OpenFace vs DLib

Side-by-side — pricing, strengths, tradeoffs, and fit.

OpenFace

Free and open-source face recognition with deep neural networks.

DLib

C++ and Python library for face detection and object training.

At a glance

Open SourceFree Tier
● Established·From $0
Open SourceFree Tier
● Established·From $0

Overview

One-liner

Free and open-source face recognition with deep neural networks.

One-liner

C++ and Python library for face detection and object training.

Maturity

Established

Maturity

Established

Open source

✓ Yes

Open source

✓ Yes

Pricing

Free tier

✓ Available

Open source — free to use

Free tier

✓ Available

Open source — free to use

Starts at

$0

Starts at

$0

Model

Flat rate

Model

Flat rate

Enterprise

✕ None

Enterprise

✕ None

Best for

✓ Best for

Teams building custom face recognition applications who need a comprehensive toolkit with multiple capabilities like landmark detection, head pose estimation, and facial action unit recognition
Developers working on projects that require self-hosted solutions for privacy or performance reasons

✓ Best for

Teams working on computer vision projects who need robust face detection and object training capabilities.
Developers looking to integrate advanced imaging functionalities in their applications using C++ or Python.

Not ideal for

✕ Not for

Projects requiring real-time processing at scale where cloud-based services might offer better performance
Applications needing a web-based interface as OpenFace is primarily a library to be integrated into applications

✕ Not for

Projects requiring real-time video processing where DLib's performance might not be optimal.
Applications that require a cloud-based service for image processing, as DLib is primarily designed for local use.

Strengths

↑ Strengths

Facial landmark detection
Head pose estimation
Facial action unit recognition
Face recognition using deep neural networks

↑ Strengths

Face detection capabilities
Training of general object detectors
Support for both C++ and Python interfaces
Robust documentation and community support

Weaknesses

↓ Weaknesses

Limited documentation and examples for complex use cases
Performance degradation with large datasets or real-time processing

↓ Weaknesses

Limited documentation and examples for C++ interface
Performance issues with large datasets in face detection tasks
Limited support for advanced computer vision features beyond face and object detection
Full OpenFace profile →Full DLib profile →