        "            finally:\n",
        "                signal.alarm(0)\n",
        "            return result\n",
        "\n",
        "        return wraps(func)(wrapper)\n",
        "\n",
        "    return decorator\n",
        "\n",
        "\n",
        "if not os.path.exists(\"/root/.ipython/ocr.py\"):\n",
        "    from subprocess import run\n",
        "    from shlex import split\n",
        "\n",
        "    shellCmd = \"wget -qq https://raw.githubusercontent.com/biplobsd/OneClickRun/master/res/ocr.py \\\n",
        "                    -O /root/.ipython/ocr.py\"\n",
        "    run(split(shellCmd))\n",
        "from ocr import runSh\n",
        "\n",
        "@timeout(10)\n",
        "def runShT(args):\n",
        "    return runSh(args, output=True)\n",
        "\n",
        "\n",
        "# MEGAcmd installing\n",
        "if not os.path.exists(\"/usr/bin/mega-cmd\"):\n",
        "    print(\"Installing MEGA ...\")\n",
        "    runSh('sudo apt-get -y update')\n",
        "    runSh('sudo apt-get -y install libmms0 libc-ares2 libc6 libcrypto++6 libgcc1 libmediainfo0v5 libpcre3 libpcrecpp0v5 libssl1.1 libstdc++6 libzen0v5 zlib1g apt-transport-https')\n",
        "    runSh('sudo curl -sL -o /var/cache/apt/archives/MEGAcmd.deb https://mega.nz/linux/MEGAsync/Debian_9.0/amd64/megacmd-Debian_9.0_amd64.deb', output=True)\n",
        "    runSh('sudo dpkg -i /var/cache/apt/archives/MEGAcmd.deb', output=True)\n",
        "    print(\"MEGA is installed.\")\n",
        "else:\n",
        "    !pkill mega-cmd\n",
        "\n",
        "# INPUT YOUR MEGA ID\n",
        "\n",
        "USERNAME = \"\"  # @param {type:\"string\"}\n",
        "PASSWORD = \"\"  # @param {type:\"string\"}\n",
        "if not (USERNAME == \"\" or PASSWORD == \"\"):\n",
        "    try:\n",
        "        runShT(f\"mega-login {USERNAME} {PASSWORD}\")\n",
        "    except TimeoutError:\n",
        "        runSh('mega-whoami', output=True)\n",
        "else:\n",
        "    print(\"Please Input your Mega IDs.\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "-XsgE21WrJL3"
      },
      "outputs": [],
      "source": [
        "#@title <center>Upload img to Mega  <center>\n",
        "import time\n",
        "import subprocess\n",
        "import contextlib\n",
        "from IPython.display import clear_output\n",
        "!cd /\n",
        "PATH_TO_FILE = \"/content/Sd-my-fork/models/Stable-diffusion/sd_xl_refiner_0.9.safetensors\"  # @param {type:\"string\"}\n",
        "\n",
        "newlines = ['\\n', '\\r\\n', '\\r']\n",
        "\n",
        "\n",
        "def unbuffered(proc, stream='stdout'):\n",
        "    stream = getattr(proc, stream)\n",
        "    with contextlib.closing(stream):\n",
        "        while True:\n",
        "            out = []\n",
        "            last = stream.read(1)\n",
        "            if last == '' and proc.poll() is not None:\n",
        "                break\n",
        "            while last not in newlines:\n",
        "                if last == '' and proc.poll() is not None:\n",
        "                    break\n",
        "                out.append(last)\n",
        "                last = stream.read(1)\n",
        "            out = ''.join(out)\n",
        "            yield out\n",
        "\n",
        "\n",
        "def transfer(path):\n",
        "    cmd = ['mega-put', path, '/colab']\n",
        "    proc = subprocess.Popen(\n",
        "        cmd,\n",
        "        stdout=subprocess.PIPE,\n",
        "        stderr=subprocess.STDOUT,\n",
        "        universal_newlines=True,\n",
        "    )\n",
        "    for line in unbuffered(proc):\n",
        "        clear_output(wait=True)\n",
        "        print(line)\n",
        "\n",
        "\n",
        "try:\n",
        "    transfer(PATH_TO_FILE)\n",
        "except FileNotFoundError:\n",
        "    print(\"Please log in to your account!\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "NlXKyudf0xpx"
      },
      "outputs": [],
      "source": [
        "#@title <center>Download img from mega<center>\n",
        "import sys\n",
        "import os\n",
        "import urllib.request\n",
        "import time\n",
        "import subprocess\n",
        "import contextlib\n",
        "from IPython.display import clear_output\n",
        "\n",
        "HOME = os.path.expanduser(\"~\")\n",
        "\n",
        "if not os.path.exists(f\"{HOME}/.ipython/ocr.py\"):\n",
        "    hCode = \"https://raw.githubusercontent.com/biplobsd/OneClickRun/master/res/ocr.py\"\n",
        "    urllib.request.urlretrieve(hCode, f\"{HOME}/.ipython/ocr.py\")\n",
        "\n",
        "from ocr import runSh, loadingAn\n",
        "\n",
        "COPY_MEGA_URL = \"\"  #@param {type:\"string\"}\n",
        "OUTPUT_PATH_OF_GDRIVE = \"\"  #@param {type:\"string\"}\n",
        "\n",
        "if not OUTPUT_PATH_OF_GDRIVE:\n",
        "    os.makedirs(\"downloads\", exist_ok=True)\n",
        "    OUTPUT_PATH_OF_GDRIVE = \"downloads\"\n",
        "\n",
        "# MEGAcmd installing\n",
        "if not os.path.exists(\"/usr/bin/mega-cmd\"):\n",
        "    loadingAn()\n",
        "    print(\"Installing MEGA ...\")\n",
        "    runSh('sudo apt-get -y update')\n",
        "    runSh('sudo apt-get -y install libmms0 libc-ares2 libc6 libcrypto++6 libgcc1 libmediainfo0v5 libpcre3 libpcrecpp0v5 libssl1.1 libstdc++6 libzen0v5 zlib1g apt-transport-https')\n",
        "    runSh('sudo curl -sL -o /var/cache/apt/archives/MEGAcmd.deb https://mega.nz/linux/MEGAsync/Debian_9.0/amd64/megacmd-Debian_9.0_amd64.deb', output=True)\n",
        "    runSh('sudo dpkg -i /var/cache/apt/archives/MEGAcmd.deb', output=True)\n",
        "    print(\"MEGA is installed.\")\n",
        "    clear_output()\n",
        "\n",
        "newlines = ['\\n', '\\r\\n', '\\r']\n",
        "\n",
        "\n",
        "def unbuffered(proc, stream='stdout'):\n",
        "    stream = getattr(proc, stream)\n",
        "    with contextlib.closing(stream):\n",
        "        while True:\n",
        "            out = []\n",
        "            last = stream.read(1)\n",
        "            if last == '' and proc.poll() is not None:\n",
        "                break\n",
        "            while last not in newlines:\n",
        "                if last == '' and proc.poll() is not None:\n",
        "                    break\n",
        "                out.append(last)\n",
        "                last = stream.read(1)\n",
        "            out = ''.join(out)\n",
        "            yield out\n",
        "\n",
        "\n",
        "def transfer():\n",
        "    import codecs\n",
        "    decoder = codecs.getincrementaldecoder(\"UTF-8\")()\n",
        "    cmd = [\"mega-get\", COPY_MEGA_URL, OUTPUT_PATH_OF_GDRIVE]\n",
        "    proc = subprocess.Popen(\n",
        "        cmd,\n",
        "        stdout=subprocess.PIPE,\n",
        "        stderr=subprocess.STDOUT,\n",
        "        universal_newlines=True,\n",
        "    )\n",
        "    for line in unbuffered(proc):\n",
        "        print(line)\n",
        "\n",
        "\n",
        "transfer()"
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}