Part 8/17:
Transitioning from prototypes to large-scale deployment necessitates robust architecture. The speaker emphasizes that beyond algorithm development, organizations must establish scalable, flexible pipelines, including:
Data Ingestion and Processing: Abstracting hardware differences, handling diverse camera types, resolutions, and conditions.
Model Deployment & Inference: Choosing models optimized for specific hardware and use cases, supporting easy updates to model weights without disrupting entire systems.
Feedback Loops: Incorporating user or system feedback into retraining and fine-tuning models to improve accuracy over time.
Building Scalable Computer Vision Solutions
Architecting the Pipeline
A high-level architecture is described: