Important
Please Help by starring the repo. π
Lip-Wise leverages Wav2Lip for audio-to-lip generation, seamlessly integrating with cutting-edge face restoration models (CodeFormer, GFPGAN, RestoreFormer) for added realism. MediaPipe ensures precise facial landmark detection, while RealESRGAN enhances background quality. Simply provide an audio clip and a reference video, and Lip-Wise orchestrates the process to deliver stunning results.
Here's what makes Lip-Wise stand out:
- Effortless Workflow: Unleash your creativity with an intuitive and user-friendly interface.
- Unleash Your Vision: No more limitations - use any video, even those without a face in every frame.
- Precision Meets Efficiency: Combining enhanced face detection, landmark recognition, and streamlined processing delivers superior results with significantly faster performance.
- Simplified Setup: Get started quickly with minimal technical hassle - a breeze even for beginners.
π‘Tip: Make sure to use GPU runtime for faster processing.
- Clone this repository:
git clone https://github.com/pawansharmaaaa/Lip_Wise
- Install
Python > 3.10
from Official Site or From Microsoft store.- Install winget from Microsoft Store.
- Download and install the CUDA Toolkit that is compatible with your system. The latest version generally supports most NVIDIA 10-series graphics cards and newer models.
- Run
setup.bat
- Run
launch.bat
- Clone this repository:
git clone https://github.com/pawansharmaaaa/Lip_Wise
- Make sure
python --version
is>3.10
- Download and install the CUDA Toolkit that is compatible with your system. The latest version generally supports most NVIDIA 10-series graphics cards and newer models.
- Make
setup.sh
an executable
chmod +x ./setup.sh
- Run
setup.sh
by double clicking on it.- Make
launch.sh
an executable
chmod +x ./launch.sh
- Run
launch.sh
by double clicking on it.
LipWise empowers you to create stunningly realistic and natural results, combining the power of AI with user-friendly features:
- Process both images and videos: Breathe life into your visuals, regardless of format.
- Advanced image and video preprocessing: Ensure optimal quality for exceptional results.
- Harness the power of leading models: GFPGAN, RestoreFormer, and CodeFormer work in tandem to deliver exceptional detail and clarity.
- RealESRGAN integration: Enhance the background quality of your visuals effortlessly.
- 3D alignment in process image: Achieve unparalleled realism with precise facial landmark detection.
- No need for face in every frame: LipWise intelligently interpolates missing frames, ensuring smooth transitions and realistic lip movements.
- Fast inference: Enjoy a fluid experience with rapid video processing.
- Video looping: Create seamless looping videos with consistent results.
- RealESRGAN integration: Elevate the background quality of your videos effortlessly
Lip-Wise is released under Apache License Version 2.0.
@inproceedings{10.1145/3394171.3413532,
author = {Prajwal, K R and Mukhopadhyay, Rudrabha and Namboodiri, Vinay P. and Jawahar, C.V.},
title = {A Lip Sync Expert Is All You Need for Speech to Lip Generation In the Wild},
year = {2020},
isbn = {9781450379885},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3394171.3413532},
doi = {10.1145/3394171.3413532},
booktitle = {Proceedings of the 28th ACM International Conference on Multimedia},
pages = {484β492},
numpages = {9},
keywords = {lip sync, talking face generation, video generation},
location = {Seattle, WA, USA},
series = {MM '20}
}
@inproceedings{zhou2022codeformer,
author = {Zhou, Shangchen and Chan, Kelvin C.K. and Li, Chongyi and Loy, Chen Change},
title = {Towards Robust Blind Face Restoration with Codebook Lookup TransFormer},
booktitle = {NeurIPS},
year = {2022}
}
@InProceedings{wang2021gfpgan,
author = {Xintao Wang and Yu Li and Honglun Zhang and Ying Shan},
title = {Towards Real-World Blind Face Restoration with Generative Facial Prior},
booktitle={The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2021}
}
@InProceedings{wang2021realesrgan,
author = {Xintao Wang and Liangbin Xie and Chao Dong and Ying Shan},
title = {Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data},
booktitle = {International Conference on Computer Vision Workshops (ICCVW)},
date = {2021}
}
Reach out to me @ lipwisedev@gmail.com