Deep-Framework

Deep-Framework provides a distributed, edge-oriented framework for real-time video stream analysis using deep learning to enable low-latency, high-throughput inference on edge architectures.

Key Features:

• Distributed and scalable processing: Enables distributed, scalable processing of concurrent video streams for real-time analytics.
• Edge-oriented deployment: Supports deployment on edge architectures to minimize latency and support high throughput.
• Docker-based multi-stream architecture: Implements a Docker-based multi-stream architecture for containerized multi-stream processing.
• Cluster configuration and service orchestration: Manages cluster configuration and service orchestration for distributed deployments.
• GPU resource allocation: Manages GPU resource allocation for computationally intensive deep learning inference.
• Deep learning framework integration: Provides Python interfaces to integrate models from popular deep learning frameworks.
• High-level APIs (HTTP, WebRTC): Exposes high-level HTTP and WebRTC APIs for streaming processed video to clients, including web browsers.
• Support for computationally intensive algorithms: Supports execution of deep learning algorithms for image and video analytics.

Scientific Applications:

• Surveillance systems: Enables low-latency video analytics for surveillance and monitoring applications.
• Autonomous vehicles: Supports in situ real-time inference for perception and decision-support in autonomous vehicles.
• Remote sensing: Processes streamed imagery for remote sensing applications where on-edge inference reduces data transfer.
• On-edge analytics to reduce centralization: Enables on-edge processing to reduce the need for transmission to centralized servers and minimize delays.

Methodology:

Implements a Docker-based multi-stream architecture with cluster configuration, service orchestration, and GPU resource allocation; integrates deep learning models via Python interfaces from popular frameworks and exposes HTTP and WebRTC APIs for streaming processed video.