Metadata-Aware Output Converters in Savant
Savant output converters can now receive the frame's metadata — source_id, PTS, objects, and more — unlocking per-source and per-frame post-processing without breaking existing converters.
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News, updates, and handy materials related to the Savant ecosystem
Scene Change Detection with Savant: Catching Camera Tampering with ReID Embeddings
A new Savant sample detects when a camera has been moved, blocked, or its scene has changed — by comparing a ReID embedding of a region of interest against the...
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The Line That Moves: Rust's Real Place in Computer Vision
The memory-safety pitch for Rust in computer vision misses the point. The real case is narrower and stronger: Rust governs the authored layer above the C/C++/CUDA substrate, and its compile-forced...
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Colocating Multiple PyFuncs with the New pygroup Element
Savant's new pygroup element runs several sequential PyFuncs inside a single GStreamer element — cutting inter-element overhead while keeping a separate telemetry span for every stage.
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What It Takes to Use a YOLO Model Legally in a Commercial Product
A fact-checked, license-by-license guide to shipping YOLO in a commercial product: permissive vs. copyleft, what copyright actually protects, which YOLO flavors are safe (YOLOX, RT-DETR, DAMO-YOLO, PP-YOLOE) versus traps (Ultralytics AGPL, GPL v6/v7/v9, YOLO-NAS weights), the COCO/ImageNet data risk, and how to build a detector you fully own.
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When Is NVIDIA Jetson Orin the Right Fit for Your Project?
A decision guide for NVIDIA Jetson Orin — when on-device neural inference makes Orin essential, how to move from dev kit to production module, the NVDEC/NVENC/NVJPEG media-engine trap, the CUDA-to-edge workflow, OS and lifecycle planning, and how Orin compares to Coral, Hailo, Rockchip, and Thor.
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How to Choose the Best Camera for Computer Vision (2026)
A use-case-first guide to picking a computer vision camera that actually works in production — covering the five deployment classes, the three tradeoffs on every spec sheet, mounting rules that beat the spec sheet, latency, and real LPR examples.
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Native CSI Camera Input for Savant on NVIDIA Jetson
Savant now supports direct CSI camera capture on NVIDIA Jetson through a new nvarguscamerasrc_bin pipeline source element. Frames land in GPU memory with zero encoding or network overhead — the shortest path from sensor to inference for robotics and embedded vision.
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Why nvv4l2h264enc Fails Inside Docker on Jetson Orin NX with JetPack 6.2.2
Hardware H.264 encoding works on the host but fails inside Docker on Jetson Orin NX with JetPack 6.2.2. The root cause turns out to be a missing two-megabyte package — and finding it required strace, DRM ioctls, and reverse-engineering NVIDIA's closed-source libraries.
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Savant vs. DeepStream: What to Use, When, and Why
DeepStream is the most optimized SDK for video analytics on NVIDIA hardware. Savant is built on top of it. This article explains the relationship between the two, what each brings to the table, and which to reach for depending on your project's requirements.
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Savant vs. PyTorch: Purpose, Architecture, and When to Use Each
PyTorch and Savant are both Python-first and CUDA-capable, yet they solve fundamentally different problems. This article explains the design philosophies, target audiences, and use cases of each — and when it makes sense to use them together.
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Building a Fan-Out/Fan-In Video Analytics Pipeline with Savant
A step-by-step guide to building a fan-out/fan-in video analytics pipeline that distributes a stream across multiple parallel modules, runs independent inference, and merges results back into a single frame using Savant and savant-rs.
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Introducing Meta-Merge: Fan-Out/Fan-In for Savant Video Analytics Pipelines
Savant ecosystem gains Meta-Merge, a new service that completes the Fan-Out/Fan-In pattern by merging metadata from parallel inference branches back into a single unified frame.
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How to Prepare an Ultralytics Model for Use in Savant
A step-by-step guide to exporting Ultralytics models to the ONNX format for use in Savant's TensorRT-based inference pipeline.
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Savant 0.6.0 is Out: The First Release to Support Blackwell GPUs
Savant 0.6.0 brings Blackwell GPU support through custom-built DeepStream 7.1 with TensorRT 10.9, plus Python 3.12 for improved CPU-bound performance.
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Choosing the Technology for a Computer Vision Product (Part 1)
An in-depth landscape overview of current and legacy tech stacks for computer vision applications, covering frameworks from OpenCV to DeepStream to Savant.
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Introducing Router: A New Savant Service for Smarter Video Stream Routing
Savant ecosystem expands with Router, a new microservice for simplifying and optimizing the routing of video streams across complex CV pipelines.
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New Release Announcement: Retina RTSP Service Now Available!
Retina RTSP Service enables seamless integration of real-time video streaming into Savant-powered AI video pipelines with low latency and high performance.
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Savant 0.5.1: DeepStream 7.0 and New Features
Savant 0.5.1 brings DeepStream 7.0 support, 34 real-world samples, Key-Value API, original resolution processing, and many more enhancements.
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USB/CSI-2 VS RTSP Cam For The Nvidia Jetson Project
We explain the advantages of USB/CSI cameras over RTSP cameras for projects working on Nvidia Jetson Orin hardware.
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Choosing A Camera For Computer Vision Wise: Resolution, Image Quality, Lens and Software
A deep dive into camera properties that matter for computer vision: sensor quality, lens selection, chip processing, and software encoding.
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Savant 0.4.8 is Out: A Bugfix Release
A minor bugfix update to Savant 0.4.x, fixing issues with JSON/image/video sink adapters.
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Savant 0.4.7 is Out: A Bugfix Release
A minor bugfix update to Savant 0.4.x for JSON/image/video sink adapters.
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Savant 0.4.1 is Out: Spotlight on Advanced Video Processing Features
Savant 0.4.1 continues the 0.4.x release cycle with new features, bug fixes, and a new watchdog service for pipeline health monitoring.
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Dump and Replay Video Traffic with a Buffer Adapter
Learn how to record and replay video streaming traffic for reproducible testing, troubleshooting, and code improvement in Savant pipelines.
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Auxiliary Video Stream Support in Savant
Savant now supports hardware-accelerated video transcoding and composition, enabling custom dashboards, resolution changes, and video walls.
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Savant 0.4.0: Advanced Adapters, Developer Tools, Video Archiving and Re-Streaming
Savant 0.4.0 focuses on system usability, interfacing, advanced computer vision, and video analytics on top of DeepStream 6.4.
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A New Integration Opens the Way in the Cloud: Meet Amazon KVS Adapters
New adapters integrate Amazon Kinesis Video Streams with Savant, combining video-optimized streaming and storage in the cloud.
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Working with Dynamic Video Sources in Savant
Learn how to dynamically attach and detach video sources to a running Savant pipeline using Docker, including Unix domain sockets and TCP/IP.
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How to Work with MJPEG USB Camera in Savant
Savant 0.3.11 adds MJPEG USB camera support -- a popular format for high-resolution, high-FPS streaming and stereo cameras.
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Emulating USB Camera in Linux
How to simulate an MJPEG USB camera in Linux using FFmpeg and a V4L2 loopback device for development and testing.
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Savant is More Than Three Times Faster Than PyTorch in Video Inference
Benchmark results demonstrating Savant's performance advantage over PyTorch for video inference, including hardware-accelerated decoding.
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How to Implement High Performance Keypoint Detection
Learn how to implement keypoint detection for pose estimation, facial recognition alignment, and action recognition using Savant.
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How to Count People in Polygonal Areas with Savant
Using Nvidia PeopleNet and Savant to accurately count and monitor people in user-defined polygonal areas for various applications.
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Car License Plate Recognition with YOLOv8 and LPR Models from Nvidia NGC
Building a license plate detection and recognition pipeline using YOLOv8 and Nvidia NGC models with the Savant framework.
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New Feature: Video Pass-Through
Media Pass-Through allows copying the incoming video stream to output without transcoding, optimizing pipelines that don't need draw functionality.
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Ten Reasons to Consider Savant for Your Computer Vision Project
Why you may find it beneficial to use Savant instead of DeepStream, OpenVINO, PyTorch, or OpenCV in your next computer vision project.
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Crafting Scalable Computer Vision Video Analytics with Kafka and KeyDB
How to build scalable computer vision applications using Kafka and KeyDB for handling real-time and delayed video processing at scale.
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Approaches on How to Surpass Real-Time Video Analytics Challenges
Exploring the challenges of real-time video analytics and practical approaches to overcome them using modern frameworks and hardware acceleration.
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How to Run Real-Time Vehicle Traffic Analysis with YOLOv8, Graphite and Grafana
Build a pipeline that calculates vehicles passing through metering zones and sends statistics to Grafana for visualization.
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Made in Savant: RocksQ -- A Persistent Python Queue
Introducing RocksQ, a high-performance persistent queue built on RocksDB for buffering video frames and metadata in Savant.
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Dynamic Parameters Reconfiguration with Etcd in Savant Framework
How to dynamically reconfigure pipeline parameters at runtime using Etcd for adaptive computer vision applications.
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Savant Release 0.2.5
Savant 0.2.5 brings significant changes, new features, and improvements to developer experience and deployment.
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OpenTelemetry in Savant: Instrumenting Deep Learning Computer Vision Pipelines
How to use OpenTelemetry to trace, log, and collect metrics for deep learning computer vision pipelines in Savant.
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Facial Identification with Savant, YOLOv5-Face, AdaFace and HNSWLib
A high-performance facial re-identification pipeline using Savant for doorbell security and video content annotation systems.
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Real-Time Instance Segmentation with YOLOv8m-seg and Savant Framework
Running real-time instance segmentation with the YOLOv8 family on Savant, enabling efficient object segmentation on edge and data center hardware.
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Savant Explained: Software Video Encoder
How Savant handles video encoding on hardware that lacks NVENC, such as Jetson Orin Nano, Tesla A100, and Tesla H100.
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Savant Explained: Pipeline Element Groups
Element Groups allow conditionally loading pipeline elements during initialization based on environment variables and expressions.
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