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SkillsMP has collected 5 skills from albumentations-team/albucore. Open a skill to review its source and details.
Showing 5 of 5 collected skills.
Albucore image processing conventions - shapes (H,W,C), dtypes (uint8/float32), benchmark-driven backend routing (OpenCV, NumPy, Torch CPU, LUT, NumKong), tests, and lockfile discipline. Use when implementing or modifying albucore modules, writing tests, or…
Running Albucore micro-benchmarks under benchmarks/, synthetic router timings, and comparing PyPI releases with uv --no-project. Use when adding benchmarks, comparing performance across versions, or documenting benchmark workflow.
Systematic performance audit for Albucore runtime code. Use whenever implementing, reviewing, profiling, or optimizing atomic image operations, backend routing, reductions, label maps, LUTs, random generation, dtype conversions, allocation-heavy paths, batch…
Optimize or review eager CPU-only Albucore PyTorch runtime paths with benchmark-backed decisions. Use when adding or changing Torch CPU kernels, Tensor/NumPy bridges, Torch backend routing, tensor layouts, allocations, threading, profiling, memory-format…
Albucore star-exported API (__all__), routers vs albucore.functions shims, and dependents such as Albumentations. Use when changing exports, documenting API, or deciding what belongs in package __all__.