OpenGM

What it is

OpenGM is a powerful tool for solving discrete optimization problems using factor graph models. It supports various algorithms and can be used in computer vision tasks, among others.

OpenGM stands out with its comprehensive support for discrete optimization and inference on factor graphs, making it a versatile tool for researchers and developers working on complex problems.

When it fits — and when it doesn’t

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

1. 01

   Steep learning curve for non-C++ developers

   OpenGM's primary language is C++, which may be challenging for developers unfamiliar with the language or its idioms.

2. 02

   Limited documentation and support resources

   The official documentation lacks comprehensive examples and tutorials, making it difficult to understand how to use advanced features effectively.

3. 03

   Performance overhead due to template-heavy design

   Extensive use of C++ templates can lead to longer compilation times and larger binary sizes compared to more straightforward implementations.

4. 04

   Narrow focus on factor graph models limits general applicability

   While powerful for discrete optimization problems, OpenGM's specialized approach makes it less suitable for a broader range of computational tasks outside its domain.

What it does well

• Support for various discrete optimization algorithms

• Factor graph representation of problems

• Modular design allowing easy integration with other tools

Pricing

Free tier

YesOpen source — free to use

Paid from

$0

Model

Flat rate

Enterprise plan

No

Pricing not independently confirmed — check the vendor’s page.