/rvc_devkit

Robust Vision Challenge Devkits; Stable releases are in this branch: https://github.com/ozendelait/rvc_devkit/tree/release

Primary LanguagePython

Robust Vision Challenge 2020 Devkits

This repository contains the devkits for the Robust Vision Challenge 2020. The devkits make it easy to participate in the challenge by:

  • downloading the required datasets,
  • converting them to a common format, and
  • creating archives for submission to the individual benchmarks.

Any updates to the devkits will be provided via this repository.

Notice that using the devkits is not required for participating in the challenge: alternatively, algorithms can be manually run on each dataset and results submitted to all benchmarks individually (as long as the same method and parameters are used for all results).

Getting started

Prerequisites: Install wget, git, and python (both versions 2.7.x and 3.x should work) if they are not installed yet.

  1. Clone this repository: git clone https://github.com/ozendelait/rvc_devkit.git
  2. Install required python packages: pip install -r requirements.txt
  3. See the README in the subfolder of the task you are interested in (depth, flow, etc.) for further task-specific instructions.

Note: Windows support is experimental and not recommended. Use an Anaconda environment and gitbash to execute the scripts. The required wget can be installed with conda install -c menpo wget

Participating

The process for participating in the challenge is as follows.

  • After following the instructions for getting started above, download the datasets for the task which you are interested in using the devkit for this task. See the README in the task subfolder for instructions on this.
  • Most datasets come with ground truth data and can be used for training your algorithm.
  • Once you are happy with the results of your algorithm based on the training datasets, run your algorithm on all datasets. See the README for the specific task for information on the expected result format.
  • Use the devkit to create submission archives for all included benchmarks.
  • Register your submission at the submission form. Choose a short method name (up to 10 characters) for your method (allowed characters: + - _ A..Z a..z 0..9) to guarantee that you can use exactly the same name on all benchmarks. Make sure to use "_RVC" as a postfix to your method name (e.g. ELAS_RVC)
  • Submit each submission archive to the respective benchmark website.