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Roadside AI Model Suite — Detect, Segment, Track

Production‑ready perception for streetside cameras and fleets: multi‑class detection (vehicles, bikes, pedestrians), lane & drivable area segmentation, traffic sign recognition, and multi‑object tracking. Optimized for Jetson/x86/ARM and deployable via SDKs or a gRPC microservice.

Edge targets: Jetson Orin/Xavier/Nano, x86, ARM64. Cloud: AWS/Azure/GCP.

Detection

cars • trucks • buses • bikes • persons

Segmentation

lanes • drivable • shoulders

Signs

Indian & intl. taxonomies

Tracking

ID stability • FPS‑aware

SDKs: C++/Python • Formats: ONNX/TensorRT/OpenVINO.

Model line‑up

Object Detection

Real‑time detection for vehicles, cyclists, pedestrians, animals, cones and more. NMS and class‑wise confidence controls with on‑device calibration.

  • Latencies from 6–18 ms @ 720p (Jetson Orin)*
  • Quantized INT8 variants for edge
  • Batch & streaming inference

Lanes & Drivable Area

Semantic/instance segmentation for lanes, drivable area and shoulders; robust in rain/low‑light with temporal smoothing.

  • HDR‑friendly pre/post pipeline
  • Polyline export & lane width estimates
  • Bird’s‑eye projection utilities

Traffic Sign Recognition

Classifier + detector combo with Indian and international taxonomies; supports occlusion and motion blur cases.

  • Configurable label maps
  • Confidence and visibility scoring
  • Easy integration with GIS layers

Multi‑Object Tracking (MOT)

ID‑stable tracking with re‑identification features for intersection analytics and dwell/time‑to‑collision studies.

  • Kalman + deep appearance models
  • Frame‑rate adaptive tuning
  • Track export: CSV/JSON

* Indicative numbers; exact latency depends on resolution, model variant and target device.

Data & annotation services

Roadside datasets

Curated scenes across day/night, weather, sensor mounts and geographies; includes manifests and licenses for research/commercial/OEM.

  • Balanced classes & hard cases
  • COCO/JSON/CSV exports
  • Sampling manifests & datasheets

Annotation specs

Boxes, polygons, lane polylines, sign classes; QA with inter‑annotator agreement and audit trails.

  • Bandpass IR data
  • Covers all form of road and vehicle
  • Day and Night scenarios

Ready to evaluate Roadside AI?

Tell us your camera setup and latency targets; we’ll propose the right variant and integration path.