g-thebest/PWStableNet

Implementation of pixel-wise video stabilization

PWStableNet: Learning Pixel-wise Warping Maps for Video Stabilization

This is a PyTorch implementation of PWStableNet: Learning Pixel-wise Warping Maps for Video Stabilization.

Source code and models will be opened soon!

If you have any questions, please contact with me: zmd1992@mail.ustc.edu.cn

Table of Contents

• Prerequisites
• Datasets
• Train
• Performance
• Demos
• Reference

       

Prerequisites

• Linux
• Python 3
• NVIDIA GPU (12G or 24G memory) + CUDA cuDNN
• pytorch 0.4.0+
• numpy
• cv2
• ...

Datasets

The dataset for is the DeepStab dataset (7.9GB) http://cg.cs.tsinghua.edu.cn/download/DeepStab.zip thanks to Miao Wang [1].

Training

• The code will download the VGG-16 PyTorch base network weights at: https://download.pytorch.org/models/vgg16-397923af.pth automatically.

• To train PWNet using the train script simply specify the parameters listed in ./lib/cfg.py as a flag or manually change them.

• The default parameters are set for the use of two NVIDIA 1080Ti graphic cards with 24G memory.

CUDA_VISIBLE_DEVICES=0,1 python3 main.py

• Note:
  • For training, an NVIDIA GPU is strongly recommended for speed.
  • Before training, you should ensure the location of preprocessed dataset, which will be supplied soon.

Performance

Original result before improvement:

we show an example videos to compare our PWNet with StabNet [1]

• The video can be download here. https://github.com/mindazhao/pix-pix-warping-video-stabilization/blob/modified/videos/example.mp4

More video result with improved PWStableNet

• Example I: https://github.com/mindazhao/pix-pix-warping-video-stabilization/blob/modified/videos/example1.avi
• Example II: https://github.com/mindazhao/pix-pix-warping-video-stabilization/blob/modified/videos/example2.avi
• Parallax:
  1. weak parallax: https://github.com/mindazhao/pix-pix-warping-video-stabilization/blob/modified/videos/weak_parallax.avi
  2. middle parallax: https://github.com/mindazhao/pix-pix-warping-video-stabilization/blob/modified/videos/middle_parallax.avi
  3. strong parallax: https://github.com/mindazhao/pix-pix-warping-video-stabilization/blob/modified/videos/strong_parallax.avi
• Low quality: https://github.com/mindazhao/pix-pix-warping-video-stabilization/blob/modified/videos/Low quality.avi

Note: If you have any problem to download these videos, you can visit another website: http://home.ustc.edu.cn/~zmd1992/PWStableNet.html

Demos

Use a pre-trained PWNet for video stabilization

Download a pre-trained network

• We are trying to provide a pre-trained model.
• Currently, we provide the following PyTorch models: model can be get from home.ustc.edu.cn/~zmd1992/PWStableNet/netG_model.pth
• You can test your own unstable videos by changing the parameter "train" with False and adjust the path yourself in function "process()".

Authors

• Minda Zhao

References

[1] M. Wang, G.-Y. Yang, J.-K. Lin, S.-H. Zhang, A. Shamir, S.-P. Lu, and S.-M. Hu, “Deep online video stabilization with multi-grid warp- ing transformation learning,” IEEE Transactions on Image Processing, vol. 28, no. 5, pp. 2283–2292, 2019