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WIMF roadmap

WIM2 codec correctness and native CPU performance come first. The next major goal is adoption: making the decoder straightforward for other applications to embed without depending on Python.

1. Integration foundation

  • Freeze the implemented WIM2 revision-2 base-container specification.
  • Publish initial lossless decoder vectors for every WIM2 tile mode.
  • Expand vectors across grayscale, RGBA, 10/16-bit, odd edge tiles, ROI, metadata, corruption rejection, and deterministic threading.
  • Add HIST, AROT, protected-history, bounded-repair, and unrecoverable-damage vectors.
  • Cover the single-layer boundary, cancellation, and malformed-input limits; unsupported progressive layer counts are reserved and rejected.
  • Add an experimental versioned C ABI with owned buffers and structured errors.
  • Freeze ABI v1 fields, enums, ownership, cleanup, threading, structured errors, exception containment, and version negotiation.
  • Add portable CMake build, install, and find_package support.
  • Add the C-ABI-only wimf-native PGM/PPM process bridge.
  • Document ABI resource limits, thread safety, ownership, errors, and decoder safety.
  • Publish standalone signed C/C++ development archives (SignPath policy and dormant workflow are ready; Foundation acceptance is external).
  • Expose portable progress/cancellation callbacks through both C++ and C APIs.
  • Package native SDK archives with WIMF/Zstandard licenses and distribution guidance.

2. Application support

  • Pillow open/save plugin for grayscale, RGB, and RGBA WIM2 images.
  • Optional ImageMagick 7 decode coder backed by the C ABI.
  • Upstream-oriented FFmpeg/libavcodec WIM2 decoder source kit.
  • Linux MIME registration and thumbnail integration.
  • Native Windows Explorer thumbnail and preview-pane providers.
  • GraphicsMagick-specific coder and upstream FFmpeg registration.
  • macOS Quick Look support.

3. Web and languages

  • Build and run the single-threaded core conformance suite as WebAssembly.
  • JavaScript/WASM package.
  • Rust bindings after the C ABI stabilizes.
  • Add other language bindings when real integration requests justify them.

4. Adoption evidence

  • Maintain a public benchmark corpus against PNG, WebP, AVIF, JPEG, and JPEG XL.
  • Publish reproducible throughput, memory, compression, corruption, platform, and compiler measurements.
  • Keep fuzzing, sanitizers, malformed-input tests, and cross-platform decoder conformance blocking for releases.
  • Provide minimal examples and an upstreaming checklist for each integration.

5. Performance optimization

  • AVX2 (x86_64)
    • Benchmark targets: 2.5-3× speedup on Intel Haswell+ / AMD Zen+
    • Measured baseline: i5-4460 (Haswell, scalar): 26.7 MP/s (Fast preset), 9.1 MP/s (Wavelet Balanced), 3.4 MP/s (Extreme Q2)
    • Implementation deferred until profiling confirms real-world gain
  • NEON (ARMv8+)
    • Benchmark targets: 2.5-3× speedup on ARMv8+ (Apple M1/M2, Raspberry Pi 4/5, Android, ChromeOS)
    • Minimum acceptable Raspberry Pi 5 target: 25+ MP/s (Fast), 10+ MP/s (Wavelet Balanced), 5+ MP/s (Extreme)
  • AVX-512
    • Experimental; deferred until AVX2/NEON paths are stable and hardware support is widespread enough to justify the maintenance cost.
    • Thermal and performance-regression risks documented.

6. Quality-of-life improvements

  • Accept case-insensitive codec names in the Python API: auto, Auto, Auto (hybrid) and similar variants should map to the same internal path.
  • Implement ROI decode conformance test (currently returns 'encode' error).
  • Add --file or --image flag to the CLI to target a single image rather than scanning an entire directory.
  • Expose progress feedback for long-running encodes (especially Extreme preset).
  • Publish recommended configuration presets in the README based on real user benchmarks:
    • quality=5, preset=Balanced, codec=auto for general daily use.
    • quality=5, preset=Balanced, codec=wavelet for web/game delivery.
    • quality=2, preset=Extreme, codec=auto for archival storage.
    • quality=4, preset=Fast, codec=auto for high-speed batch work.
    • lossless=True, preset=Balanced, codec=auto for visually lossless quality.
  • Publish standalone wimf-native CLI binary for systems without Python.

7. Platform validation

  • Complete and publish benchmarks for:
    • x86_64 scalar baseline (completed: i5-4460, 2014)
    • x86_64 AVX2 on Kaby Lake or newer
    • ARM NEON on Apple M1/M2
    • ARM NEON on Raspberry Pi 5
  • Maintain decoder conformance across all supported platforms.
  • Document minimal hardware requirements and expected performance tiers.

Base16, Base32, and Base64 transport support is implemented. These encodings help move WIMF through text-only systems but are not compression formats.

GPU acceleration, plugins inside the codec, and another container redesign remain deferred until profiling or adopter demand identifies a concrete need.

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