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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": [],
"gpuType": "T4",
"collapsed_sections": [
"UdQ1VHdI8lCf"
]
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
},
"accelerator": "GPU"
},
"cells": [
{
"cell_type": "markdown",
"source": [
"# Colab for roop-unleashed - Gradio version\n",
"https://github.com/C0untFloyd/roop-unleashed\n"
],
"metadata": {
"id": "G9BdiCppV6AS"
}
},
{
"cell_type": "markdown",
"source": [
"Installing & preparing requirements"
],
"metadata": {
"id": "0ZYRNb0AWLLW"
}
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "t1yPuhdySqCq"
},
"outputs": [],
"source": [
"!git clone https://github.com/C0untFloyd/roop-unleashed.git\n",
"%cd roop-unleashed\n",
"!mv config_colab.yaml config.yaml\n",
"!pip install pip install -r requirements.txt"
]
},
{
"cell_type": "markdown",
"source": [
"Running roop-unleashed with default config"
],
"metadata": {
"id": "u_4JQiSlV9Fi"
}
},
{
"cell_type": "code",
"source": [
"!python run.py"
],
"metadata": {
"id": "Is6U2huqSzLE"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"### Download generated images folder\n",
"(only needed if you want to zip the generated output)"
],
"metadata": {
"id": "UdQ1VHdI8lCf"
}
},
{
"cell_type": "code",
"source": [
"import shutil\n",
"import os\n",
"from google.colab import files\n",
"\n",
"def zip_directory(directory_path, zip_path):\n",
" shutil.make_archive(zip_path, 'zip', directory_path)\n",
"\n",
"# Set the directory path you want to download\n",
"directory_path = '/content/roop-unleashed/output'\n",
"\n",
"# Set the zip file name\n",
"zip_filename = 'fake_output.zip'\n",
"\n",
"# Zip the directory\n",
"zip_directory(directory_path, zip_filename)\n",
"\n",
"# Download the zip file\n",
"files.download(zip_filename+'.zip')\n"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 17
},
"id": "oYjWveAmw10X",
"outputId": "5b4c3650-f951-434a-c650-5525a8a70c1e"
},
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<IPython.core.display.Javascript object>"
],
"application/javascript": [
"\n",
" async function download(id, filename, size) {\n",
" if (!google.colab.kernel.accessAllowed) {\n",
" return;\n",
" }\n",
" const div = document.createElement('div');\n",
" const label = document.createElement('label');\n",
" label.textContent = `Downloading \"${filename}\": `;\n",
" div.appendChild(label);\n",
" const progress = document.createElement('progress');\n",
" progress.max = size;\n",
" div.appendChild(progress);\n",
" document.body.appendChild(div);\n",
"\n",
" const buffers = [];\n",
" let downloaded = 0;\n",
"\n",
" const channel = await google.colab.kernel.comms.open(id);\n",
" // Send a message to notify the kernel that we're ready.\n",
" channel.send({})\n",
"\n",
" for await (const message of channel.messages) {\n",
" // Send a message to notify the kernel that we're ready.\n",
" channel.send({})\n",
" if (message.buffers) {\n",
" for (const buffer of message.buffers) {\n",
" buffers.push(buffer);\n",
" downloaded += buffer.byteLength;\n",
" progress.value = downloaded;\n",
" }\n",
" }\n",
" }\n",
" const blob = new Blob(buffers, {type: 'application/binary'});\n",
" const a = document.createElement('a');\n",
" a.href = window.URL.createObjectURL(blob);\n",
" a.download = filename;\n",
" div.appendChild(a);\n",
" a.click();\n",
" div.remove();\n",
" }\n",
" "
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<IPython.core.display.Javascript object>"
],
"application/javascript": [
"download(\"download_789eab11-93d2-4880-adf3-6aceee0cc5f9\", \"fake_output.zip.zip\", 80125)"
]
},
"metadata": {}
}
]
}
]
} |