edge-cv-pipeline

What problem does it solve?

This Skill enables the creation and deployment of efficient computer vision pipelines on resource-constrained edge devices like Jetson and Raspberry Pi, ensuring real-time performance.

Core Features & Use Cases

• Hardware-Aware Design: Prioritizes performance and resource constraints specific to edge hardware.
• End-to-End Pipeline Construction: Covers capture, preprocessing, inference, postprocessing, and publishing.
• Model Optimization Guidance: Provides decision trees for selecting optimal model formats (TFLite, ONNX, TensorRT).
• Use Case: Build a real-time object detection system for a security camera on a Raspberry Pi, optimizing the pipeline to run smoothly on the device's limited processing power.

Quick Start

Build a computer vision pipeline for a Jetson Nano using a TFLite model and publishing results via MQTT.