🚀 Real-Time AI Stereo Vision Library

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.

• 🔥 High Precision: Delivers real-time, accurate 3D mapping and object recognition from stereo image input.
• ⚡ Fast Pipeline: All necessary computations run seamlessly on the GPU, enabling real-time performance.
• 🎥 Camera-Agnostic: Accepts stereo images from any rectified camera setup, giving you the flexibility to use your own hardware.
• 💰 Cost Efficiency: Runs using just cameras, enabling depth perception with minimal hardware cost.
• 🌐 Minimal Dependencies: The pipeline depends only on CUDA Toolkit, cuDNN, and TensorRT, providing a lean and production-grade foundation.

Use of retinify is governed by the current retinify End User License Agreement.
By cloning, building, installing, or using retinify, you agree to the EULA.
If you do not agree, you must not use or update retinify.

For common questions, see the FAQ.

#include <retinify/retinify.hpp>
#include <opencv2/opencv.hpp>

// LOAD INPUT IMAGES
cv::Mat leftImage = cv::imread("path/to/left.png");
cv::Mat rightImage = cv::imread("path/to/right.png");

// PREPARE OUTPUT CONTAINER
cv::Mat disparity = cv::Mat::zeros(leftImage.size(), CV_32FC1);

// CREATE STEREO MATCHING PIPELINE
retinify::Pipeline pipeline;

// INITIALIZE THE PIPELINE
pipeline.Initialize(leftImage.cols, leftImage.rows);

// EXECUTE STEREO MATCHING
pipeline.Execute(leftImage.ptr<uint8_t>(), leftImage.step[0],
                 rightImage.ptr<uint8_t>(), rightImage.step[0]);

// RETRIEVE DISPARITY
pipeline.RetrieveDisparity(disparity.ptr<float>(), disparity.step[0]);

📖 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	⚙️ Env	📦 Status

Latency includes the time for image upload, inference, and disparity download, reported as the median over 10,000 iterations (measured with retinify::Pipeline).
These measurements were taken using each setting of retinify::DepthMode.

For a list of third-party dependencies, please refer to NOTICE.md.

For all inquiries, including support, collaboration, and EULA-related matters, please contact:
[email protected]