RetinaFace
Deep learning facial detector with landmarks for Python
Pricing
Free tier
Flat rate
Adoption
→StableLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is RetinaFace?
RetinaFace is a deep learning-based tool that detects faces and their landmarks in images, providing high accuracy and precision. It's ideal for applications requiring robust face detection capabilities.
Key differentiator
“RetinaFace stands out for its precision in facial landmark localization and robustness across different image conditions, making it a preferred choice for developers needing high accuracy in face detection tasks.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
API requires Python-specific patterns, TypeScript SDK is community-maintained
Official repository lacks comprehensive guides or tutorials for advanced use cases
Processing times increase significantly with higher resolution inputs, impacting real-time applications
Optimal performance requires GPUs; CPU fallback is much slower and less efficient
Fit analysis
Who is it for?
✓ Best for
Developers building real-time facial detection systems who need high accuracy and speed
Projects that require precise localization of facial landmarks for augmented reality or security purposes
✕ Not a fit for
Applications requiring face recognition beyond just detection (RetinaFace does not perform identity verification)
Real-time applications with extremely low latency requirements, as it may have higher processing times compared to simpler models
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Next step
Get Started with RetinaFace
Step-by-step setup guide with code examples and common gotchas.