stable_diffusion_v1_4.ipynb

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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/hiro106/stable-diffusion-trial/blob/main/stable_diffusion_v1_4.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Google Colab で はじめる Stable Diffusion v1.4  \n",
        "https://note.com/npaka/n/ndd549d2ce556"
      ],
      "metadata": {
        "id": "d75Ap7EYK6Eg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# パッケージのインストール\n",
        "!pip install diffusers==0.2.4 transformers scipy ftfy"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Q_oRorY2LKRB",
        "outputId": "44473616-d8c8-4ee2-d369-79c1d477d4e9"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting diffusers==0.2.4\n",
            "  Downloading diffusers-0.2.4-py3-none-any.whl (112 kB)\n",
            "\u001b[K     |████████████████████████████████| 112 kB 4.7 MB/s \n",
            "\u001b[?25hCollecting transformers\n",
            "  Downloading transformers-4.24.0-py3-none-any.whl (5.5 MB)\n",
            "\u001b[K     |████████████████████████████████| 5.5 MB 30.2 MB/s \n",
            "\u001b[?25hRequirement already satisfied: scipy in /usr/local/lib/python3.7/dist-packages (1.7.3)\n",
            "Collecting ftfy\n",
            "  Downloading ftfy-6.1.1-py3-none-any.whl (53 kB)\n",
            "\u001b[K     |████████████████████████████████| 53 kB 1.8 MB/s \n",
            "\u001b[?25hRequirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.7/dist-packages (from diffusers==0.2.4) (2022.6.2)\n",
            "Requirement already satisfied: torch>=1.4 in /usr/local/lib/python3.7/dist-packages (from diffusers==0.2.4) (1.12.1+cu113)\n",
            "Collecting huggingface-hub<1.0,>=0.8.1\n",
            "  Downloading huggingface_hub-0.10.1-py3-none-any.whl (163 kB)\n",
            "\u001b[K     |████████████████████████████████| 163 kB 63.1 MB/s \n",
            "\u001b[?25hRequirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from diffusers==0.2.4) (1.21.6)\n",
            "Requirement already satisfied: Pillow in /usr/local/lib/python3.7/dist-packages (from diffusers==0.2.4) (7.1.2)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.7/dist-packages (from diffusers==0.2.4) (3.8.0)\n",
            "Requirement already satisfied: importlib-metadata in /usr/local/lib/python3.7/dist-packages (from diffusers==0.2.4) (4.13.0)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from diffusers==0.2.4) (2.23.0)\n",
            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.7/dist-packages (from huggingface-hub<1.0,>=0.8.1->diffusers==0.2.4) (4.1.1)\n",
            "Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.7/dist-packages (from huggingface-hub<1.0,>=0.8.1->diffusers==0.2.4) (21.3)\n",
            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.7/dist-packages (from huggingface-hub<1.0,>=0.8.1->diffusers==0.2.4) (6.0)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.7/dist-packages (from huggingface-hub<1.0,>=0.8.1->diffusers==0.2.4) (4.64.1)\n",
            "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from packaging>=20.9->huggingface-hub<1.0,>=0.8.1->diffusers==0.2.4) (3.0.9)\n",
            "Collecting tokenizers!=0.11.3,<0.14,>=0.11.1\n",
            "  Downloading tokenizers-0.13.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.6 MB)\n",
            "\u001b[K     |████████████████████████████████| 7.6 MB 48.5 MB/s \n",
            "\u001b[?25hRequirement already satisfied: wcwidth>=0.2.5 in /usr/local/lib/python3.7/dist-packages (from ftfy) (0.2.5)\n",
            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata->diffusers==0.2.4) (3.10.0)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->diffusers==0.2.4) (2022.9.24)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->diffusers==0.2.4) (3.0.4)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->diffusers==0.2.4) (2.10)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->diffusers==0.2.4) (1.24.3)\n",
            "Installing collected packages: tokenizers, huggingface-hub, transformers, ftfy, diffusers\n",
            "Successfully installed diffusers-0.2.4 ftfy-6.1.1 huggingface-hub-0.10.1 tokenizers-0.13.2 transformers-4.24.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# トークン変数の準備\n",
        "YOUR_TOKEN=\"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\""
      ],
      "metadata": {
        "id": "fcglxE5cLKT5"
      },
      "execution_count": 4,
      "outputs": []
    },
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      "source": [
        "from diffusers import StableDiffusionPipeline\n",
        "\n",
        "# StableDiffusionパイプラインの準備\n",
        "pipe = StableDiffusionPipeline.from_pretrained(\"CompVis/stable-diffusion-v1-4\", use_auth_token=YOUR_TOKEN)\n",
        "pipe.to(\"cuda\")"
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              "StableDiffusionPipeline {\n",
              "  \"_class_name\": \"StableDiffusionPipeline\",\n",
              "  \"_diffusers_version\": \"0.2.4\",\n",
              "  \"feature_extractor\": [\n",
              "    \"transformers\",\n",
              "    \"CLIPFeatureExtractor\"\n",
              "  ],\n",
              "  \"safety_checker\": [\n",
              "    \"stable_diffusion\",\n",
              "    \"StableDiffusionSafetyChecker\"\n",
              "  ],\n",
              "  \"scheduler\": [\n",
              "    \"diffusers\",\n",
              "    \"PNDMScheduler\"\n",
              "  ],\n",
              "  \"text_encoder\": [\n",
              "    \"transformers\",\n",
              "    \"CLIPTextModel\"\n",
              "  ],\n",
              "  \"tokenizer\": [\n",
              "    \"transformers\",\n",
              "    \"CLIPTokenizer\"\n",
              "  ],\n",
              "  \"unet\": [\n",
              "    \"diffusers\",\n",
              "    \"UNet2DConditionModel\"\n",
              "  ],\n",
              "  \"vae\": [\n",
              "    \"diffusers\",\n",
              "    \"AutoencoderKL\"\n",
              "  ]\n",
              "}"
            ]
          },
          "metadata": {},
          "execution_count": 5
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 画像生成\n",
        "prompt = \"cosmetic bottle reasonable price\"\n",
        "image = pipe(prompt)[\"sample\"][0]\n",
        "image.save(f\"japanese_cat_skipping.png\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 49,
          "referenced_widgets": [
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            "4435885cbbfc4619a5d40e29c29883d9",
            "6cde51c4f6c14c1d93a38faa61ab494a"
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        "id": "JQAOOKPQLKY8",
        "outputId": "4bfc01f4-2b86-4605-dc12-7f69dcc50613"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "0it [00:00, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "1b21a63a7d1747d792782380153f492e"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 画像生成\n",
        "prompt = \"cosmetic bottle authority\"\n",
        "image = pipe(prompt)[\"sample\"][0]\n",
        "image.save(f\"japanese_cat_skipping2.png\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 49,
          "referenced_widgets": [
            "9cebf31a87424216b6aadc9c59582c8e",
            "2f03b9d125aa4c84b63ff9c4476407fc",
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            "971f548da69c4b0884ad9fc6f1f28b08",
            "ac7394d7d0f347d38c85acfcd5b07ccf",
            "46dd819666ac40f6a717ce5f68934609",
            "3f4655ed8e44478ca8639a4c612b89a0",
            "227a38723c9949728c2acacf7031193c",
            "1c884b3f92744bed9c0f6e2f2d99f3c7",
            "29ee7987baf949dda4476040be3996a1",
            "f04e9f3810ed4a5ba3d18b761c1b0052"
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        },
        "id": "Twq9kxv5NVo0",
        "outputId": "919f8b78-f46c-4694-9190-79ade6b40744"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "0it [00:00, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "9cebf31a87424216b6aadc9c59582c8e"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 画像生成\n",
        "prompt = \"japanese cat skipping\"\n",
        "image = pipe(prompt)[\"sample\"][0]\n",
        "image.save(f\"japanese_cat_skipping3.png\")"
      ],
      "metadata": {
        "id": "IF_tYMX-NlNV"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# 画像生成\n",
        "prompt = \"Japanese prime minister in Chiyoda ward\"\n",
        "image = pipe(prompt)[\"sample\"][0]\n",
        "image.save(f\"Japanese_prime_minister_in_Chiyoda_ward.png\")"
      ],
      "metadata": {
        "id": "FWMUKTb8LKbg"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# 画像生成\n",
        "prompt = \"Japanese prime minister in Chiyoda ward\"\n",
        "image = pipe(prompt)[\"sample\"][0]\n",
        "image.save(f\"Japanese_prime_minister_in_Chiyoda_ward_2.png\")"
      ],
      "metadata": {
        "id": "bHorhWLiLKeG"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# 画像生成\n",
        "prompt = \"Japanese prime minister in Chiyoda ward\"\n",
        "image = pipe(prompt)[\"sample\"][0]\n",
        "image.save(f\"Japanese_prime_minister_in_Chiyoda_ward_3.png\")"
      ],
      "metadata": {
        "id": "E2tWzQ7PLKgg"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# 画像生成\n",
        "prompt = \"Photo of a tiger on the top of Mt. Fuji\"\n",
        "image = pipe(prompt)[\"sample\"][0]\n",
        "image.save(f\"Photo of a tiger on the top of Mt. Fuji.png\")"
      ],
      "metadata": {
        "id": "w-RLjvkcLKi8"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# 画像生成\n",
        "prompt = \"Photo of a tiger on the top of Mt. Fuji\"\n",
        "image = pipe(prompt)[\"sample\"][0]\n",
        "image.save(f\"Photo of a tiger on the top of Mt. Fuji2.png\")"
      ],
      "metadata": {
        "id": "DEnuJ3AXLKlM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# 画像生成\n",
        "prompt = \"Photo of a tiger on the top of Mt. Fuji\"\n",
        "image = pipe(prompt)[\"sample\"][0]\n",
        "image.save(f\"Photo of a tiger on the top of Mt. Fuji3.png\")"
      ],
      "metadata": {
        "id": "JZjDxg_NO9tf"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# 画像生成\n",
        "prompt = \"Japanese modern art of Samurai\"\n",
        "image = pipe(prompt)[\"sample\"][0]\n",
        "image.save(f\"Japanese modern art of Samurai.png\")"
      ],
      "metadata": {
        "id": "oXS2Gu3_PltU"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# 画像生成\n",
        "prompt = \"Japanese modern art of Samurai\"\n",
        "image = pipe(prompt)[\"sample\"][0]\n",
        "image.save(f\"Japanese modern art of Samurai2.png\")"
      ],
      "metadata": {
        "id": "C1VcIpQgPlv8"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# 画像生成\n",
        "prompt = \"Japanese modern art of Samurai\"\n",
        "image = pipe(prompt)[\"sample\"][0]\n",
        "image.save(f\"Japanese modern art of Samurai3.png\")"
      ],
      "metadata": {
        "id": "PjHYyzXCPly_"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "qoP10syyO9wW"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}