senior-computer-vision

Yes, you can integrate multiple computer vision frameworks like Ultralytics, Detectron2, and MMDetection. The skill provides reference configurations and automation tooling to streamline framework integration for object detection and segmentation pipelines.

Yes, this skill supports both instance and semantic segmentation tasks. It builds production-grade computer vision pipelines using CNN and Vision Transformer architectures, covering multi-task CV workflows end-to-end.

The best way to optimize computer vision models for edge environments is through model export and optimization workflows. This skill applies ONNX and TensorRT configurations to deploy detection and segmentation models efficiently on edge devices.

Yes, you can use PyTorch and ONNX runtime together. The skill lists torch and onnxruntime as dependencies, enabling model training in PyTorch and subsequent export to ONNX for cross-platform deployment.

Build a multi-task computer vision pipeline by selecting CNN or Vision Transformer architectures for detection and segmentation. The skill provides automation scripts to bootstrap and configure production-ready CV systems with these architectures.