# AIFotoONLUS (.NET) — scaffold

This workspace contains the initial scaffold for migrating the YOLO-based number recognition Python script to .NET 10.

Projects:
- `AIFotoONLUS.Core` — core inference library (OpenCvSharp)
- `AIFotoONLUS.Console` — console batch runner
- `AIFotoONLUS.WPF` — simple WPF demo frontend

Quick build & run (Windows):
1. Ensure .NET 10 SDK is installed.
2. From `src` run:
   - `dotnet restore`
   - `dotnet build`
3. Copy the `models/` folder (contains detection/recognition .cfg and .weights) to the `src` output folder or run the apps from repository root so `models/` is accessible.

Console example:
  dotnet run --project src\AIFotoONLUS.Console -- -d "..\images\onlus" -c result.csv

Notes:
- Core engine currently loads Darknet models and scaffolds the detection/recognition pipeline.
- Parsing of network outputs (YOLO postprocessing) and recognition logic will be implemented next.
- WPF app is a minimal demo (code-behind). We'll replace with MVVM as we iterate.