mirror of
https://github.com/iperov/DeepFaceLab.git
synced 2025-08-22 14:24:40 -07:00
Merge pull request #35 from faceshiftlabs/build/add-colab-notebook
Adds colab jupyter notebook
This commit is contained in:
Jeremy Hummel
GitHub
commit
f2ed44f3c4
1 changed files with 728 additions and 0 deletions
728
colab.ipynb
Normal file
728
colab.ipynb
Normal file
|
|
@ -0,0 +1,728 @@
|
|||
{
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 0,
|
||||
"metadata": {
|
||||
"colab": {
|
||||
"name": "DFL_UpToDate.ipynb",
|
||||
"version": "0.3.2",
|
||||
"provenance": [],
|
||||
"collapsed_sections": [
|
||||
"JuVn21kt40Gw",
|
||||
"6jHv35sm-Qiy",
|
||||
"tUNVcbujhm00",
|
||||
"WTuyUxgdLA13",
|
||||
"avAcSL_uvtq_",
|
||||
"f7GNQ7kZx7Ha"
|
||||
]
|
||||
},
|
||||
"kernelspec": {
|
||||
"name": "python3",
|
||||
"display_name": "Python 3"
|
||||
},
|
||||
"accelerator": "GPU"
|
||||
},
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "0cKdTCuv4tXh",
|
||||
"colab_type": "text"
|
||||
},
|
||||
"source": [
|
||||
"# Welcome to DFL-Colab!\n",
|
||||
"\n",
|
||||
"This is an adapted version of the DFL for Google Colab.\n",
|
||||
"\n",
|
||||
"Version 2.5\n",
|
||||
"\n",
|
||||
"# Overview\n",
|
||||
"* Extractor works in full functionality.\n",
|
||||
"* Training can work without preview.\n",
|
||||
"* Converter works in full functionality.\n",
|
||||
"* You can import/export workspace with your Google Drive.\n",
|
||||
"* Import/export and another manipulations with workspace you can do in \"Manage workspace\" block\n",
|
||||
"* Google Colab machine active for 12 hours. DFL-Colab makes a backup of your workspace in training mode, after 11 hours from the start of the session.\n",
|
||||
"* Google does not like long-term heavy calculations. Therefore, for training more than two sessions in a row, use two Google accounts. It is recommended to split your training over 2 accounts, but you can use one Google Drive account to store your workspace.\n",
|
||||
"\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "JuVn21kt40Gw",
|
||||
"colab_type": "text"
|
||||
},
|
||||
"source": [
|
||||
"# Clone Github repository and install requirements\n",
|
||||
"\n",
|
||||
"* Clone Github repository or pull updates\n",
|
||||
"* Requirements install is automatically"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"metadata": {
|
||||
"id": "JG-f2WqT4fLK",
|
||||
"colab_type": "code",
|
||||
"cellView": "both",
|
||||
"colab": {}
|
||||
},
|
||||
"source": [
|
||||
"#@title Clone or pull DeepFaceLab from Github\n",
|
||||
"\n",
|
||||
"Mode = \"clone\" #@param [\"clone\", \"pull\"]\n",
|
||||
"\n",
|
||||
"from pathlib import Path\n",
|
||||
"if (Mode == \"clone\"):\n",
|
||||
" !git clone https://github.com/faceshiftlabs/DeepFaceLab.git\n",
|
||||
"else:\n",
|
||||
" %cd /content/DeepFaceLab\n",
|
||||
" !git pull\n",
|
||||
"\n",
|
||||
"!pip install -r /content/DeepFaceLab/requirements-colab.txt\n",
|
||||
"!pip install --upgrade scikit-image\n",
|
||||
"\n",
|
||||
"if not Path(\"/content/workspace\").exists():\n",
|
||||
" !wget -q --no-check-certificate -r 'https://docs.google.com/uc?export=download&id=1hTH2h6l_4kKrczA8EkN6GyuXx4lzmCnK' -O pretrain_CelebA.zip\n",
|
||||
" !mkdir /content/pretrain\n",
|
||||
" !unzip -q /content/pretrain_CelebA.zip -d /content/pretrain/\n",
|
||||
" !rm /content/pretrain_CelebA.zip\n",
|
||||
"\n",
|
||||
"print(\"Done!\")"
|
||||
],
|
||||
"execution_count": 0,
|
||||
"outputs": []
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "hqwOlJG4MdLC",
|
||||
"colab_type": "text"
|
||||
},
|
||||
"source": [
|
||||
"#Manage workspace\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"* You can import/export workspace or individual data, like model files with Google Drive\n",
|
||||
"* Also, you can use HFS (HTTP Fileserver) for directly import/export you workspace from your computer\n",
|
||||
"* You can clear all workspace or delete part of it\n",
|
||||
"\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"metadata": {
|
||||
"id": "z4w_sUzgOQmL",
|
||||
"colab_type": "code",
|
||||
"cellView": "form",
|
||||
"outputId": "9bfe6ad8-9f60-4707-9874-c2567784e5bc",
|
||||
"colab": {
|
||||
"base_uri": "https://localhost:8080/",
|
||||
"height": 236
|
||||
}
|
||||
},
|
||||
"source": [
|
||||
"#@title Import from Drive\n",
|
||||
"\n",
|
||||
"Mode = \"workspace\" #@param [\"workspace\", \"data_src\", \"data_dst\", \"data_src aligned\", \"data_dst aligned\", \"models\"]\n",
|
||||
"Archive_name = \"workspace.zip\" #@param {type:\"string\"}\n",
|
||||
"\n",
|
||||
"#Mount Google Drive as folder\n",
|
||||
"from google.colab import drive\n",
|
||||
"drive.mount('/content/drive', force_remount=True)\n",
|
||||
"\n",
|
||||
"def zip_and_copy(path, mode):\n",
|
||||
" unzip_cmd=\" -q \"+Archive_name\n",
|
||||
" \n",
|
||||
" %cd $path\n",
|
||||
" copy_cmd = \"/content/drive/My\\ Drive/\"+Archive_name+\" \"+path\n",
|
||||
" !cp $copy_cmd\n",
|
||||
" !unzip $unzip_cmd \n",
|
||||
" !rm $Archive_name\n",
|
||||
"\n",
|
||||
"if Mode == \"workspace\":\n",
|
||||
" zip_and_copy(\"/content\", \"workspace\")\n",
|
||||
"elif Mode == \"data_src\":\n",
|
||||
" zip_and_copy(\"/content/workspace\", \"data_src\")\n",
|
||||
"elif Mode == \"data_dst\":\n",
|
||||
" zip_and_copy(\"/content/workspace\", \"data_dst\")\n",
|
||||
"elif Mode == \"data_src aligned\":\n",
|
||||
" zip_and_copy(\"/content/workspace/data_src\", \"aligned\")\n",
|
||||
"elif Mode == \"data_dst aligned\":\n",
|
||||
" zip_and_copy(\"/content/workspace/data_dst\", \"aligned\")\n",
|
||||
"elif Mode == \"models\":\n",
|
||||
" zip_and_copy(\"/content/workspace\", \"model\")\n",
|
||||
" \n",
|
||||
"print(\"Done!\")\n",
|
||||
"\n"
|
||||
],
|
||||
"execution_count": 0,
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3Aietf%3Awg%3Aoauth%3A2.0%3Aoob&scope=email%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdocs.test%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdrive%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdrive.photos.readonly%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fpeopleapi.readonly&response_type=code\n",
|
||||
"\n",
|
||||
"Enter your authorization code:\n",
|
||||
"··········\n",
|
||||
"Mounted at /content/drive\n",
|
||||
"/content\n",
|
||||
"Done!\n",
|
||||
"Mounted at /content/drive\n",
|
||||
"/content\n",
|
||||
"replace workspace/data_src/aligned/02319.jpg? [y]es, [n]o, [A]ll, [N]one, [r]ename: N\n",
|
||||
"Done!\n"
|
||||
],
|
||||
"name": "stdout"
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"metadata": {
|
||||
"id": "0Y3WfuwoNXqC",
|
||||
"colab_type": "code",
|
||||
"cellView": "form",
|
||||
"colab": {}
|
||||
},
|
||||
"source": [
|
||||
"#@title Export to Drive { form-width: \"30%\" }\n",
|
||||
"Mode = \"workspace\" #@param [\"workspace\", \"data_src\", \"data_dst\", \"data_src aligned\", \"data_dst aligned\", \"merged\", \"models\"]\n",
|
||||
"Archive_name = \"workspace.zip\" #@param {type:\"string\"}\n",
|
||||
"\n",
|
||||
"#Mount Google Drive as folder\n",
|
||||
"from google.colab import drive\n",
|
||||
"drive.mount('/content/drive', force_remount=True)\n",
|
||||
"\n",
|
||||
"def zip_and_copy(path, mode):\n",
|
||||
" zip_cmd=\"-r -q \"+Archive_name+\" \"\n",
|
||||
" \n",
|
||||
" %cd $path\n",
|
||||
" zip_cmd+=mode\n",
|
||||
" !zip $zip_cmd\n",
|
||||
" copy_cmd = \" \"+Archive_name+\" /content/drive/My\\ Drive/\"\n",
|
||||
" !cp $copy_cmd\n",
|
||||
" !rm $Archive_name\n",
|
||||
"\n",
|
||||
"if Mode == \"workspace\":\n",
|
||||
" zip_and_copy(\"/content\", \"workspace\")\n",
|
||||
"elif Mode == \"data_src\":\n",
|
||||
" zip_and_copy(\"/content/workspace\", \"data_src\")\n",
|
||||
"elif Mode == \"data_dst\":\n",
|
||||
" zip_and_copy(\"/content/workspace\", \"data_dst\")\n",
|
||||
"elif Mode == \"data_src aligned\":\n",
|
||||
" zip_and_copy(\"/content/workspace/data_src\", \"aligned\")\n",
|
||||
"elif Mode == \"data_dst aligned\":\n",
|
||||
" zip_and_copy(\"/content/workspace/data_dst\", \"aligned\")\n",
|
||||
"elif Mode == \"merged\":\n",
|
||||
" zip_and_copy(\"/content/workspace/data_dst\", \"merged\")\n",
|
||||
"elif Mode == \"models\":\n",
|
||||
" zip_and_copy(\"/content/workspace\", \"model\")\n",
|
||||
" \n",
|
||||
"print(\"Done!\")\n"
|
||||
],
|
||||
"execution_count": 0,
|
||||
"outputs": []
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"metadata": {
|
||||
"id": "0hIvJtxwTGcb",
|
||||
"colab_type": "code",
|
||||
"colab": {}
|
||||
},
|
||||
"source": [
|
||||
"#@title Import from URL{ form-width: \"30%\", display-mode: \"form\" }\n",
|
||||
"URL = \"http://\" #@param {type:\"string\"}\n",
|
||||
"Mode = \"unzip to content\" #@param [\"unzip to content\", \"unzip to content/workspace\", \"unzip to content/workspace/data_src\", \"unzip to content/workspace/data_src/aligned\", \"unzip to content/workspace/data_dst\", \"unzip to content/workspace/data_dst/aligned\", \"unzip to content/workspace/model\", \"download to content/workspace\"]\n",
|
||||
"\n",
|
||||
"import urllib\n",
|
||||
"from pathlib import Path\n",
|
||||
"\n",
|
||||
"def unzip(zip_path, dest_path):\n",
|
||||
"\n",
|
||||
" \n",
|
||||
" unzip_cmd = \" unzip -q \" + zip_path + \" -d \"+dest_path\n",
|
||||
" !$unzip_cmd \n",
|
||||
" rm_cmd = \"rm \"+dest_path + url_path.name\n",
|
||||
" !$rm_cmd\n",
|
||||
" print(\"Unziped!\")\n",
|
||||
" \n",
|
||||
"\n",
|
||||
"if Mode == \"unzip to content\":\n",
|
||||
" dest_path = \"/content/\"\n",
|
||||
"elif Mode == \"unzip to content/workspace\":\n",
|
||||
" dest_path = \"/content/workspace/\"\n",
|
||||
"elif Mode == \"unzip to content/workspace/data_src\":\n",
|
||||
" dest_path = \"/content/workspace/data_src/\"\n",
|
||||
"elif Mode == \"unzip to content/workspace/data_src/aligned\":\n",
|
||||
" dest_path = \"/content/workspace/data_src/aligned/\"\n",
|
||||
"elif Mode == \"unzip to content/workspace/data_dst\":\n",
|
||||
" dest_path = \"/content/workspace/data_dst/\"\n",
|
||||
"elif Mode == \"unzip to content/workspace/data_dst/aligned\":\n",
|
||||
" dest_path = \"/content/workspace/data_dst/aligned/\"\n",
|
||||
"elif Mode == \"unzip to content/workspace/model\":\n",
|
||||
" dest_path = \"/content/workspace/model/\"\n",
|
||||
"elif Mode == \"download to content/workspace\":\n",
|
||||
" dest_path = \"/content/workspace/\"\n",
|
||||
"\n",
|
||||
"if not Path(\"/content/workspace\").exists():\n",
|
||||
" cmd = \"mkdir /content/workspace; mkdir /content/workspace/data_src; mkdir /content/workspace/data_src/aligned; mkdir /content/workspace/data_dst; mkdir /content/workspace/data_dst/aligned; mkdir /content/workspace/model\"\n",
|
||||
" !$cmd\n",
|
||||
"\n",
|
||||
"url_path = Path(URL)\n",
|
||||
"urllib.request.urlretrieve ( URL, dest_path + url_path.name )\n",
|
||||
"\n",
|
||||
"if (url_path.suffix == \".zip\") and (Mode!=\"download to content/workspace\"):\n",
|
||||
" unzip(dest_path + url_path.name, dest_path)\n",
|
||||
"\n",
|
||||
" \n",
|
||||
"print(\"Done!\")"
|
||||
],
|
||||
"execution_count": 0,
|
||||
"outputs": []
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"metadata": {
|
||||
"id": "7V1sc7rxNKLO",
|
||||
"colab_type": "code",
|
||||
"cellView": "form",
|
||||
"colab": {}
|
||||
},
|
||||
"source": [
|
||||
"#@title Export to URL\n",
|
||||
"URL = \"http://\" #@param {type:\"string\"}\n",
|
||||
"Mode = \"upload workspace\" #@param [\"upload workspace\", \"upload data_src\", \"upload data_dst\", \"upload data_src aligned\", \"upload data_dst aligned\", \"upload merged\", \"upload model\"]\n",
|
||||
"\n",
|
||||
"cmd_zip = \"zip -r -q \"\n",
|
||||
"\n",
|
||||
"def run_cmd(zip_path, curl_url):\n",
|
||||
" cmd_zip = \"zip -r -q \"+zip_path\n",
|
||||
" cmd_curl = \"curl --silent -F \"+curl_url+\" -D out.txt > /dev/null\"\n",
|
||||
" !$cmd_zip\n",
|
||||
" !$cmd_curl\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"if Mode == \"upload workspace\":\n",
|
||||
" %cd \"/content\"\n",
|
||||
" run_cmd(\"workspace.zip workspace/\",\"'data=@/content/workspace.zip' \"+URL)\n",
|
||||
"elif Mode == \"upload data_src\":\n",
|
||||
" %cd \"/content/workspace\"\n",
|
||||
" run_cmd(\"data_src.zip data_src/\", \"'data=@/content/workspace/data_src.zip' \"+URL)\n",
|
||||
"elif Mode == \"upload data_dst\":\n",
|
||||
" %cd \"/content/workspace\"\n",
|
||||
" run_cmd(\"data_dst.zip data_dst/\", \"'data=@/content/workspace/data_dst.zip' \"+URL)\n",
|
||||
"elif Mode == \"upload data_src aligned\":\n",
|
||||
" %cd \"/content/workspace\"\n",
|
||||
" run_cmd(\"data_src_aligned.zip data_src/aligned\", \"'data=@/content/workspace/data_src_aligned.zip' \"+URL )\n",
|
||||
"elif Mode == \"upload data_dst aligned\":\n",
|
||||
" %cd \"/content/workspace\"\n",
|
||||
" run_cmd(\"data_dst_aligned.zip data_dst/aligned/\", \"'data=@/content/workspace/data_dst_aligned.zip' \"+URL)\n",
|
||||
"elif Mode == \"upload merged\":\n",
|
||||
" %cd \"/content/workspace/data_dst\"\n",
|
||||
" run_cmd(\"merged.zip merged/\",\"'data=@/content/workspace/data_dst/merged.zip' \"+URL )\n",
|
||||
"elif Mode == \"upload model\":\n",
|
||||
" %cd \"/content/workspace\"\n",
|
||||
" run_cmd(\"model.zip model/\", \"'data=@/content/workspace/model.zip' \"+URL)\n",
|
||||
" \n",
|
||||
" \n",
|
||||
"!rm *.zip\n",
|
||||
"\n",
|
||||
"%cd \"/content\"\n",
|
||||
"print(\"Done!\")"
|
||||
],
|
||||
"execution_count": 0,
|
||||
"outputs": []
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"metadata": {
|
||||
"id": "Ta6ue_UGMkki",
|
||||
"colab_type": "code",
|
||||
"cellView": "form",
|
||||
"colab": {}
|
||||
},
|
||||
"source": [
|
||||
"#@title Delete and recreate\n",
|
||||
"Mode = \"Delete and recreate workspace\" #@param [\"Delete and recreate workspace\", \"Delete models\", \"Delete data_src\", \"Delete data_src aligned\", \"Delete data_src video\", \"Delete data_dst\", \"Delete data_dst aligned\", \"Delete merged frames\"]\n",
|
||||
"\n",
|
||||
"%cd \"/content\" \n",
|
||||
"\n",
|
||||
"if Mode == \"Delete and recreate workspace\":\n",
|
||||
" cmd = \"rm -r /content/workspace ; mkdir /content/workspace; mkdir /content/workspace/data_src; mkdir /content/workspace/data_src/aligned; mkdir /content/workspace/data_dst; mkdir /content/workspace/data_dst/aligned; mkdir /content/workspace/model\" \n",
|
||||
"elif Mode == \"Delete models\":\n",
|
||||
" cmd = \"rm -r /content/workspace/model/*\"\n",
|
||||
"elif Mode == \"Delete data_src\":\n",
|
||||
" cmd = \"rm /content/workspace/data_src/*.png || rm -r /content/workspace/data_src/*.jpg\"\n",
|
||||
"elif Mode == \"Delete data_src aligned\":\n",
|
||||
" cmd = \"rm -r /content/workspace/data_src/aligned/*\"\n",
|
||||
"elif Mode == \"Delete data_src video\":\n",
|
||||
" cmd = \"rm -r /content/workspace/data_src.*\"\n",
|
||||
"elif Mode == \"Delete data_dst\":\n",
|
||||
" cmd = \"rm /content/workspace/data_dst/*.png || rm /content/workspace/data_dst/*.jpg\"\n",
|
||||
"elif Mode == \"Delete data_dst aligned\":\n",
|
||||
" cmd = \"rm -r /content/workspace/data_dst/aligned/*\"\n",
|
||||
"elif Mode == \"Delete merged frames\":\n",
|
||||
" cmd = \"rm -r /content/workspace/data_dst/merged\"\n",
|
||||
" \n",
|
||||
"!$cmd\n",
|
||||
"print(\"Done!\")"
|
||||
],
|
||||
"execution_count": 0,
|
||||
"outputs": []
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "tUNVcbujhm00",
|
||||
"colab_type": "text"
|
||||
},
|
||||
"source": [
|
||||
"# Extract and sorting\n",
|
||||
"* Extract frames for SRC or DST video.\n",
|
||||
"* Denoise SRC or DST video. \"Factor\" param set intesity of denoising\n",
|
||||
"* Detect and align faces with one of detectors. (S3FD - recommended). If you need, you can get frames with debug landmarks.\n",
|
||||
"* Export workspace to Google Drive after extract and sort it manually (Last block of Notebook)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"metadata": {
|
||||
"id": "qwJEbz5Nhot0",
|
||||
"colab_type": "code",
|
||||
"cellView": "form",
|
||||
"colab": {}
|
||||
},
|
||||
"source": [
|
||||
"#@title Extract frames\n",
|
||||
"Video = \"data_src\" #@param [\"data_src\", \"data_dst\"]\n",
|
||||
"\n",
|
||||
"%cd \"/content\"\n",
|
||||
"\n",
|
||||
"cmd = \"DeepFaceLab/main.py videoed extract-video\"\n",
|
||||
"\n",
|
||||
"if Video == \"data_dst\":\n",
|
||||
" cmd+= \" --input-file workspace/data_dst.* --output-dir workspace/data_dst/\"\n",
|
||||
"else:\n",
|
||||
" cmd+= \" --input-file workspace/data_src.* --output-dir workspace/data_src/\"\n",
|
||||
" \n",
|
||||
"!python $cmd"
|
||||
],
|
||||
"execution_count": 0,
|
||||
"outputs": []
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"metadata": {
|
||||
"id": "bFmPo0s2lTil",
|
||||
"colab_type": "code",
|
||||
"cellView": "form",
|
||||
"colab": {}
|
||||
},
|
||||
"source": [
|
||||
"#@title Denoise frames\n",
|
||||
"Data = \"data_src\" #@param [\"data_src\", \"data_dst\"]\n",
|
||||
"Factor = 1 #@param {type:\"slider\", min:1, max:20, step:1}\n",
|
||||
"\n",
|
||||
"cmd = \"DeepFaceLab/main.py videoed denoise-image-sequence --input-dir workspace/\"+Data+\" --factor \"+str(Factor)\n",
|
||||
"\n",
|
||||
"%cd \"/content\"\n",
|
||||
"!python $cmd"
|
||||
],
|
||||
"execution_count": 0,
|
||||
"outputs": []
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"metadata": {
|
||||
"id": "nmq0Sj2bmq7d",
|
||||
"colab_type": "code",
|
||||
"cellView": "form",
|
||||
"colab": {}
|
||||
},
|
||||
"source": [
|
||||
"#@title Detect faces\n",
|
||||
"Data = \"data_src\" #@param [\"data_src\", \"data_dst\"]\n",
|
||||
"Detector = \"S3FD\" #@param [\"S3FD\", \"MT\"]\n",
|
||||
"Debug = False #@param {type:\"boolean\"}\n",
|
||||
"\n",
|
||||
"detect_type = \"s3fd\"\n",
|
||||
"if Detector == \"S3FD\":\n",
|
||||
" detect_type = \"s3fd\"\n",
|
||||
"elif Detector == \"MT\":\n",
|
||||
" detect_type = \"mt\"\n",
|
||||
"\n",
|
||||
"folder = \"workspace/\"+Data\n",
|
||||
"folder_align = folder+\"/aligned\"\n",
|
||||
"debug_folder = folder_align+\"/debug\"\n",
|
||||
"\n",
|
||||
"cmd = \"DeepFaceLab/main.py extract --input-dir \"+folder+\" --output-dir \"+folder_align\n",
|
||||
"\n",
|
||||
"if Debug:\n",
|
||||
" cmd+= \" --debug-dir \"+debug_folder\n",
|
||||
"\n",
|
||||
"cmd+=\" --detector \"+detect_type\n",
|
||||
" \n",
|
||||
"%cd \"/content\"\n",
|
||||
"!python $cmd"
|
||||
],
|
||||
"execution_count": 0,
|
||||
"outputs": []
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"metadata": {
|
||||
"id": "TRNxUFE6p6Eu",
|
||||
"colab_type": "code",
|
||||
"cellView": "form",
|
||||
"colab": {}
|
||||
},
|
||||
"source": [
|
||||
"#@title Sort aligned\n",
|
||||
"Data = \"data_src\" #@param [\"data_src\", \"data_dst\"]\n",
|
||||
"sort_type = \"hist\" #@param [\"hist\", \"hist-dissim\", \"face-yaw\", \"face-pitch\", \"blur\", \"final\"]\n",
|
||||
"\n",
|
||||
"cmd = \"DeepFaceLab/main.py sort --input-dir workspace/\"+Data+\"/aligned --by \"+sort_type\n",
|
||||
"\n",
|
||||
"%cd \"/content\"\n",
|
||||
"!python $cmd"
|
||||
],
|
||||
"execution_count": 0,
|
||||
"outputs": []
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "WTuyUxgdLA13",
|
||||
"colab_type": "text"
|
||||
},
|
||||
"source": [
|
||||
"# Train model\n",
|
||||
"\n",
|
||||
"* Choose your model type, but SAE is recommend for everyone\n",
|
||||
"* Set model options on output field\n",
|
||||
"* You can see preview manually, if go to model folder in filemanager and double click on preview.jpg file\n",
|
||||
"* Your workspace will be archived and upload to mounted Drive after 11 hours from start session\n",
|
||||
"* If you select \"Backup_every_hour\" option, your workspace will be backed up every hour.\n",
|
||||
"* Also, you can export your workspace manually in \"Manage workspace\" block"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"metadata": {
|
||||
"id": "Z0Kya-PJLDhv",
|
||||
"colab_type": "code",
|
||||
"cellView": "both",
|
||||
"outputId": "db06ff5b-4aae-4d4b-bad0-9c980782ba3b",
|
||||
"colab": {
|
||||
"base_uri": "https://localhost:8080/"
|
||||
}
|
||||
},
|
||||
"source": [
|
||||
"#@title Training\n",
|
||||
"Model = \"SAE\" #@param [\"SAE\", \"H128\", \"LIAEF128\", \"DF\", \"DEV_FANSEG\", \"RecycleGAN\"]\n",
|
||||
"Backup_every_hour = True #@param {type:\"boolean\"}\n",
|
||||
"\n",
|
||||
"%cd \"/content\"\n",
|
||||
"\n",
|
||||
"#Mount Google Drive as folder\n",
|
||||
"from google.colab import drive\n",
|
||||
"drive.mount('/content/drive')\n",
|
||||
"\n",
|
||||
"import psutil, os, time\n",
|
||||
"\n",
|
||||
"p = psutil.Process(os.getpid())\n",
|
||||
"uptime = time.time() - p.create_time()\n",
|
||||
"\n",
|
||||
"if (Backup_every_hour):\n",
|
||||
" if not os.path.exists('workspace.zip'):\n",
|
||||
" print(\"Creating workspace archive ...\")\n",
|
||||
" !zip -r -q workspace.zip workspace\n",
|
||||
" print(\"Archive created!\")\n",
|
||||
" else:\n",
|
||||
" print(\"Archive exist!\")\n",
|
||||
"\n",
|
||||
"if (Backup_every_hour):\n",
|
||||
" print(\"Time to end session: \"+str(round((43200-uptime)/3600))+\" hours\")\n",
|
||||
" backup_time = str(3600)\n",
|
||||
" backup_cmd = \" --execute-program -\"+backup_time+\" \\\"import os; os.system('zip -r -q workspace.zip workspace/model'); os.system('cp /content/workspace.zip /content/drive/My\\ Drive/'); print(' Backuped!') \\\"\" \n",
|
||||
"elif (round(39600-uptime) > 0):\n",
|
||||
" print(\"Time to backup: \"+str(round((39600-uptime)/3600))+\" hours\")\n",
|
||||
" backup_time = str(round(39600-uptime))\n",
|
||||
" backup_cmd = \" --execute-program \"+backup_time+\" \\\"import os; os.system('zip -r -q workspace.zip workspace'); os.system('cp /content/workspace.zip /content/drive/My\\ Drive/'); print(' Backuped!') \\\"\" \n",
|
||||
"else:\n",
|
||||
" print(\"Session expires in less than an hour.\")\n",
|
||||
" backup_cmd = \"\"\n",
|
||||
" \n",
|
||||
"cmd = \"DeepFaceLab/main.py train --training-data-src-dir workspace/data_src/aligned --training-data-dst-dir workspace/data_dst/aligned --pretraining-data-dir pretrain/aligned --model-dir workspace/model --model \"+Model\n",
|
||||
" \n",
|
||||
"if (backup_cmd != \"\"):\n",
|
||||
" train_cmd = (cmd+backup_cmd)\n",
|
||||
"else:\n",
|
||||
" train_cmd = (cmd)\n",
|
||||
"\n",
|
||||
"!python $train_cmd"
|
||||
],
|
||||
"execution_count": 0,
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"/content\n",
|
||||
"Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n",
|
||||
"Creating workspace archive ...\n",
|
||||
"Archive created!\n",
|
||||
"Time to end session: 12 hours\n",
|
||||
"Running trainer.\n",
|
||||
"\n",
|
||||
"Loading model...\n",
|
||||
"Press enter in 2 seconds to override model settings.\n",
|
||||
"Enable autobackup? (y/n ?:help skip:n) : /usr/lib/python3.6/multiprocessing/semaphore_tracker.py:143: UserWarning: semaphore_tracker: There appear to be 1 leaked semaphores to clean up at shutdown\n",
|
||||
" len(cache))\n",
|
||||
"\n",
|
||||
"n\n",
|
||||
"Write preview history? (y/n ?:help skip:n) : \n",
|
||||
"n\n",
|
||||
"Target iteration (skip:unlimited/default) : \n",
|
||||
"0\n",
|
||||
"Batch_size (?:help skip:16) : 10\n",
|
||||
"Enable ping-pong? (y/n ?:help skip:False) : ?\n",
|
||||
"Cycles batch size between 1 and chosen batch size, simulating super convergence\n",
|
||||
"Enable ping-pong? (y/n ?:help skip:False) : y\n",
|
||||
"Ping-pong iteration (skip:1000/default) : \n",
|
||||
"1000\n",
|
||||
"Feed faces to network sorted by yaw? (y/n ?:help skip:y): \n",
|
||||
"y\n",
|
||||
"Flip faces randomly? (y/n ?:help skip:y) : ?\n",
|
||||
"Predicted face will look more naturally without this option, but src faceset should cover all face directions as dst faceset.\n",
|
||||
"Flip faces randomly? (y/n ?:help skip:y) : n\n",
|
||||
"Optimizer mode? ( 1,2,3 ?:help skip:1) : \n",
|
||||
"1\n",
|
||||
"Use pixel loss? (y/n, ?:help skip: n ) : \n",
|
||||
"n\n",
|
||||
"Face style power ( 0.0 .. 100.0 ?:help skip:0.00) : \n",
|
||||
"0.0\n",
|
||||
"Background style power ( 0.0 .. 100.0 ?:help skip:0.00) : \n",
|
||||
"0.0\n",
|
||||
"Apply random color transfer to src faceset? (0) None, (1) LCT, (2) RCT, (3) RCT-c, (4) RCT-p, (5) RCT-pc, (6) mRTC, (7) mRTC-c, (8) mRTC-p, (9) mRTC-pc ?:help skip:False) : 0\n",
|
||||
"Enable gradient clipping? (y/n, ?:help skip:y) : \n",
|
||||
"y\n",
|
||||
"Using TensorFlow backend.\n",
|
||||
"WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.\n",
|
||||
"Instructions for updating:\n",
|
||||
"Colocations handled automatically by placer.\n",
|
||||
"WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/math_ops.py:3066: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
|
||||
"Instructions for updating:\n",
|
||||
"Use tf.cast instead.\n",
|
||||
"Loading: 100% 4895/4895 [00:08<00:00, 562.57it/s]\n",
|
||||
"Sorting: 100% 64/64 [00:00<00:00, 624.66it/s]\n",
|
||||
"Loading: 0it [00:00, ?it/s]\n",
|
||||
"Sorting: 100% 64/64 [00:00<00:00, 586103.62it/s]\n",
|
||||
"========= Model Summary ==========\n",
|
||||
"== ==\n",
|
||||
"== Model name: SAE ==\n",
|
||||
"== ==\n",
|
||||
"== Current iteration: 202787 ==\n",
|
||||
"== ==\n",
|
||||
"==------- Model Options --------==\n",
|
||||
"== ==\n",
|
||||
"== batch_size: 10 ==\n",
|
||||
"== sort_by_yaw: True ==\n",
|
||||
"== random_flip: False ==\n",
|
||||
"== resolution: 192 ==\n",
|
||||
"== face_type: f ==\n",
|
||||
"== learn_mask: True ==\n",
|
||||
"== optimizer_mode: 1 ==\n",
|
||||
"== archi: df ==\n",
|
||||
"== ae_dims: 512 ==\n",
|
||||
"== e_ch_dims: 42 ==\n",
|
||||
"== d_ch_dims: 21 ==\n",
|
||||
"== multiscale_decoder: True ==\n",
|
||||
"== ca_weights: True ==\n",
|
||||
"== pixel_loss: False ==\n",
|
||||
"== face_style_power: 0.0 ==\n",
|
||||
"== bg_style_power: 0.0 ==\n",
|
||||
"== apply_random_ct: 0 ==\n",
|
||||
"== clipgrad: True ==\n",
|
||||
"== batch_cap: 10 ==\n",
|
||||
"== ping_pong: True ==\n",
|
||||
"== paddle: ping ==\n",
|
||||
"== ping_pong_iter: 1000 ==\n",
|
||||
"== ==\n",
|
||||
"==--------- Running On ---------==\n",
|
||||
"== ==\n",
|
||||
"== Device index: 0 ==\n",
|
||||
"== Name: Tesla T4 ==\n",
|
||||
"== VRAM: 15.00GB ==\n",
|
||||
"== ==\n",
|
||||
"==================================\n",
|
||||
"Starting. Press \"Enter\" to stop training and save model.\n",
|
||||
"Process Process-2:\n",
|
||||
"Traceback (most recent call last):\n",
|
||||
" File \"/usr/lib/python3.6/multiprocessing/process.py\", line 258, in _bootstrap\n",
|
||||
" self.run()\n",
|
||||
" File \"/usr/lib/python3.6/multiprocessing/process.py\", line 93, in run\n",
|
||||
" self._target(*self._args, **self._kwargs)\n",
|
||||
" File \"/content/DeepFaceLab/utils/iter_utils.py\", line 39, in process_func\n",
|
||||
" gen_data = next (self.generator_func)\n",
|
||||
" File \"/content/DeepFaceLab/samplelib/SampleGeneratorFace.py\", line 85, in batch_func\n",
|
||||
" raise ValueError('Not enough training data. Gather more faces!')\n",
|
||||
"ValueError: Not enough training data. Gather more faces!\n",
|
||||
"/usr/lib/python3.6/multiprocessing/semaphore_tracker.py:143: UserWarning: semaphore_tracker: There appear to be 1 leaked semaphores to clean up at shutdown\n",
|
||||
" len(cache))\n"
|
||||
],
|
||||
"name": "stdout"
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "avAcSL_uvtq_",
|
||||
"colab_type": "text"
|
||||
},
|
||||
"source": [
|
||||
"# Convert frames"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"metadata": {
|
||||
"id": "A3Y8K22Sv9Gn",
|
||||
"colab_type": "code",
|
||||
"cellView": "form",
|
||||
"colab": {}
|
||||
},
|
||||
"source": [
|
||||
"#@title Convert\n",
|
||||
"Model = \"SAE\" #@param [\"SAE\", \"H128\", \"LIAEF128\", \"DF\", \"RecycleGAN\"]\n",
|
||||
"\n",
|
||||
"cmd = \"DeepFaceLab/main.py convert --input-dir workspace/data_dst --output-dir workspace/data_dst/merged --aligned-dir workspace/data_dst/aligned --model-dir workspace/model --model \"+Model\n",
|
||||
"\n",
|
||||
"%cd \"/content\"\n",
|
||||
"!python $cmd"
|
||||
],
|
||||
"execution_count": 0,
|
||||
"outputs": []
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"metadata": {
|
||||
"id": "JNeGfiZpxlnz",
|
||||
"colab_type": "code",
|
||||
"cellView": "form",
|
||||
"colab": {}
|
||||
},
|
||||
"source": [
|
||||
"#@title Get result video and copy to Drive \n",
|
||||
"\n",
|
||||
"!python DeepFaceLab/main.py videoed video-from-sequence --input-dir workspace/data_dst/merged --output-file workspace/result.mp4 --reference-file workspace/data_dst.mp4\n",
|
||||
"!cp /content/workspace/result.mp4 /content/drive/My\\ Drive/"
|
||||
],
|
||||
"execution_count": 0,
|
||||
"outputs": []
|
||||
}
|
||||
]
|
||||
}
|
||||
Loading…
Add table
Add a link
Reference in a new issue