# opendatacam/opendatacam

An open source tool to quantify the world

Repository: https://github.com/opendatacam/opendatacam
Canonical: https://ross.abutalabs.com/products/opendatacam
Homepage: https://opendata.cam
Language: JavaScript
License: MIT
License Family: permissive
Topics: yolo, camera, iot, smart-city, computer-vision, dataviz, jetson, darknet, jetson-nano, jetson-tx2, jetson-xavier
Last push: 2026-04-23T01:52:02+00:00

## Health v2 (maintenance only)
Score: 58/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 78, release rhythm 8, longevity 100
- inputs: {"age_days": 3291, "days_push": 133, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1725, forks 300 (observed 2026-08-28T04:05:28.146598+00:00)

## What it is
OpenDataCam is an open-source computer vision application that detects and tracks moving objects in camera feeds or video files using YOLO/Darknet, counting them via user-defined virtual counters. It runs self-contained on NVIDIA GPUs and Jetson edge devices, exposing a web UI and REST API while keeping all data local.

## Use cases
- count cars and pedestrians from a camera for traffic studies
- measure modal split and turn counts at intersections
- analyze pedestrian trajectories in a public square
- run object counting on a Jetson Nano at the edge
- analyze pre-recorded video files for moving object counts
- build a smart city sensor with privacy-preserving on-device analytics

## When to choose
- you need to count or track moving objects (vehicles, bikes, pedestrians) from video without saving footage
- you want a self-contained, privacy-friendly edge deployment on NVIDIA Jetson or GPU servers
- you need an API-driven counting tool with a ready-made web UI and trajectory analysis

## When to avoid
- you need object detection on CPU-only hardware or non-NVIDIA GPUs
- you need to store or analyze the video imagery itself, since OpenDataCam discards visual data
- you need a general-purpose video surveillance or recording system

## Facets
- artifact type: application
- maturity: active
- function: computer-vision, video-processing, analytics, data-visualization, api-framework
- domain: computer-vision, iot, analytics, machine-learning
- platform: self-hosted
- tags: yolo, darknet, jetson, object-tracking, edge-computing, traffic-counting, smart-city, video-analytics, privacy-preserving, traffic-analysis, docker, linux, gpu, web-server

## Member repositories
- opendatacam/opendatacam (main) score 58

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:28.146598+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:33:52.103629+00:00, confidence not recorded.
  - readme: https://github.com/opendatacam/opendatacam (fetched 2026-08-28T04:05:28.146598+00:00, sha 4646c8a1fbc1)
  - homepage: https://opendata.cam (fetched 2026-08-29T11:09:36.044001+00:00, sha 89912a4e1d4a)
  - site_page: https://opendata.cam/features (fetched 2026-08-29T11:09:36.046733+00:00, sha 55b70443aad6)
  - site_page: https://opendata.cam/docs (fetched 2026-08-29T11:09:36.048575+00:00, sha df606e29e1f9)
- Data as of 2026-08-30T08:39:29.467469+00:00.