Variopinta 0.5.0

Variopinta 0.5.0

• Support native grayscale uint8 images in HW and HWC1 layouts across the
  transform catalog, preserving array rank and returning owned, contiguous output.
• Accept scalar and one-element normalization statistics and image fills that
  broadcast to grayscale or RGB. Active three-element values require RGB;
  grayscale normalization requires compatible values such as mean=0.5, std=0.5.
• Add Image(decode_mode="gray") for encoded-buffer and path inputs, grayscale
  JPEG/PNG outputs, and contiguous single-channel CHW tensor output.
• Upgrade explain() to schema 5 with per-target channel alternatives and
  channel-aware execution reporting. Consumers of schema 4 must update.
• Add a Fashion-MNIST notebook with grayscale augmentation previews and PyTorch
  classifier training on CPU or CUDA.
• Add an Oxford-IIIT Pet notebook with shared image/mask augmentation, keyed
  replay, and segmentation training with PyTorch Lightning.