Innomium Vision · Edge YOLO

Person detection
built for crowds.

Sentinel is Innomium's cutting-edge YOLO model — very light, very strong, and tuned for the hardest real-world scenes. From airport concourses to stadium gates, it finds every person with 92% accuracy.

Accuracy
92%
Model size
19 MB
Runtime
Edge / Browser
Sentinel detecting people in a dense crowd at a stadium entrance
Live detection High-density crowd · Stadium entrance

Proven performance

From raw scene to precise detections.

Sentinel maintains high recall in dense, overlapping crowds — the kind of scenes where generic detectors miss people or flood you with false positives.

Input Raw camera frame
Crowd entering a stadium — input frame without detections
Sentinel output Bounding boxes + confidence
Same crowd with Sentinel person detections and confidence scores

Crowd-grade recall

Detects individuals even when partially occluded in dense queues at turnstiles, gates, and terminal walkways.

Confidence you can trust

Scoring-aware post-processing and TTA consensus keep high-confidence detections clean in complex scenes.

Deployment-ready

A compact 19 MB ONNX model suitable for edge cameras, kiosks, and in-browser demos without a GPU farm.

Capabilities

Enterprise vision, without enterprise weight.

Adaptive confidence

Dynamic thresholds respond to scene density — maximizing recall when few people are present and precision when the crowd thickens.

Ultra-light ONNX

~19 MB footprint loads fast and runs on CPU via ONNX Runtime — in the cloud, on edge hardware, or directly in the browser.

TTA consensus

Test-time augmentation cross-validates detections across flipped views to reduce false alarms before they reach your pipeline.

Privacy-first

This demo runs inference entirely in your browser. Frames never leave your device — ideal for regulated environments.

Use cases

Where Sentinel delivers.

Aviation

Airports & transit

Passenger flow, queue monitoring, and gate-level occupancy in high-throughput terminals.

Venues

Stadiums & events

Entry-point crowd analysis, congestion detection, and real-time headcount at scale.

Retail

Stores & malls

Foot traffic analytics and zone density with a model small enough for in-store edge boxes.

Cities

Public spaces

Situational awareness for campuses, plazas, and smart-city pilot deployments.

Interactive demo

Upload your own scene.

Run the production ONNX model in your browser — same pipeline, TTA and adaptive confidence included.

Initializing model...
Detected
Latency
Input
No image loaded
Output
Awaiting detection
Detection JSON
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Deploy Sentinel in your vision stack.

Very light. Very strong. 92% accuracy in crowds. Built by Innomium for airports, venues, and edge deployments that cannot afford to miss a person.