/MovingObjectSegmentation

Moving Object Segmentation

Primary LanguageJupyter NotebookGNU General Public License v3.0GPL-3.0

Moving Object Segmentation

Requirements

  1. Python 3.6.9
  2. PyTorch 1.3
  3. OpenCV 4.0.1
  4. tensorboardX 2.2
  5. matplotlib

Dataset

Steps for preparing CDNet2014

  1. Download the dataset from changedetection.net and unzip the contents in ./dataset/currentFr

  2. Download pre-computed frames from Google Drive and place the contents in ./dataset

  3. In the end, ./dataset folder should have the following subfolders: currentFr, currentFrFpm, emptyBg, emptyBgFpm, recentBg, recentBgFpm.

Cross-validation

  1. Run python train.py --set_number <k> for <k> = 1, 2, 3 and 4 to compute the results for each fold. This code will save the results to log.csv.

  2. Follow the steps in notebooks/crossvalidation.ipynb to analyze cross-validation results.

Visualization of Spatio-Temporal Data Augmentations

Follow the steps in notebooks/visualization.ipynb to visualize spatio-temporal data augmentations.

Training and Cross-Validation with other datasets.

Change ./configs/data_config.py and ./configs/full_cv_config.py for training the networks with different datasets.