Welcome to Selam’s documentation!

Contents:

Selam

Documentation Status Updates

Underwater object tracking framework for Robosub

Features

  1. Underwater image preprocessing
  2. Object proposals
  3. Automatic machine learning
  4. Object tracking

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

Getting Started

Stable release

To install Selam, run this command in your terminal:

$ pip install selam

This is the preferred method to install Selam, as it will always install the most recent stable release.

If you don’t have pip installed, this Python installation guide can guide you through the process.

From sources

The sources for Selam can be downloaded from the Github repo.

You can either clone the public repository:

$ git clone git://github.com/jinified/selam

Or download the tarball:

$ curl  -OL https://github.com/jinified/selam/tarball/master

Once you have a copy of the source, you can install it with:

$ python setup.py install

Training & Evaluation

Ground Truth Generation

Using AIBU

References

Tracker Evaluation

Using VOT Toolkit

References

Preprocessing

Color Correction

Core API

References

Underwater Image Enhancement

Core API

References

Object Proposal

Grouping-based object proposal

Core API

References

Window scoring-based object proposal

Core API

References

Blob-based object proposal

Core API

References

Saliency-based object proposal

Core API

References

Feature Engineering

Choosing color spaces

Core API

References

Feature Detector & Descriptor

Core API

References

Model Learning

Data Augmentation

Core API

References

Training Classifier

Core API

References

Unsupervised Learning

Core API

References

Automatic machine learning

Feature Selection

Core API

References

Model Selection

Core API

References

Object Tracking

Single Object Tracking (Fixed Model)

Core API

References

Online Update

Core API

References

Indices and tables