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[ITEP-73288] Computer vision pipeline API design document #494
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Defines API workflows and implementation considerations for customer domain experts deploying vision analytics with SceneScape integration.
Keep only the vision pipeline API design document changes in this branch.
… into feature/vision-pipeline-api-design-doc
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saratpoluri
reviewed
Oct 16, 2025
saratpoluri
reviewed
Oct 16, 2025
saratpoluri
reviewed
Oct 16, 2025
saratpoluri
reviewed
Oct 16, 2025
saratpoluri
reviewed
Oct 16, 2025
saratpoluri
reviewed
Oct 16, 2025
saratpoluri
reviewed
Oct 16, 2025
saratpoluri
reviewed
Oct 16, 2025
saratpoluri
reviewed
Oct 16, 2025
saratpoluri
reviewed
Oct 16, 2025
saratpoluri
reviewed
Oct 16, 2025
saratpoluri
reviewed
Oct 16, 2025
- Eliminate duplicate reference in MQTT Publishing bullet point - Keep detailed explanation in dedicated Topic Generation section - Improve document clarity and reduce redundancy
- Standardize sequence diagrams to use 'User' consistently - Add robust camera error handling with persistent reconnection capabilities - Add comprehensive system monitoring API for observability - Add multimodal input support section with audio, LiDAR, and radar - Add security considerations note referencing separate hardening guide - Improve document structure and readability for target audience
vibhubithar
reviewed
Oct 20, 2025
vibhubithar
reviewed
Oct 20, 2025
…ilience - Create core operating principles section - Strengthen separation of concerns language throughout Camera and Pipeline APIs - Add JSON configuration examples for a couple of camera types - Fix sequence diagram terminology and ensure consistency Incorporate review feedback from Vibhu and Sarat, emphasizing the importance of resilience in production environments and modular system design for operational manageability.
Specify that a stage operates on an array of outputs from a single previous stage, not outputs from multiple different stages, removing ambiguity about pipeline architecture.
Specify that pipelines must support configuring MQTT broker connection details including host, port, credentials, TLS settings, and optional topic namespace prefix via the REST API.
…e of the note container.
…ne-api-design-doc
… it breaks GitHub rendering of the diagrams. Will look for cross-support with Sphynx using some other method.
… feedback from Tomasz D.
…tion - Move misplaced items between Requirements and Considerations - Strengthen requirement language (should → must) for mandatory items - Reorganize Time Coordination, Performance Management, and Latency sections - Clarify system resource limits and frame drop strategy requirements - Separate actionable requirements from implementation guidance
…ion results" to "send pipeline results"
tdorauintc
reviewed
Oct 27, 2025
…mposition per feedback from Tomasz D. - Add Advanced Pipeline Composition section with DAG architecture - Implement comprehensive DAG syntax with sequential, parallel, and branching patterns - Add visual Mermaid diagram showing metadata convergence architecture - Include practical JSON metadata examples with model tracking - Add hardware targeting syntax (@gpu, @NPU, @cpu) for per-stage optimization - Implement stage aliases (vehicle, vattrib, lpd, lpr, reid) with critical importance warnings - Add comprehensive model metadata tracking (name, version, hash) for reproducibility - Include complex DAG examples for traffic intersection and video analysis workflows - Add DAG validation, execution order, and performance optimization details - Update document date and clarify scope to include supporting functionality
saratpoluri
reviewed
Oct 28, 2025
…e, clarify model info is available via separate endpoint, and combine timestamp/camera ID bullets for clarity.
…ss to model info per stage, without specifying output structure and without requiring this information in pipeline metadata output
tdorauintc
approved these changes
Nov 4, 2025
jdanieck
approved these changes
Nov 7, 2025
saratpoluri
approved these changes
Nov 10, 2025
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📝 Description
This PR introduces a comprehensive design document for the Vision Pipeline API, targeting domain experts who need to deploy computer vision capabilities without deep technical knowledge. The document defines a simple, API-first approach for connecting cameras, configuring composable analytics pipelines, and accessing object detection metadata.
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