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## Frequency Asked Question
**Q: `ffmpeg` is not recognized as an internal or external command**
In Linux, you can install the ffmpeg via `conda install ffmpeg`. Or on Mac OS X, try to install ffmpeg via `brew install ffmpeg`. On windows, make sure you have `ffmpeg` in the `%PATH%` as suggested in [#54](https://github.com/Winfredy/SadTalker/issues/54), then, following [this](https://www.geeksforgeeks.org/how-to-install-ffmpeg-on-windows/) installation to install `ffmpeg`.
**Q: Running Requirments.**
Please refer to the discussion here: https://github.com/Winfredy/SadTalker/issues/124#issuecomment-1508113989
**Q: ModuleNotFoundError: No module named 'ai'**
please check the checkpoint's size of the `epoch_20.pth`. (https://github.com/Winfredy/SadTalker/issues/167, https://github.com/Winfredy/SadTalker/issues/113)
**Q: Illegal Hardware Error: Mac M1**
please reinstall the `dlib` by `pip install dlib` individually. (https://github.com/Winfredy/SadTalker/issues/129, https://github.com/Winfredy/SadTalker/issues/109)
**Q: FileNotFoundError: [Errno 2] No such file or directory: checkpoints\BFM_Fitting\similarity_Lm3D_all.mat**
Make sure you have downloaded the checkpoints and gfpgan as [here](https://github.com/Winfredy/SadTalker#-2-download-trained-models) and placed them in the right place.
**Q: RuntimeError: unexpected EOF, expected 237192 more bytes. The file might be corrupted.**
The files are not automatically downloaded. Please update the code and download the gfpgan folders as [here](https://github.com/Winfredy/SadTalker#-2-download-trained-models).
**Q: CUDA out of memory error**
please refer to https://stackoverflow.com/questions/73747731/runtimeerror-cuda-out-of-memory-how-setting-max-split-size-mb
```
# windows
set PYTORCH_CUDA_ALLOC_CONF=max_split_size_mb:128
python inference.py ...
# linux
export PYTORCH_CUDA_ALLOC_CONF=max_split_size_mb:128
python inference.py ...
```
**Q: Error while decoding stream #0:0: Invalid data found when processing input [mp3float @ 0000015037628c00] Header missing**
Our method only support wav or mp3 files as input, please make sure the feeded audios are in these formats.
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# Best Practices and Tips for configuration
> Our model only works on REAL people or the portrait image similar to REAL person. The anime talking head genreation method will be released in future.
Advanced confiuration options for `inference.py`:
| Name | Configuration | default | Explaination |
|:------------- |:------------- |:----- | :------------- |
| Enhance Mode | `--enhancer` | None | Using `gfpgan` or `RestoreFormer` to enhance the generated face via face restoration network
| Background Enhancer | `--background_enhancer` | None | Using `realesrgan` to enhance the full video.
| Still Mode | ` --still` | False | Using the same pose parameters as the original image, fewer head motion.
| Expressive Mode | `--expression_scale` | 1.0 | a larger value will make the expression motion stronger.
| save path | `--result_dir` |`./results` | The file will be save in the newer location.
| preprocess | `--preprocess` | `crop` | Run and produce the results in the croped input image. Other choices: `resize`, where the images will be resized to the specific resolution. `full` Run the full image animation, use with `--still` to get better results.
| ref Mode (eye) | `--ref_eyeblink` | None | A video path, where we borrow the eyeblink from this reference video to provide more natural eyebrow movement.
| ref Mode (pose) | `--ref_pose` | None | A video path, where we borrow the pose from the head reference video.
| 3D Mode | `--face3dvis` | False | Need additional installation. More details to generate the 3d face can be founded [here](docs/face3d.md).
| free-view Mode | `--input_yaw`,<br> `--input_pitch`,<br> `--input_roll` | None | Genearting novel view or free-view 4D talking head from a single image. More details can be founded [here](https://github.com/Winfredy/SadTalker#generating-4d-free-view-talking-examples-from-audio-and-a-single-image).
### About `--preprocess`
Our system automatically handles the input images via `crop`, `resize` and `full`.
In `crop` mode, we only generate the croped image via the facial keypoints and generated the facial anime avator. The animation of both expression and head pose are realistic.
> Still mode will stop the eyeblink and head pose movement.
| [input image @bagbag1815](https://twitter.com/bagbag1815/status/1642754319094108161) | crop | crop w/still |
|:--------------------: |:--------------------: | :----: |
| <img src='../examples/source_image/full_body_2.png' width='380'> | ![full_body_2](example_crop.gif) | ![full_body_2](example_crop_still.gif) |
In `resize` mode, we resize the whole images to generate the fully talking head video. Thus, an image similar to the ID photo can be produced. ⚠️ It will produce bad results for full person images.
| <img src='../examples/source_image/full_body_2.png' width='380'> | <img src='../examples/source_image/full4.jpeg' width='380'> |
|:--------------------: |:--------------------: |
| ❌ not suitable for resize mode | ✅ good for resize mode |
| <img src='resize_no.gif'> | <img src='resize_good.gif' width='380'> |
In `full` mode, our model will automatically process the croped region and paste back to the original image. Remember to use `--still` to keep the original head pose.
| input | `--still` | `--still` & `enhancer` |
|:--------------------: |:--------------------: | :--:|
| <img src='../examples/source_image/full_body_2.png' width='380'> | <img src='./example_full.gif' width='380'> | <img src='./example_full_enhanced.gif' width='380'>
### About `--enhancer`
For higher resolution, we intergate [gfpgan](https://github.com/TencentARC/GFPGAN) and [real-esrgan](https://github.com/xinntao/Real-ESRGAN) for different purpose. Just adding `--enhancer <gfpgan or RestoreFormer>` or `--background_enhancer <realesrgan>` for the enhancement of the face and the full image.
```bash
# make sure above packages are available:
pip install gfpgan
pip install realesrgan
```
### About `--face3dvis`
This flag indicate that we can generated the 3d-rendered face and it's 3d facial landmarks. More details can be founded [here](face3d.md).
| Input | Animated 3d face |
|:-------------: | :-------------: |
| <img src='../examples/source_image/art_0.png' width='200px'> | <video src="https://user-images.githubusercontent.com/4397546/226856847-5a6a0a4d-a5ec-49e2-9b05-3206db65e8e3.mp4"></video> |
> Kindly ensure to activate the audio as the default audio playing is incompatible with GitHub.
#### Reference eye-link mode.
| Input, w/ reference video , reference video |
|:-------------: |
| ![free_view](using_ref_video.gif)|
| If the reference video is shorter than the input audio, we will loop the reference video .
#### Generating 4D free-view talking examples from audio and a single image
We use `input_yaw`, `input_pitch`, `input_roll` to control head pose. For example, `--input_yaw -20 30 10` means the input head yaw degree changes from -20 to 30 and then changes from 30 to 10.
```bash
python inference.py --driven_audio <audio.wav> \
--source_image <video.mp4 or picture.png> \
--result_dir <a file to store results> \
--input_yaw -20 30 10
```
| Results, Free-view results, Novel view results |
|:-------------: |
| ![free_view](free_view_result.gif)|
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## changelogs
- __[2023.04.06]__: stable-diffiusion webui extension is release.
- __[2023.04.03]__: Enable TTS in huggingface and gradio local demo.
- __[2023.03.30]__: Launch beta version of the full body mode.
- __[2023.03.30]__: Launch new feature: through using reference videos, our algorithm can generate videos with more natural eye blinking and some eyebrow movement.
- __[2023.03.29]__: `resize mode` is online by `python infererence.py --preprocess resize`! Where we can produce a larger crop of the image as discussed in https://github.com/Winfredy/SadTalker/issues/35.
- __[2023.03.29]__: local gradio demo is online! `python app.py` to start the demo. New `requirments.txt` is used to avoid the bugs in `librosa`.
- __[2023.03.28]__: Online demo is launched in [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/vinthony/SadTalker), thanks AK!
- __[2023.03.22]__: Launch new feature: generating the 3d face animation from a single image. New applications about it will be updated.
- __[2023.03.22]__: Launch new feature: `still mode`, where only a small head pose will be produced via `python inference.py --still`.
- __[2023.03.18]__: Support `expression intensity`, now you can change the intensity of the generated motion: `python inference.py --expression_scale 1.3 (some value > 1)`.
- __[2023.03.18]__: Reconfig the data folders, now you can download the checkpoint automatically using `bash scripts/download_models.sh`.
- __[2023.03.18]__: We have offically integrate the [GFPGAN](https://github.com/TencentARC/GFPGAN) for face enhancement, using `python inference.py --enhancer gfpgan` for better visualization performance.
- __[2023.03.14]__: Specify the version of package `joblib` to remove the errors in using `librosa`, [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Winfredy/SadTalker/blob/main/quick_demo.ipynb) is online!
- __[2023.03.06]__: Solve some bugs in code and errors in installation
- __[2023.03.03]__: Release the test code for audio-driven single image animation!
- __[2023.02.28]__: SadTalker has been accepted by CVPR 2023!
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## 3D Face Visualization
We use `pytorch3d` to visualize the 3D faces from a single image.
The requirements for 3D visualization are difficult to install, so here's a tutorial:
```bash
git clone https://github.com/OpenTalker/SadTalker.git
cd SadTalker
conda create -n sadtalker3d python=3.8
source activate sadtalker3d
conda install ffmpeg
conda install -c fvcore -c iopath -c conda-forge fvcore iopath
conda install libgcc gmp
pip install torch==1.11.0+cu113 torchvision==0.12.0+cu113 torchaudio==0.11.0 --extra-index-url https://download.pytorch.org/whl/cu113
# insintall pytorch3d
pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/py38_cu113_pyt1110/download.html
pip install -r requirements3d.txt
### install gpfgan for enhancer
pip install git+https://github.com/TencentARC/GFPGAN
### when occurs gcc version problem `from pytorch import _C` from pytorch3d, add the anaconda path to LD_LIBRARY_PATH
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/$YOUR_ANACONDA_PATH/lib/
```
Then, generate the result via:
```bash
python inference.py --driven_audio <audio.wav> \
--source_image <video.mp4 or picture.png> \
--result_dir <a file to store results> \
--face3dvis
```
The results will appear, named `face3d.mp4`.
More applications about 3D face rendering will be released soon.
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### macOS
This method has been tested on a M1 Mac (13.3)
```bash
git clone https://github.com/OpenTalker/SadTalker.git
cd SadTalker
conda create -n sadtalker python=3.8
conda activate sadtalker
# install pytorch 2.0
pip install torch torchvision torchaudio
conda install ffmpeg
pip install -r requirements.txt
pip install dlib # macOS needs to install the original dlib.
```
### Windows Native
- Make sure you have `ffmpeg` in the `%PATH%` as suggested in [#54](https://github.com/Winfredy/SadTalker/issues/54), following [this](https://www.geeksforgeeks.org/how-to-install-ffmpeg-on-windows/) tutorial to install `ffmpeg` or using scoop.
### Windows WSL
- Make sure the environment: `export LD_LIBRARY_PATH=/usr/lib/wsl/lib:$LD_LIBRARY_PATH`
### Docker Installation
A community Docker image by [@thegenerativegeneration](https://github.com/thegenerativegeneration) is available on the [Docker hub](https://hub.docker.com/repository/docker/wawa9000/sadtalker), which can be used directly:
```bash
docker run --gpus "all" --rm -v $(pwd):/host_dir wawa9000/sadtalker \
--driven_audio /host_dir/deyu.wav \
--source_image /host_dir/image.jpg \
--expression_scale 1.0 \
--still \
--result_dir /host_dir
```
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## Run SadTalker as a Stable Diffusion WebUI Extension.
1. Install the lastest version of [stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui) and install SadTalker via `extension`.
<img width="726" alt="image" src="https://user-images.githubusercontent.com/4397546/230698519-267d1d1f-6e99-4dd4-81e1-7b889259efbd.png">
2. Download the checkpoints manually, for Linux and Mac:
```bash
cd SOMEWHERE_YOU_LIKE
bash <(wget -qO- https://raw.githubusercontent.com/Winfredy/OpenTalker/main/scripts/download_models.sh)
```
For Windows, you can download all the checkpoints [here](https://github.com/OpenTalker/SadTalker/tree/main#2-download-models).
3.1. Option 1: put the checkpoint in `stable-diffusion-webui/models/SadTalker` or `stable-diffusion-webui/extensions/SadTalker/checkpoints/`, the checkpoints will be detected automatically.
3.2. Option 2: Set the path of `SADTALKTER_CHECKPOINTS` in `webui_user.sh`(linux) or `webui_user.bat`(windows) by:
> only works if you are directly starting webui from `webui_user.sh` or `webui_user.bat`.
```bash
# Windows (webui_user.bat)
set SADTALKER_CHECKPOINTS=D:\SadTalker\checkpoints
# Linux/macOS (webui_user.sh)
export SADTALKER_CHECKPOINTS=/path/to/SadTalker/checkpoints
```
4. Start the WebUI via `webui.sh or webui_user.sh(linux)` or `webui_user.bat(windows)` or any other method. SadTalker can also be used in stable-diffusion-webui directly.
<img width="726" alt="image" src="https://user-images.githubusercontent.com/4397546/230698614-58015182-2916-4240-b324-e69022ef75b3.png">
## Questions
1. if you are running on CPU, you need to specific `--disable-safe-unpickle` in `webui_user.sh` or `webui_user.bat`.
```bash
# windows (webui_user.bat)
set COMMANDLINE_ARGS="--disable-safe-unpickle"
# linux (webui_user.sh)
export COMMANDLINE_ARGS="--disable-safe-unpickle"
```
(If you're unable to use the `full` mode, please read this [discussion](https://github.com/Winfredy/SadTalker/issues/78).)
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mkdir ./checkpoints
# lagency download link
# wget -nc https://github.com/Winfredy/SadTalker/releases/download/v0.0.2/auido2exp_00300-model.pth -O ./checkpoints/auido2exp_00300-model.pth
# wget -nc https://github.com/Winfredy/SadTalker/releases/download/v0.0.2/auido2pose_00140-model.pth -O ./checkpoints/auido2pose_00140-model.pth
# wget -nc https://github.com/Winfredy/SadTalker/releases/download/v0.0.2/epoch_20.pth -O ./checkpoints/epoch_20.pth
# wget -nc https://github.com/Winfredy/SadTalker/releases/download/v0.0.2/facevid2vid_00189-model.pth.tar -O ./checkpoints/facevid2vid_00189-model.pth.tar
# wget -nc https://github.com/Winfredy/SadTalker/releases/download/v0.0.2/shape_predictor_68_face_landmarks.dat -O ./checkpoints/shape_predictor_68_face_landmarks.dat
# wget -nc https://github.com/Winfredy/SadTalker/releases/download/v0.0.2/wav2lip.pth -O ./checkpoints/wav2lip.pth
# wget -nc https://github.com/Winfredy/SadTalker/releases/download/v0.0.2/mapping_00229-model.pth.tar -O ./checkpoints/mapping_00229-model.pth.tar
# wget -nc https://github.com/Winfredy/SadTalker/releases/download/v0.0.2/mapping_00109-model.pth.tar -O ./checkpoints/mapping_00109-model.pth.tar
# wget -nc https://github.com/Winfredy/SadTalker/releases/download/v0.0.2/hub.zip -O ./checkpoints/hub.zip
# unzip -n ./checkpoints/hub.zip -d ./checkpoints/
#### download the new links.
wget -nc https://github.com/OpenTalker/SadTalker/releases/download/v0.0.2-rc/mapping_00109-model.pth.tar -O ./checkpoints/mapping_00109-model.pth.tar
wget -nc https://github.com/OpenTalker/SadTalker/releases/download/v0.0.2-rc/mapping_00229-model.pth.tar -O ./checkpoints/mapping_00229-model.pth.tar
wget -nc https://github.com/OpenTalker/SadTalker/releases/download/v0.0.2-rc/SadTalker_V0.0.2_256.safetensors -O ./checkpoints/SadTalker_V0.0.2_256.safetensors
wget -nc https://github.com/OpenTalker/SadTalker/releases/download/v0.0.2-rc/SadTalker_V0.0.2_512.safetensors -O ./checkpoints/SadTalker_V0.0.2_512.safetensors
# wget -nc https://github.com/Winfredy/SadTalker/releases/download/v0.0.2/BFM_Fitting.zip -O ./checkpoints/BFM_Fitting.zip
# unzip -n ./checkpoints/BFM_Fitting.zip -d ./checkpoints/
### enhancer
mkdir -p ./gfpgan/weights
wget -nc https://github.com/xinntao/facexlib/releases/download/v0.1.0/alignment_WFLW_4HG.pth -O ./gfpgan/weights/alignment_WFLW_4HG.pth
wget -nc https://github.com/xinntao/facexlib/releases/download/v0.1.0/detection_Resnet50_Final.pth -O ./gfpgan/weights/detection_Resnet50_Final.pth
wget -nc https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth -O ./gfpgan/weights/GFPGANv1.4.pth
wget -nc https://github.com/xinntao/facexlib/releases/download/v0.2.2/parsing_parsenet.pth -O ./gfpgan/weights/parsing_parsenet.pth
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import os, sys
from pathlib import Path
import tempfile
import gradio as gr
from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call
from modules.shared import opts, OptionInfo
from modules import shared, paths, script_callbacks
import launch
import glob
from huggingface_hub import snapshot_download
def check_all_files_safetensor(current_dir):
kv = {
"SadTalker_V0.0.2_256.safetensors": "sadtalker-256",
"SadTalker_V0.0.2_512.safetensors": "sadtalker-512",
"mapping_00109-model.pth.tar" : "mapping-109" ,
"mapping_00229-model.pth.tar" : "mapping-229" ,
}
if not os.path.isdir(current_dir):
return False
dirs = os.listdir(current_dir)
for f in dirs:
if f in kv.keys():
del kv[f]
return len(kv.keys()) == 0
def check_all_files(current_dir):
kv = {
"auido2exp_00300-model.pth": "audio2exp",
"auido2pose_00140-model.pth": "audio2pose",
"epoch_20.pth": "face_recon",
"facevid2vid_00189-model.pth.tar": "face-render",
"mapping_00109-model.pth.tar" : "mapping-109" ,
"mapping_00229-model.pth.tar" : "mapping-229" ,
"wav2lip.pth": "wav2lip",
"shape_predictor_68_face_landmarks.dat": "dlib",
}
if not os.path.isdir(current_dir):
return False
dirs = os.listdir(current_dir)
for f in dirs:
if f in kv.keys():
del kv[f]
return len(kv.keys()) == 0
def download_model(local_dir='./checkpoints'):
REPO_ID = 'vinthony/SadTalker'
snapshot_download(repo_id=REPO_ID, local_dir=local_dir, local_dir_use_symlinks=False)
def get_source_image(image):
return image
def get_img_from_txt2img(x):
talker_path = Path(paths.script_path) / "outputs"
imgs_from_txt_dir = str(talker_path / "txt2img-images/")
imgs = glob.glob(imgs_from_txt_dir+'/*/*.png')
imgs.sort(key=lambda x:os.path.getmtime(os.path.join(imgs_from_txt_dir, x)))
img_from_txt_path = os.path.join(imgs_from_txt_dir, imgs[-1])
return img_from_txt_path, img_from_txt_path
def get_img_from_img2img(x):
talker_path = Path(paths.script_path) / "outputs"
imgs_from_img_dir = str(talker_path / "img2img-images/")
imgs = glob.glob(imgs_from_img_dir+'/*/*.png')
imgs.sort(key=lambda x:os.path.getmtime(os.path.join(imgs_from_img_dir, x)))
img_from_img_path = os.path.join(imgs_from_img_dir, imgs[-1])
return img_from_img_path, img_from_img_path
def get_default_checkpoint_path():
# check the path of models/checkpoints and extensions/
checkpoint_path = Path(paths.script_path) / "models"/ "SadTalker"
extension_checkpoint_path = Path(paths.script_path) / "extensions"/ "SadTalker" / "checkpoints"
if check_all_files_safetensor(checkpoint_path):
# print('founding sadtalker checkpoint in ' + str(checkpoint_path))
return checkpoint_path
if check_all_files_safetensor(extension_checkpoint_path):
# print('founding sadtalker checkpoint in ' + str(extension_checkpoint_path))
return extension_checkpoint_path
if check_all_files(checkpoint_path):
# print('founding sadtalker checkpoint in ' + str(checkpoint_path))
return checkpoint_path
if check_all_files(extension_checkpoint_path):
# print('founding sadtalker checkpoint in ' + str(extension_checkpoint_path))
return extension_checkpoint_path
return None
def install():
kv = {
"face_alignment": "face-alignment==1.3.5",
"imageio": "imageio==2.19.3",
"imageio_ffmpeg": "imageio-ffmpeg==0.4.7",
"librosa":"librosa==0.8.0",
"pydub":"pydub==0.25.1",
"scipy":"scipy==1.8.1",
"tqdm": "tqdm",
"yacs":"yacs==0.1.8",
"yaml": "pyyaml",
"av":"av",
"gfpgan": "gfpgan",
}
# # dlib is not necessary currently
# if 'darwin' in sys.platform:
# kv['dlib'] = "dlib"
# else:
# kv['dlib'] = 'dlib-bin'
# #### we need to have a newer version of imageio for our method.
# launch.run_pip("install imageio==2.19.3", "requirements for SadTalker")
for k,v in kv.items():
if not launch.is_installed(k):
print(k, launch.is_installed(k))
launch.run_pip("install "+ v, "requirements for SadTalker")
if os.getenv('SADTALKER_CHECKPOINTS'):
print('load Sadtalker Checkpoints from '+ os.getenv('SADTALKER_CHECKPOINTS'))
elif get_default_checkpoint_path() is not None:
os.environ['SADTALKER_CHECKPOINTS'] = str(get_default_checkpoint_path())
else:
print(
""""
SadTalker will not support download all the files from hugging face, which will take a long time.
please manually set the SADTALKER_CHECKPOINTS in `webui_user.bat`(windows) or `webui_user.sh`(linux)
"""
)
# python = sys.executable
# launch.run(f'"{python}" -m pip uninstall -y huggingface_hub', live=True)
# launch.run(f'"{python}" -m pip install --upgrade git+https://github.com/huggingface/huggingface_hub@main', live=True)
# ### run the scripts to downlod models to correct localtion.
# # print('download models for SadTalker')
# # launch.run("cd " + paths.script_path+"/extensions/SadTalker && bash ./scripts/download_models.sh", live=True)
# # print('SadTalker is successfully installed!')
# download_model(paths.script_path+'/extensions/SadTalker/checkpoints')
def on_ui_tabs():
install()
sys.path.extend([paths.script_path+'/extensions/SadTalker'])
repo_dir = paths.script_path+'/extensions/SadTalker/'
result_dir = opts.sadtalker_result_dir
os.makedirs(result_dir, exist_ok=True)
from app_sadtalker import sadtalker_demo
if os.getenv('SADTALKER_CHECKPOINTS'):
checkpoint_path = os.getenv('SADTALKER_CHECKPOINTS')
else:
checkpoint_path = repo_dir+'checkpoints/'
audio_to_video = sadtalker_demo(checkpoint_path=checkpoint_path, config_path=repo_dir+'src/config', warpfn = wrap_queued_call)
return [(audio_to_video, "SadTalker", "extension")]
def on_ui_settings():
talker_path = Path(paths.script_path) / "outputs"
section = ('extension', "SadTalker")
opts.add_option("sadtalker_result_dir", OptionInfo(str(talker_path / "SadTalker/"), "Path to save results of sadtalker", section=section))
script_callbacks.on_ui_settings(on_ui_settings)
script_callbacks.on_ui_tabs(on_ui_tabs)
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# ### some test command before commit.
# python inference.py --preprocess crop --size 256
# python inference.py --preprocess crop --size 512
# python inference.py --preprocess extcrop --size 256
# python inference.py --preprocess extcrop --size 512
# python inference.py --preprocess resize --size 256
# python inference.py --preprocess resize --size 512
# python inference.py --preprocess full --size 256
# python inference.py --preprocess full --size 512
# python inference.py --preprocess extfull --size 256
# python inference.py --preprocess extfull --size 512
python inference.py --preprocess full --size 256 --enhancer gfpgan
python inference.py --preprocess full --size 512 --enhancer gfpgan
python inference.py --preprocess full --size 256 --enhancer gfpgan --still
python inference.py --preprocess full --size 512 --enhancer gfpgan --still