Skip to content

Latest commit

 

History

History
53 lines (40 loc) · 1.6 KB

README.md

File metadata and controls

53 lines (40 loc) · 1.6 KB

LRCN_PyTorch

This project includes the whole training process. Specifically, I use PyTorch 1.7 VideoIO / Video Datasets Loading API / Video Transform to process the Data. More Details：How to use Video Datasets，Video IO，Video Classification Models，Video Transform in PyTorch

The LRCN's paper：Long-term Recurrent Convolutional Networks for Visual Recognition and Description. download

 

Performance

Accuracy
62.43% (only 4 epochs)

 

Training Environment

  • Ubuntu 16.04.7 LTS
  • CUDA Version: 10.1
  • PyTorch 1.7.1
  • torchvision 0.8.2
  • numpy 1.19.2
  • pillow 8.1.0
  • python 3.8.5
  • av 8.0.3
  • matplotlib 3.3.4

 

Data Preparation

Original Dataset：UCF101

After downloading the UCF101 dataset: UCF101.rar and UCF101TrainTestSplits-RecognitionTask.zip, you should seperately unrar them. Then put it into the directory named data

Project
│--- data
│------ UCF101
│------ UCF101TrainTestSplits-RecognitionTask
│--- other files

 

Train

Before training, make sure you have a directory named model in the root project to save checkpoint file.

python3 train.py

 

Problems

I recorded some problems and solutions when writing the code. Really so sorry that I only write in Chinese! Here is the Link