Akiba So
99b98b96b0
Make on-device OCR a pluggable local service so it runs locally on every platform (not just Windows), aimed at GoodNotes/Notability-class handwriting on low-power hardware (e.g. Zen2 APU, CPU/iGPU). - New OcrBackend abstraction (lib/services/ocr/): selector prefers an embedded ONNX recognition backend, falling back to the OS-native backend (Windows WinRT), and to a clean no-op when neither is available. - OnnxRecognitionBackend: flutter_onnxruntime session from a bundled asset, dart:ui preprocessing (resize to 48px, CHW float32, normalized), pure-Dart CTC greedy decode. Fully guarded — absent model/dict is a no-op; never throws. - ocr_engine.dart kept as a thin facade (recognizeImage) delegating to the selector, so ocr_service.dart is unchanged. - CtcDecoder unit-tested (6 tests). flutter analyze clean; all tests pass. - Model is not committed; tool/fetch_ocr_model.sh + assets/models/ocr/README.md document fetching PP-OCRv4 rec + dict on the dev machine. - CI: forward HTTPS_PROXY to the Windows build so CMake can fetch the ONNX Runtime native lib behind the GFW; README documents the system-install alternative. PP-OCR geometry/blank assumptions documented for on-device tuning. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
15 lines
487 B
Dart
15 lines
487 B
Dart
import 'dart:typed_data';
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import 'ocr/ocr_backends.dart';
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/// Local OCR entry point. Delegates to a pluggable backend (embedded ONNX
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/// recognition when a model is bundled, otherwise the native platform OCR).
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///
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/// The static API is kept for back-compat with [OcrService].
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class OcrEngine {
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/// Recognize text from a PNG image. Returns null when unavailable or empty.
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static Future<String?> recognizeImage(Uint8List pngBytes) {
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return OcrBackends.recognize(pngBytes);
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}
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}
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