65b411b23d
- Add CLAUDE.md with project overview, tech stack, build commands, architecture description, coding standards, and sample images section - Add full directory structure: src/, docs/, tests/, import/ - Add CMakeLists.txt with C++20, OpenCV/LibRaw/Qt6 dependencies, converter_core static lib, optional GUI, and GTest tests - Add architecture documentation: ARCHITECTURE.md, PIPELINE.md, MODULES.md - Add source skeletons for all pipeline stages: RawLoader, Preprocessor, NegativeDetector, Inverter, ColorCorrector, CropProcessor, OutputWriter, Pipeline, MainWindow, CliRunner, main.cpp - Add initial test stubs for pipeline and rawloader - Add sample ARW files in import/ for integration testing Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
90 lines
2.9 KiB
Markdown
90 lines
2.9 KiB
Markdown
# CLAUDE.md
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This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
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## Project
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C++ desktop app converting digitized analog film negatives (35mm, 120mm) to digital positives. Supports JPG/PNG and RAW input (CR2/NEF/ARW/DNG), outputs PNG/JPG with inversion, C41/B&W correction, auto-crop, and batch processing. Cross-platform: Windows/Linux/macOS.
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## Tech Stack
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- **Language:** C++20
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- **Image processing:** OpenCV 4.10+ and LibRaw 0.21+ (RAW demosaicing)
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- **GUI:** Qt 6.8 LTS (LGPLv3)
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- **Build:** CMake 3.20+, vcpkg (Windows), Ninja
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- **CLI:** Optional batch mode without GUI
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## Build Commands
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```bash
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# Linux (Ubuntu/Debian)
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sudo apt install libopencv-dev libqt6widgets6 libraw-dev cmake ninja-build
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cmake -B build -G Ninja -DCMAKE_BUILD_TYPE=Release
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cmake --build build
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# Windows (vcpkg)
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vcpkg install opencv[contrib] libraw qt6-base:x64-windows
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cmake -B build -G Ninja -DCMAKE_TOOLCHAIN_FILE=vcpkg.cmake
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cmake --build build
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# macOS (Homebrew)
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brew install opencv libraw qt@6 cmake ninja
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cmake -B build -G Ninja
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cmake --build build
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```
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## Architecture
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Processing pipeline:
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```
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Input → Loader → Preprocess → Detect → Invert → Color Correction → Post-Process → Output
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```
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**Core data structure:**
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```cpp
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struct ImageData {
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cv::Mat rgb; // Demosaiced 16-bit
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std::string make; // "Canon", "Nikon"
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float exposure; // WB/EXIF data
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};
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```
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**Pipeline stages:**
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1. **Loader** (`src/converter/rawloader`): LibRaw for RAW→RGB16, OpenCV for JPG/PNG
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2. **Preprocess**: RAW→RGB16 conversion, deskew
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3. **Detect** (`src/converter/negative`): Negative vs. positive via histogram analysis and orange color masking
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4. **Invert**: `cv::bitwise_not()` + film-specific color matrix
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5. **Color**: C41 orange cast removal, auto white balance from EXIF
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6. **Post** (`src/converter/crop`): Levels, sharpening, dust removal, auto frame detection
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7. **Output**: 16-bit TIFF and 8-bit PNG
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Error handling uses `std::expected<ImageData, Error>` throughout.
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## Coding Standards
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- Always call `LibRaw::recycle()` after use
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- Qt file dialogs: `QFileDialog::getOpenFileNames("RAW (*.cr2 *.nef *.dng)")`
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- Tests use RAW golden files with pixel diff tolerance <1%
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- Do not exceed 4GB in-memory RAW data
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- Do not use lossy demosaicing (LibRaw default is lossless)
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- Always log RAW metadata
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## Sample Images
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The `import/` directory contains example RAW files for manual testing and development:
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| File | Format | Description |
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|------|--------|-------------|
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| `import/DSC09246.ARW` | Sony ARW | Example negative for conversion testing |
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| `import/unbenannt.ARW` | Sony ARW | Example negative for conversion testing |
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Use these files to test the full pipeline end-to-end without needing external test data.
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## License Compliance
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README.md must include:
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- Qt LGPLv3 attribution and source download link: https://www.qt.io/download-open-source
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- Instructions for re-linking Qt DLLs
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- LibRaw CDDL attribution: https://www.libraw.org
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