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Targeted cutout extraction and single-item cloud identification - #272

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Monster0506 merged 1 commit into
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feat/257-targeted-cutout-identification
Sep 20, 2026
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Monster0506 merged 1 commit into
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feat/257-targeted-cutout-identification

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Closes #257

Summary

  • Implemented client-side canvas cutout extraction (extractCutout / getCutoutBlob in wwwroot/js/camera-scanner.js) with polygon path clipping and tight bounding box cropping.
  • Added IdentifyCutoutAsync to IPhysicalAssetDetectionService and NvidiaAssetDetectionService with specialized SingleItemPrompt focused on isolated cutouts (brand, model/flavor/edition, condition tags, category).
  • Wired cutout extraction into LiveCameraScanner.razor: clicking 'Accept item' generates the transparent PNG cutout and passes CutoutBytes to the review pipeline.
  • Connected single-item AI identification in PhysicalAssets.razor: automatically queries the vision model on accepted cutouts to populate Brand, Model, Label, and Tags into inventory review and AI valuation.
  • Added unit tests for cutout extraction in tests/js/camera-scanner.test.mjs and single-item identification in tests/MoneyMirror.Tests/PhysicalAssets/NvidiaAssetDetectionServiceTests.cs.

@Monster0506
Monster0506 merged commit 5b535c4 into main Sep 20, 2026
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@Monster0506

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Force nudge for CI: pushed 94d917a (auto-estimate value change). Local verification: dotnet test 232/232 passed, dotnet format --verify-no-changes clean, live-verified end-to-end against the running app (photo upload -> auto value estimate, no manual button).

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Targeted cutout extraction and single-item cloud identification

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