Retinify is an advanced AI-powered stereo vision library designed for robotics. It enables real-time, high-precision 3D perception by leveraging GPU and NPU acceleration.
Its C++ API allows the same code to run seamlessly across various acceleration backends.
retinify::tools offers OpenCV-compatible utility functions for image and disparity processing.
Important
The core retinify::Pipeline is independent of OpenCV and supports various image data types.
#include <retinify/retinify.hpp>
#include <opencv2/opencv.hpp>
// LOAD INPUT IMAGES
cv::Mat leftImage = cv::imread(<left_image_path>);
cv::Mat rightImage = cv::imread(<right_image_path>);
// PREPARE OUTPUT CONTAINER
cv::Mat disparity;
// CREATE STEREO MATCHING PIPELINE
retinify::tools::LRConsistencyPipeline pipeline;
// INITIALIZE THE PIPELINE
pipeline.Initialize();
// EXECUTE STEREO MATCHING
pipeline.Run(leftImage, rightImage, disparity);📖 retinify-documentation — Developer guide and API reference.
-
🚀 Installation Guide
Step-by-step guide to build and install retinify. -
🔨 Tutorials
Hands-on examples to get you started with real-world use cases. -
🧩 API Reference
Detailed class and function-level documentation for developers.
| ⚡ Target | Status |
|---|---|
| Coming soon | |
| Coming soon |
- 🌐 Open Source: Fully customizable and freely available under an open-source license.
- 🔥 High Precision: Delivers real-time, accurate 3D mapping and object recognition from stereo image input.
- 💰 Cost Efficiency: Runs using just cameras, enabling depth perception with minimal hardware cost.
- 🎥 Camera-Agnostic: Accepts stereo images from any rectified camera setup, giving you the flexibility to use your own hardware.
For a list of third-party dependencies, please refer to NOTICE.md.
For any inquiries, please feel free to contact us at contact@retinify.ai.
We would be pleased to assist you and look forward to hearing from you.