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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "M74Gs_TjYl_B"
},
"source": [
"[](https://colab.research.google.com/github/Winfredy/SadTalker/blob/main/quick_demo.ipynb)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github"
},
"source": [
"### SadTalker：Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation \n",
"\n",
"[arxiv](https://arxiv.org/abs/2211.12194) | [project](https://sadtalker.github.io) | [Github](https://github.com/Winfredy/SadTalker)\n",
"\n",
"Wenxuan Zhang, Xiaodong Cun, Xuan Wang, Yong Zhang, Xi Shen, Yu Guo, Ying Shan, Fei Wang.\n",
"\n",
"Xi'an Jiaotong University, Tencent AI Lab, Ant Group\n",
"\n",
"CVPR 2023\n",
"\n",
"TL;DR: A realistic and stylized talking head video generation method from a single image and audio\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "kA89DV-sKS4i"
},
"source": [
"Installation (around 5 mins)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "qJ4CplXsYl_E"
},
"outputs": [],
"source": [
"### make sure that CUDA is available in Edit -> Nootbook settings -> GPU\n",
"!nvidia-smi --query-gpu=name,memory.total,memory.free --format=csv,noheader"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "Mdq6j4E5KQAR"
},
"outputs": [],
"source": [
"!update-alternatives --install /usr/local/bin/python3 python3 /usr/bin/python3.8 2 \n",
"!update-alternatives --install /usr/local/bin/python3 python3 /usr/bin/python3.9 1 \n",
"!python --version \n",
"!apt-get update\n",
"!apt install software-properties-common\n",
"!sudo dpkg --remove --force-remove-reinstreq python3-pip python3-setuptools python3-wheel\n",
"!apt-get install python3-pip\n",
"\n",
"print('Git clone project and install requirements...')\n",
"!git clone https://github.com/Winfredy/SadTalker &> /dev/null\n",
"%cd SadTalker \n",
"!export PYTHONPATH=/content/SadTalker:$PYTHONPATH \n",
"!python3.8 -m pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu113\n",
"!apt update\n",
"!apt install ffmpeg &> /dev/null \n",
"!python3.8 -m pip install -r requirements.txt"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "DddcKB_nKsnk"
},
"source": [
"Download models (1 mins)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "eDw3_UN8K2xa"
},
"outputs": [],
"source": [
"print('Download pre-trained models...')\n",
"!rm -rf checkpoints\n",
"!bash scripts/download_models.sh"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "kK7DYeo7Yl_H"
},
"outputs": [],
"source": [
"# borrow from makeittalk\n",
"import ipywidgets as widgets\n",
"import glob\n",
"import matplotlib.pyplot as plt\n",
"print(\"Choose the image name to animate: (saved in folder 'examples/')\")\n",
"img_list = glob.glob1('examples/source_image', '*.png')\n",
"img_list.sort()\n",
"img_list = [item.split('.')[0] for item in img_list]\n",
"default_head_name = widgets.Dropdown(options=img_list, value='full3')\n",
"def on_change(change):\n",
" if change['type'] == 'change' and change['name'] == 'value':\n",
" plt.imshow(plt.imread('examples/source_image/{}.png'.format(default_head_name.value)))\n",
" plt.axis('off')\n",
" plt.show()\n",
"default_head_name.observe(on_change)\n",
"display(default_head_name)\n",
"plt.imshow(plt.imread('examples/source_image/{}.png'.format(default_head_name.value)))\n",
"plt.axis('off')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "-khNZcnGK4UK"
},
"source": [
"Animation"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "ToBlDusjK5sS"
},
"outputs": [],
"source": [
"# selected audio from exmaple/driven_audio\n",
"img = 'examples/source_image/{}.png'.format(default_head_name.value)\n",
"print(img)\n",
"!python3.8 inference.py --driven_audio ./examples/driven_audio/RD_Radio31_000.wav \\\n",
" --source_image {img} \\\n",
" --result_dir ./results --still --preprocess full --enhancer gfpgan"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "fAjwGmKKYl_I"
},
"outputs": [],
"source": [
"# visualize code from makeittalk\n",
"from IPython.display import HTML\n",
"from base64 import b64encode\n",
"import os, sys\n",
"\n",
"# get the last from results\n",
"\n",
"results = sorted(os.listdir('./results/'))\n",
"\n",
"mp4_name = glob.glob('./results/'+results[-1]+'/*.mp4')[0]\n",
"\n",
"mp4 = open('{}'.format(mp4_name),'rb').read()\n",
"data_url = \"data:video/mp4;base64,\" + b64encode(mp4).decode()\n",
"\n",
"print('Display animation: {}'.format(mp4_name), file=sys.stderr)\n",
"display(HTML(\"\"\"\n",
" <video width=256 controls>\n",
" <source src=\"%s\" type=\"video/mp4\">\n",
" </video>\n",
" \"\"\" % data_url))\n"
]
}
],
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"display_name": "base",
"language": "python",
"name": "python3"
},
"language_info": {
"name": "python",
"version": "3.9.7"
},
"vscode": {
"interpreter": {
"hash": "db5031b3636a3f037ea48eb287fd3d023feb9033aefc2a9652a92e470fb0851b"
}
},
"accelerator": "GPU",
"gpuClass": "standard"
},
"nbformat": 4,
"nbformat_minor": 0
} |