Graph

Use Graph when a single linear pipeline is no longer enough. In real deployments, you often need:

• One input, multiple consumers: run inference, recording, and telemetry from the same stream without duplicating ingest.
• Multi-stream coordination: synchronize or merge outputs from multiple cameras/sources before downstream decisions.
• Mixed workloads: combine media-heavy pipeline stages with lightweight in-process logic (routing, filtering, policy checks).
• Selective branching: route only specific frames/events to expensive stages (for example secondary models).
• Operational isolation: keep custom control logic in stage nodes while leaving media/runtime-heavy parts in pipeline nodes.

graph::Graph provides this as a DAG (Directed Acyclic Graph): deterministic forward flow, explicit fan-out/join, and hybrid execution.

How it works

1. Define nodes and edges in Graph.
2. Build with GraphSession.
3. Run with GraphRun.

You can mix:

• PipelineNode for regular NEAT Node/NodeGroup pipeline fragments.
• StageNode for in-process custom logic.

Core objects

• Graph: DAG container with typed ports and edges.
• GraphSession: compiles the DAG into runnable segments.
• GraphRun: runtime handle for push/pull and stats.
• Compiler: partitions and wires pipeline/stage backends.

Key node families

• PipelineNode
• StageNode
• StreamScheduler
• JoinBundle

See also

• Node
• Pipeline
• Session

Tutorials

• Graph Basics
• Graph Model Hybrid
• Graph Multistream