23 lines
1,011 B
Markdown
23 lines
1,011 B
Markdown
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# AIFotoONLUS (.NET) — scaffold
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This workspace contains the initial scaffold for migrating the YOLO-based number recognition Python script to .NET 10.
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Projects:
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- `AIFotoONLUS.Core` — core inference library (OpenCvSharp)
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- `AIFotoONLUS.Console` — console batch runner
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- `AIFotoONLUS.WPF` — simple WPF demo frontend
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Quick build & run (Windows):
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1. Ensure .NET 10 SDK is installed.
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2. From `src` run:
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- `dotnet restore`
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- `dotnet build`
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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.
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Console example:
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dotnet run --project src\AIFotoONLUS.Console -- -d "..\images\onlus" -c result.csv
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Notes:
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- Core engine currently loads Darknet models and scaffolds the detection/recognition pipeline.
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- Parsing of network outputs (YOLO postprocessing) and recognition logic will be implemented next.
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- WPF app is a minimal demo (code-behind). We'll replace with MVVM as we iterate.
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