GhostXia / Dain-App

Source code for Dain-App

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DAIN-APP Application

This is the source code for the video interpolation application Dain-App, developed on top of the source code of DAIN Dain GIT Project

Table of Contents

  1. Introduction
  2. Citation
  3. Requirements and Dependencies
  4. Installation
  5. Running application with interface
  6. Running application with command line
  7. Slow-motion Generation
  8. Training New Models
  9. Google Colab Demo

Introduction

Dain-App comes with a user interface and a command line script to help new users to start using it with little change to the code. You can also get the Windows binary from the build section.

You can see a few results from those Youtube videos. Turning animations to 60FPS. Turning Sprite Art to 60FPS. Turning Stop Motion to 60FPS. Turning ANIME P1 to 60FPS. Turning ANIME P2 to 60FPS.

Citation

If you find the code and datasets useful in your research, please cite:

@article{Dain-App,
	title={Dain-App: Application for Video Interpolations},
	author={Gabriel Poetsch},
	year={2020}
}
@inproceedings{DAIN,
    author    = {Bao, Wenbo and Lai, Wei-Sheng and Ma, Chao and Zhang, Xiaoyun and Gao, Zhiyong and Yang, Ming-Hsuan}, 
    title     = {Depth-Aware Video Frame Interpolation}, 
    booktitle = {IEEE Conference on Computer Vision and Pattern Recognition},
    year      = {2019}
}
@article{MEMC-Net,
     title={MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Interpolation and Enhancement},
     author={Bao, Wenbo and Lai, Wei-Sheng, and Zhang, Xiaoyun and Gao, Zhiyong and Yang, Ming-Hsuan},
     journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
     doi={10.1109/TPAMI.2019.2941941},
     year={2018}
}	

Requirements and Dependencies

  • numba=0.51.2
  • numpy=1.19.2
  • opencv-python=4.4.0.46
  • pillow=8.0.1
  • pyqt5=5.15.1
  • python=3.8.5
  • scikit-learn=0.23.2
  • scipy=1.5.4
  • torch=1.7.0+cu110
  • torchvision=0.8.1+cu110
  • tqdm=4.51.0
  • ffmpeg

Installation

Check out the Colab code:

Remember you need to build the .cuda scripts before the app can work.

Running application with interface

python my_design.py

Running application with command line

You can see all commands for CLI using this code:

python my_design.py -cli -h

A example of a working code:

python  my_design.py -cli --input "gif/example.gif" -o "example_folder/" -on "interpolated.gif" -m "model_weights/best.pth" -fh 3 --interpolations 2 --depth_awarenes 0 --loop 0 -p 0 --alpha 0 --check_scene_change 10 --png_compress 0 --crf 1 --pixel_upscale_downscale_before 1 --pixel_downscale_upscale_after 1 --pixel_upscale_after 1 --mute_ffmpeg 1 --split_size_x -1 --split_size_y -1 --split_pad 150 --half 0 --step_extract 1 --step_interpolate 1 --batch_size 1 --use_benchmark 0 --force_flow 1 --smooth_flow 0 --downscale -1 --fast_mode 0

Training New Models

Currently Dain-App training code is broken, to train new models, use the DAIN github and import the models to Dain-App

Google Colab Demo

Contact

Gabriel Poetsch

License

See MIT License

About

Source code for Dain-App

License:MIT License


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