Case study · 2025

Insidious AI — Real-Time Vision Desktop App

C#/.NET desktop app running real-time object detection on screen frames with DirectML acceleration and PS5/Xbox controller input.

  • C#
  • .NET
  • WPF
  • ONNX Runtime
  • DirectML
  • Computer Vision
Insidious AI system design overview

System design

 Screen capture (frame loop)
        │
        ▼
 Pre-process (crop · resize · normalise)
        │
        ▼
 ONNX model  ──► DirectML (GPU)  /  CPU fallback
        │
        ▼
 Post-process (boxes · confidence · target selection)
        │
        ▼
 Input layer ── mouse  |  PS5 DualSense / Xbox controller
        ▲
 WPF UI: settings, model selection, overlays

What I changed

  • Complete UI redesign of the WPF application
  • CPU-first model initialisation for reliable start-up on machines without a compatible GPU
  • Native controller support (PS5 DualSense and Xbox), not just mouse input
  • Built on the DirectML fork of Aimmy for faster inference; credit to the original authors

Engineering takeaway

Real-time inference is a latency budget: every stage of capture → model → input has to fit inside a frame.

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