Opendatacam is live · free · last verified 26 Oct 2026 · viability monitor
Opendatacam
Open source computer vision to count and track moving objects from cameras or video on your own hardware.
Pick OpenDataCam if you want traffic or footfall counting where the visual data never leaves your own box — turn counts, modal split and trajectory work are its home turf, and the counter logic plus REST API give you real control. Budget engineering time, not just money: it runs from Docker, needs a CUDA-capable GPU (CUDA 11 / cuDNN 8, or Jetpack 5.x on Jetson), and accuracy hinges on which YOLO weights your hardware can carry. If you want a managed dashboard with someone else on the hook for uptime, a hosted computer-vision analytics service is the better trade. Against roll-your-own OpenCV counting, OpenDataCam saves you the tracking, counting and UI work.
Verdict generatedVerified 4d ago · liveness 59/100 · cite: rightaichoice.com/tools/opendatacam
- Traffic engineers working on modal split, turn counts and congestion
- Smart city and municipal teams that need privacy-preserving camera data
- Urban mobility and computer vision researchers
- Developers and makers comfortable with Docker and GPU setup
- Teams that want a fully managed, cloud-hosted analytics dashboard
- Projects that require facial recognition or identity matching
- Beginners with no Docker or NVIDIA GPU/CUDA experience
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Skip OpenDataCam if you need a managed cloud dashboard and someone else to run it — it is a self-hosted Docker deployment you install and maintain on your own CUDA-capable hardware.
You supply the hardware: a CUDA-capable NVIDIA GPU is required, so a Jetson Nano, Xavier, desktop or server is an out-of-pocket cost before you count anything.
The community edition is a free, open-source distribution you run on your own hardware, so the meaningful comparison isn't subscription price — it's total cost of ownership. Against a hosted computer-vision analytics subscription, you trade a recurring fee and per-camera charges for a GPU device, install time and ongoing maintenance. For a single camera experiment that is cheap; for a large multi-site rollout, price the edge hardware and engineering hours before assuming it undercuts a managed
In short
Opendatacam — Open source computer vision to count and track moving objects from cameras or video on your own hardware. Best for Traffic engineers working on modal split, turn counts and congestion, Smart city and municipal teams that need privacy-preserving camera data, Urban mobility and computer vision researchers. Free to use.
What is Opendatacam?
Opendatacam — Open source computer vision to count and track moving objects from cameras or video on your own hardware. Best for Traffic engineers working on modal split, turn counts and congestion, Smart city and municipal teams that need privacy-preserving camera data, Urban mobility and computer vision researchers. Free to use.
OpenDataCam is an open-source tool that uses machine learning to detect and follow moving objects in video feeds and pre-recorded files, then reports anonymous counts. It is built around YOLO-based object detection with 50+ classes out of the box, and you can train your own model when the default weights miss what you need. Detection alone isn't the point — OpenDataCam tracks objects across frames, so you can define virtual counters in the web UI or via the REST API and log time, object type and direction each time something crosses. Counter chaining lets you follow turns and paths through a junction, and trajectory analysis shows how movement flows through a scene. Sources include USB cameras, IP cameras, RTSP streams, YouTube Live and dropped-in video files. All processing happens on location: only metadata — object paths and counts — is stored, and no visual data is saved or leaves the device. It runs from Docker images on NVIDIA Jetson devices (Nano, Xavier), laptops, desktops and GPU servers, and is documented as running at least 10 FPS on any Jetson with default settings, though actual accuracy and speed depend on which YOLO weights your hardware can run. The maintainers publish paid professional offers and services alongside the free open-source edition, and the code on GitHub is licensed CC BY-SA 4.0.
Key features
- YOLO-based object detection with 50+ common object classes out of the box
- Custom model training for objects the default weights don't detect
- Virtual counters configured through the web UI or REST API
- Counter chaining to log turns and multi-point paths
- Trajectory analysis of object movement through a scene
- Real-time input from USB cameras, IP cameras and RTSP streams
- YouTube Live stream as a video source
- Pre-recorded video file analysis, including drag-and-drop into the browser
- Runs on NVIDIA Jetson Nano, Xavier and Xavier NX edge devices
- Runs on laptops, desktops and GPU servers with NVIDIA hardware
- On-device processing: no visual data saved or leaving the device
- Metadata-only storage of object paths and counts
- Web UI for configuration and live visualisation
- REST API for camera control and retrieving count data
- Docker and Docker-Compose based deployment with auto-restart container
Our long-form take written Jul 30, 2026 is more than 90 days old, so it is being re-reviewed against current data and is not shown.
Models under the hood
as of 2026-10-22
Limitations
- Accuracy depends on which YOLO weights the hardware can run, and FPS depends on the hardware and the YOLO weights used — the docs make no fixed accuracy promise.
- Getting started requires Docker and Docker-Compose; NVIDIA GPU acceleration needs CUDA 11, cuDNN 8 and the Nvidia container toolkit, while Jetson devices need Jetpack 5.x.
- Installation is command-line driven via a per-platform install script.
as of 2026-09-29
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Is Opendatacam still active?
Opendatacam is live · free · last verified 26 Oct 2026 · viability monitor.
Viability score
How well maintained and how widely used is Opendatacam? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →What do users say about Opendatacam?
What people actually say about Opendatacam — is it worth it?
Our community sentiment research written Jul 30, 2026 is more than 90 days old, so it is being re-reviewed against current data and is not shown.
How we verified this
Every listed fact about Opendatacam— pricing, features, links, status — is re-read from the vendor's own pages by our verification pipeline and each change is logged with a date; the last pass ran on 26 Oct 2026. Pages mix model-assisted synthesis with human review; see how we verify.
Verification history
We have re-verified Opendatacam 7 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — changed SSL certificate
- — changed limitations
- — changed our verdict, features, hidden costs, who it suits, description, limitations, switching in, switching out, who should skip it, pricing tiers, pricing fit, setup time, use cases
- — changed limitations
- — changed SSL certificate, domain expiry
- — changed limitations
Showing the 6 most recent of 7 verification passes.
Free to cite with attribution — this page re-verifies continuously.
How much does Opendatacam cost in 2026?
Opendatacam: Free to use. Pricing last verified 26 Oct 2026.
Plans compared
Every published Opendatacam tier, its price as the vendor publishes it, who it fits, and what it adds over the tier below. The 12-month cost projection follows.
| Plan | Price | Billing | Who it's for |
|---|---|---|---|
| Open Source Community Edition | Free | — | Researchers, traffic engineers and developers who have a CUDA-capable GPU or Jetson device and are comfortable running Docker themselves.Adds: Starting tier and free entry point: the full open-source toolkit — YOLO detection, virtual counters, trajectory analysis, REST API, web UI and the Docker deployment images. |
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Where the pricing makes sense
The company stage and team size where Opendatacam's pricing actually pencils out — and where peers do it cheaper.
The community edition is a free, open-source distribution you run on your own hardware, so the meaningful comparison isn't subscription price — it's total cost of ownership. Against a hosted computer-vision analytics subscription, you trade a recurring fee and per-camera charges for a GPU device, install time and ongoing maintenance. For a single camera experiment that is cheap; for a large multi-site rollout, price the edge hardware and engineering hours before assuming it undercuts a managed
Has Opendatacam's pricing changed?
No plan price for Opendatacam has moved since we began logging in Aug 2026; the pricing page is re-read on every verification pass.
Who should pick Opendatacam?
Pick Opendatacam if you are Traffic engineers working on modal split, turn counts and congestion, Smart city and municipal teams that need privacy-preserving camera data, Urban mobility and computer vision researchers, Developers and makers comfortable with Docker and GPU setup.
Look elsewhere if you are Teams that want a fully managed, cloud-hosted analytics dashboard, Projects that require facial recognition or identity matching, Beginners with no Docker or NVIDIA GPU/CUDA experience, Anyone needing to stream or record the video itself rather than count objects.
Skip it if Skip OpenDataCam if you need a managed cloud dashboard and someone else to run it — it is a self-hosted Docker deployment you install and maintain on your own CUDA-capable hardware.
GeneratedReal-world workflow fit
Concrete scenarios for the personas Opendatacam actually fits — and what changes day-one when you adopt it.
Install OpenDataCam on a Jetson Xavier with the platform-specific install script, point it at an RTSP camera overlooking a junction, draw counters on each approach in the web UI and enable counter chaining.
Outcome: Each crossing is logged with time, object type and direction, and chained crossings show turns through the junction without any video being retained.
Drag a recorded street video into the browser window on a desktop with an NVIDIA GPU, define a count line, and let the default YOLO weights run the analysis.
Outcome: You get a trajectory and count dataset for the clip to compare against manual observation, with the source footage never stored by the tool.
Mount a camera over a dock entrance, run OpenDataCam on a local GPU server via Docker, and pull counts through the REST API into an existing dashboard.
Outcome: Vehicle arrivals and departures are counted from metadata alone, letting you trigger processes like notifications on arrival without cameras leaving the site.
Use cases
- Count pedestrians crossing a street intersection from a USB camera feed
- Analyse vehicle modal split (cars vs bikes vs trucks) on a highway from an IP camera
- Track turn movements at a junction to inform traffic light timing work
- Monitor bicycle lane usage in a park from pre-recorded video
- Build a people counter for a retail space to see footfall patterns over time
- Count forklift or vehicle movements in a warehouse or dock area
- Run a privacy-preserving traffic count for a research or smart-city pilot
- Test detection accuracy on your own footage before committing to a fixed installation
Setup time & first value
How long it actually takes to get something useful out of Opendatacam — broken out by persona, not the marketing-page minute.
With Docker and Docker-Compose already installed and a supported GPU in place, a desktop or Jetson install script typically gets you to a demo video and a working web UI in a single session. Add a few hours if you don't have CUDA 11 / cuDNN 8 or the Nvidia container toolkit set up, and more if you are configuring a field camera, custom YOLO weights and counter definitions for real data.
Switching to or from Opendatacam
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From manual video observation: install via the Docker script, then drop your existing recordings in and define counters instead of tallying by hand.
- →From a cloud computer-vision counting service: replicate your counters in the OpenDataCam web UI and run the same feeds locally so counts stay on your hardware.
- →From a custom OpenCV/DeepSORT counting script: replace your bespoke tracking and counting loop with OpenDataCam's counter chaining and REST API.
- ↗To a commercial analytics platform: export your recorded counts and trajectories and reproduce the counters in the vendor's dashboard if you need managed hosting.
- ↗To a bespoke computer-vision pipeline: reuse OpenDataCam's YOLO weights and recorded metadata as a baseline, then build your own tracker around them.
Resources & guides
- Documentationopendata.cam
Docs · Opendatacam
Full product docs from opendata.cam
- Documentationopendata.cam
Installation · Opendatacam
Full product docs from opendata.cam
- Documentationopendata.cam
Configuration · Opendatacam
Full product docs from opendata.cam
- API Referenceopendata.cam
Api · Opendatacam
Methods, params, types from opendata.cam
- Resourcegithub.com
Opendatacam · Opendatacam
Helpful link from github.com
Tutorials & Learning
YouTube returned 6 videos for “Opendatacam”, and we withheld 6: 6 could not be judged, because “Opendatacam” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Opendatacam.
Official links
What are the best Opendatacam alternatives?
The closest alternatives to Opendatacam we list are Dlib, SimpleCV and Opencv. Ranked by direct product-type match, not category overlap.
| Alternative | Pricing | Starts at | Last verified |
|---|---|---|---|
| Dlib | Free | Free | — |
| SimpleCV | Free | Free | — |
| Opencv | Free | Free | — |
Alternatives to Opendatacam
View all
Tools that pair well with Opendatacam
Common stack mates teams adopt alongside Opendatacam, with the specific reason each pairing earns its keep.
Dlib
Dlib is an open-source C++ machine learning and computer vision toolkit for on-device deep learning.
SimpleCV
Open source Python framework that wraps OpenCV in a beginner-friendly API for classic computer vision prototyping.
Opencv
OpenCV: free, open-source computer vision library for real-time image and video processing
Opendatacam vs its closest rival
Opendatacam's closest head-to-head is with Truleo — If you run a police department and need to connect jail calls, body cameras, and RMS into automated leads and reports, Truleo is built for that—but it costs. If you want to count traffic or track objects privately on your own hardware for free, Opendatacam is the clear pick. These tools target entirely different domains; your choice is dictated by whether you work in law enforcement or need a self-hosted computer vision counter. Verdict generated
Head-to-head comparisons
Opendatacam vs Truleo
If you run a police department and need to connect jail calls, body cameras, and RMS into automated leads and reports, Truleo is built for that—but it costs. If you want to count traffic or track objects privately on your own hardware for free, Opendatacam is the clear pick. These tools target entirely different domains; your choice is dictated by whether you work in law enforcement or need a self-hosted computer vision counter.
GeneratedOpendatacam vs Presto Voice
If you run a large QSR chain and need a drive-thru voice AI that boosts revenue and order accuracy with minimal staff overhead, Presto Voice is the turnkey enterprise choice—backed by recent partnerships (Dairy Queen, April 2026) and proven upselling. If you're a traffic engineer or urban mobility researcher needing a privacy-first, self-hosted object counting tool, Opendatacam is free and powerful but requires technical setup. They are not competitors; the right pick depends entirely on your domain.
GeneratedOpendatacam vs Screenplayiq
If you're a screenwriter or producer seeking data-driven feedback on your script's marketability, ScreenplayIQ is your pick. If you need an open-source, privacy-preserving tool to count and track objects from video feeds (traffic, logistics, etc.), Opendatacam is the clear winner. They serve entirely different domains, so choose based on your primary need.
GeneratedFrequently asked questions
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