giles ad1d7893f8 Integrate fast CUDA kernels for GPU effects pipeline ...

Replace slow scipy.ndimage operations with custom CUDA kernels:
- gpu_rotate: AFFINE_WARP_KERNEL (< 1ms vs 20ms for scipy)
- gpu_blend: BLEND_KERNEL for fast alpha blending
- gpu_brightness/contrast: BRIGHTNESS_CONTRAST_KERNEL
- Add gpu_zoom, gpu_hue_shift, gpu_invert, gpu_ripple

Preserve GPU arrays through pipeline:
- Updated _maybe_to_numpy() to keep CuPy arrays for GPU primitives
- Primitives detect CuPy arrays via __cuda_array_interface__
- No unnecessary CPU round-trips between operations

New jit_compiler.py contains all CUDA kernels with FastGPUOps
class using ping-pong buffer strategy for efficient in-place ops.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

2026-02-04 02:53:46 +00:00

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