real-time object detection and classification
Analyzes video streams in real-time using local YOLO models to identify and classify objects such as people, vehicles, animals, and packages. Processing occurs on local hardware with sub-second latency, eliminating cloud dependencies.
multi-camera video ingestion and management
Accepts and manages video feeds from multiple RTSP/ONVIF compatible cameras, handling stream normalization, buffering, and coordination across unlimited camera sources. Supports diverse camera hardware ecosystems.
historical event search and filtering
Enables searching through historical detection events by object type, timestamp, camera, and confidence level. Allows users to quickly find specific incidents or patterns in their security footage.
rtsp/onvif camera protocol support
Supports standard RTSP and ONVIF protocols for camera communication, enabling compatibility with a wide range of IP cameras from different manufacturers without proprietary integrations.
open-source codebase and customization
Provides complete access to source code, allowing technical users to customize detection models, add features, and modify behavior to suit specific needs. Enables community contributions and transparency.
subscription-free operation
Operates entirely without recurring subscription fees or cloud service dependencies. All functionality is available through one-time setup on user-owned hardware with no ongoing costs.
local video storage and retention management
Stores video recordings locally on user-controlled hardware with configurable retention policies. Eliminates cloud storage dependencies and provides unlimited storage capacity based on available disk space.
event-triggered recording and snapshots
Captures and stores video clips and snapshots when specific detection events occur, such as person detection or vehicle arrival. Reduces storage overhead by recording only relevant moments rather than continuous footage.
+6 more capabilities