Skip to content

DJAlexJ/LRCN-for-Video-Regression

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

53 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

LRCN (Long-term Reccurent Convolutional Networks) approach for video regression

Idea is taken from https://arxiv.org/pdf/1411.4389.pdf

To begin working with LRCN library, perform the following steps:

  1. !git clone https://github.com/DJAlexJ/LRCN-for-Video-Regression.git
  2. cd LRCN-for-Video-Regression && pip install -e .

Before training you have to a create folder with movie trailers and prepare a markup for them. Paths to the trailers, markup and model wieghts should be specified in config.py

Markup example

Title Score
movie1.mp4 8.7
... ...
movieN.flv 5.2

Training model

from lrcnreg/lrcnreg folder: python train.py (python train.py -h to see additional arguments)

Getting predictions

from lrcnreg/lrcnreg/scripts: python predict.py --input_path='Path to the trailers' --output_path='File with predictions (e.g. ./res.txt)' --weights='Path to the model weights'

About

LRCN approach for video regression that uses CNNs for visual input and LSTMs to process sequences of frame embeddings

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published