{ "nbformat": 4, "nbformat_minor": 0, "metadata": { "colab": { "provenance": [], "authorship_tag": "ABX9TyPKBKhp0febZwFeoBEUFB5r" }, "kernelspec": { "name": "python3", "display_name": "Python 3" }, "language_info": { "name": "python" }, "widgets": { "application/vnd.jupyter.widget-state+json": { "4bd64e113ca7427998bd22fa07c6a5b2": { "model_module": "@jupyter-widgets/controls", "model_name": "ButtonModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ButtonModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ButtonView", "button_style": "success", "description": "✔ Done", "disabled": true, "icon": "", "layout": "IPY_MODEL_b67f1fa6fa7142d6b90c3a04600083d2", "style": "IPY_MODEL_74cc9bb3b6124b8ab184ed5e16bd8cbb", "tooltip": "" } }, "b67f1fa6fa7142d6b90c3a04600083d2": { "model_module": "@jupyter-widgets/base", 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"right": null, "top": null, "visibility": null, "width": null } }, "74cc9bb3b6124b8ab184ed5e16bd8cbb": { "model_module": "@jupyter-widgets/controls", "model_name": "ButtonStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ButtonStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "button_color": null, "font_weight": "" } } } } }, "cells": [ { "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", "Shared_Drive = \"\" #@param {type:\"string\"}\n", "#@markdown - Leave empty if you're not using a shared drive\n", "\n", "print(\"\u001b[0;33mConnecting...\")\n", "drive.mount('/content/gdrive')\n", "\n", "if Shared_Drive!=\"\" and os.path.exists(\"/content/gdrive/Shareddrives\"):\n", " mainpth=\"Shareddrives/\"+Shared_Drive\n", "else:\n", " mainpth=\"MyDrive\"\n", "\n", "clear_output()\n", "inf('\\u2714 Done','success', '50px')\n", "\n", "#@markdown ---" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 49, "referenced_widgets": [ "4bd64e113ca7427998bd22fa07c6a5b2", "b67f1fa6fa7142d6b90c3a04600083d2", "74cc9bb3b6124b8ab184ed5e16bd8cbb" ] }, "id": "PsMA61hEqyny", "outputId": "48da1305-ded8-439b-c904-d6fac6669d7b" }, "execution_count": 1, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Button(button_style='success', description='✔ Done', disabled=True, layout=Layout(min_width='50px'), style=But…" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "4bd64e113ca7427998bd22fa07c6a5b2" } }, "metadata": {} } ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "YXvRbuFFoPQT", "outputId": "d9fc704d-9192-4845-cbd7-91c4fd07b0eb" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Collecting gradio\n", " Downloading gradio-3.50.2-py3-none-any.whl (20.3 MB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m20.3/20.3 MB\u001b[0m \u001b[31m54.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hCollecting aiofiles<24.0,>=22.0 (from gradio)\n", " Downloading aiofiles-23.2.1-py3-none-any.whl (15 kB)\n", "Requirement already satisfied: altair<6.0,>=4.2.0 in /usr/local/lib/python3.10/dist-packages (from gradio) (4.2.2)\n", "Collecting fastapi (from gradio)\n", " Downloading fastapi-0.104.0-py3-none-any.whl (92 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m92.9/92.9 kB\u001b[0m \u001b[31m9.6 MB/s\u001b[0m eta 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/root/.cache/pip/wheels/01/a6/d1/1c0828c304a4283b2c1639a09ad86f83d7c487ef34c6b4a1bf\n", "Successfully built ffmpy\n", "Installing collected packages: pydub, ffmpy, websockets, typing-extensions, semantic-version, python-multipart, orjson, h11, aiofiles, uvicorn, starlette, huggingface-hub, httpcore, httpx, fastapi, gradio-client, gradio\n", " Attempting uninstall: typing-extensions\n", " Found existing installation: typing_extensions 4.5.0\n", " Uninstalling typing_extensions-4.5.0:\n", " Successfully uninstalled typing_extensions-4.5.0\n", "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n", "lida 0.0.10 requires kaleido, which is not installed.\n", "tensorflow-probability 0.22.0 requires typing-extensions<4.6.0, but you have typing-extensions 4.8.0 which is incompatible.\u001b[0m\u001b[31m\n", "\u001b[0mSuccessfully installed aiofiles-23.2.1 fastapi-0.104.0 ffmpy-0.3.1 gradio-3.50.2 gradio-client-0.6.1 h11-0.14.0 httpcore-0.18.0 httpx-0.25.0 huggingface-hub-0.18.0 orjson-3.9.9 pydub-0.25.1 python-multipart-0.0.6 semantic-version-2.10.0 starlette-0.27.0 typing-extensions-4.8.0 uvicorn-0.23.2 websockets-11.0.3\n", "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (2.31.0)\n", "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests) (3.3.0)\n", "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests) (3.4)\n", "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests) (2.0.7)\n", "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests) (2023.7.22)\n", "Requirement already satisfied: pillow in /usr/local/lib/python3.10/dist-packages (9.4.0)\n" ] } ], "source": [ "#@markdown # Install Requirements\n", "\n", "!pip install gradio\n", "!pip install requests\n", "!pip install pillow" ] }, { "cell_type": "code", "source": [ "#@markdown # Run Interface\n", "\n", "import gradio as gr\n", "import requests\n", "import io\n", "import random\n", "import os\n", "from PIL import Image\n", "\n", "HF_READ_TOKEN = \"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\" #@param {type:\"string\"}\n", "API_URL = \"https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0\"\n", "headers = {\"Authorization\": f\"Bearer {HF_READ_TOKEN}\"}\n", "\n", "def query(prompt, is_negative=False, image_style=\"None style\", steps=50, cfg_scale=7, seed=None):\n", " if image_style == \"None style\":\n", " payload = {\n", " \"inputs\": prompt + \", 8k\",\n", " \"is_negative\": is_negative,\n", " \"steps\": steps,\n", " \"cfg_scale\": cfg_scale,\n", " \"seed\": seed if seed is not None else random.randint(-1, 2147483647)\n", " }\n", " elif image_style == \"Cinematic\":\n", " payload = {\n", " \"inputs\": prompt+\", realistic, detailed, textured, skin, hair, eyes, by Alex Huguet, Mike Hill, Ian Spriggs, JaeCheol Park, Marek Denko\",\n", " \"is_negative\": is_negative+\", abstract, cartoon, stylized\",\n", " \"steps\": steps,\n", " \"cfg_scale\": cfg_scale,\n", " \"seed\": seed if seed is not None else random.randint(-1, 2147483647)\n", " }\n", " elif image_style == \"Digital Art\":\n", " payload = {\n", " \"inputs\": prompt + \", faded , vintage , nostalgic , by Jose Villa , Elizabeth Messina , Ryan Brenizer , Jonas Peterson , Jasmine Star\",\n", " \"is_negative\": is_negative + \", sharp , modern , bright\",\n", " \"steps\": steps,\n", " \"cfg_scale\": cfg_scale,\n", " \"seed\": seed if seed is not None else random.randint(-1, 2147483647)\n", " }\n", " elif image_style == \"Portrait\":\n", " payload = {\n", " \"inputs\": prompt + \", soft light, sharp, exposure blend, medium shot, bokeh, (hdr:1.4), high contrast, (cinematic, teal and orange:0.85), (muted colors, dim colors, soothing tones:1.3), low saturation, (hyperdetailed:1.2), (noir:0.4), (natural skin texture, hyperrealism, soft light, sharp:1.2)\",\n", " \"is_negative\": is_negative,\n", " \"steps\": steps,\n", " \"cfg_scale\": cfg_scale,\n", " \"seed\": seed if seed is not None else random.randint(-1, 2147483647)\n", " }\n", " # Вставьте ваш код для запроса к модели и получения изображения\n", " image_bytes = requests.post(API_URL, headers=headers, json=payload).content\n", " image = Image.open(io.BytesIO(image_bytes))\n", " return image\n", "\n", "\n", "css = \"\"\"\n", " .gradio-container {\n", " font-family: 'IBM Plex Sans', sans-serif;\n", " }\n", " .gr-button {\n", " color: white;\n", " border-color: black;\n", " background: black;\n", " }\n", " input[type='range'] {\n", " accent-color: black;\n", " }\n", " .dark input[type='range'] {\n", " accent-color: #dfdfdf;\n", " }\n", " .gradio-container {\n", " max-width: 730px !important;\n", " margin: auto;\n", " padding-top: 1.5rem;\n", " }\n", " #gallery {\n", " min-height: 22rem;\n", " margin-bottom: 15px;\n", " margin-left: auto;\n", " margin-right: auto;\n", " border-bottom-right-radius: .5rem !important;\n", " border-bottom-left-radius: .5rem !important;\n", " }\n", " #gallery>div>.h-full {\n", " min-height: 20rem;\n", " }\n", " .details:hover {\n", " text-decoration: underline;\n", " }\n", " .gr-button {\n", " white-space: nowrap;\n", " }\n", " .gr-button:focus {\n", " border-color: rgb(147 197 253 / var(--tw-border-opacity));\n", " outline: none;\n", " box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000);\n", " --tw-border-opacity: 1;\n", " --tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color);\n", " --tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color);\n", " --tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity));\n", " --tw-ring-opacity: .5;\n", " }\n", " #advanced-btn {\n", " font-size: .7rem !important;\n", " line-height: 19px;\n", " margin-top: 12px;\n", " margin-bottom: 12px;\n", " padding: 2px 8px;\n", " border-radius: 14px !important;\n", " }\n", " #advanced-options {\n", " display: none;\n", " margin-bottom: 20px;\n", " }\n", " .footer {\n", " margin-bottom: 45px;\n", " margin-top: 35px;\n", " text-align: center;\n", " border-bottom: 1px solid #e5e5e5;\n", " }\n", " .footer>p {\n", " font-size: .8rem;\n", " display: inline-block;\n", " padding: 0 10px;\n", " transform: translateY(10px);\n", " background: white;\n", " }\n", " .dark .footer {\n", " border-color: #303030;\n", " }\n", " .dark .footer>p {\n", " background: #0b0f19;\n", " }\n", " .acknowledgments h4{\n", " margin: 1.25em 0 .25em 0;\n", " font-weight: bold;\n", " font-size: 115%;\n", " }\n", " .animate-spin {\n", " animation: spin 1s linear infinite;\n", " }\n", " @keyframes spin {\n", " from {\n", " transform: rotate(0deg);\n", " }\n", " to {\n", " transform: rotate(360deg);\n", " }\n", " }\n", " #share-btn-container {padding-left: 0.5rem !important; padding-right: 0.5rem !important; background-color: #000000; justify-content: center; align-items: center; border-radius: 9999px !important; max-width: 13rem; margin-left: auto;}\n", " div#share-btn-container > div {flex-direction: row;background: black;align-items: center}\n", " #share-btn-container:hover {background-color: #060606}\n", " #share-btn {all: initial; color: #ffffff;font-weight: 600; cursor:pointer; font-family: 'IBM Plex Sans', sans-serif; margin-left: 0.5rem !important; padding-top: 0.5rem !important; padding-bottom: 0.5rem !important;right:0;}\n", " #share-btn * {all: unset}\n", " #share-btn-container div:nth-child(-n+2){width: auto !important;min-height: 0px !important;}\n", " #share-btn-container .wrap {display: none !important}\n", " #share-btn-container.hidden {display: none!important}\n", "\n", " .gr-form{\n", " flex: 1 1 50%; border-top-right-radius: 0; border-bottom-right-radius: 0;\n", " }\n", " #prompt-container{\n", " gap: 0;\n", " }\n", " #prompt-container .form{\n", " border-top-right-radius: 0;\n", " border-bottom-right-radius: 0;\n", " }\n", " #gen-button{\n", " border-top-left-radius:0;\n", " border-bottom-left-radius:0;\n", " }\n", " #prompt-text-input, #negative-prompt-text-input{padding: .45rem 0.625rem}\n", " #component-16{border-top-width: 1px!important;margin-top: 1em}\n", " .image_duplication{position: absolute; width: 100px; left: 50px}\n", " .tabitem{border: 0 !important}\n", "\"\"\"\n", "\n", "with gr.Blocks(css=css) as sdxl:\n", " gr.HTML(\n", " \"\"\"\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "

\n", " 🎨 Super-Fast SDXL on Colab\n", "

\n", "
\n", "

\n", " SDXL is a high quality text-to-image model from Stability AI. This demo is running on HuggingFace Inference API ⚡, to achieve efficient and cost-effective inference of 1024×1024 images. What model?\n", "

\n", " \n", " \"\"\"\n", " )\n", "\n", " with gr.Row():\n", " with gr.Column(scale=1):\n", " text_prompt = gr.Textbox(label=\"Prompt\", placeholder=\"a cute cat\", lines=1, elem_id=\"prompt-text-input\")\n", " negative_prompt = gr.Textbox(label=\"Negative Prompt\", value=\"text, blurry, fuzziness\", lines=1, elem_id=\"negative-prompt-text-input\")\n", " image_style = gr.Dropdown(label=\"Style\", choices=[\"None style\", \"Cinematic\", \"Digital Art\", \"Portrait\"], value=\"None style\", allow_custom_value=False)\n", " text_button = gr.Button(\"Generate\", variant='primary', elem_id=\"gen-button\")\n", " with gr.Row():\n", " with gr.Column(scale=1):\n", " image_output = gr.Image(type=\"pil\", label=\"Output Image\", elem_id=\"gallery\")\n", "\n", " text_button.click(query, inputs=[text_prompt, negative_prompt, image_style], outputs=image_output)\n", "\n", "sdxl.launch(show_api=False)\n" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 626 }, "id": "aI3p1Z6BotJ6", "outputId": "45eb0abc-813e-4962-9d6b-72271b27c982" }, "execution_count": 4, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Setting queue=True in a Colab notebook requires sharing enabled. Setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n", "\n", "Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n", "Running on public URL: https://37a6d604a362850b45.gradio.live\n", "\n", "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "
" ] }, "metadata": {} }, { "output_type": "execute_result", "data": { "text/plain": [] }, "metadata": {}, "execution_count": 4 } ] } ] }