v0.1.12

What's new

3D / Bundle Adjustment

• Schur-complement bundle adjustment — dense reduced camera system (k3d.bundle_adjust_schur)
• SE(3) pose graph optimization (k3d.pose_graph_optimize)
• Cheirality-robust BA with pose-only mode and fixed-point gauge (k3d.bundle_adjust)
• IRLS Huber + Cauchy robust loss for BA
• solve_pnp_ransac moved into k3d namespace

RANSAC

• Generic RANSAC framework with NEON+AVX2 scorer and LO-RANSAC
• Homography estimator with rayon parallel scoring
• BA robust-kernel wiring

Segmentation + Depth (kornia_rs.segmentation, kornia_rs.depth)

• COCO RLE ↔ mask encode/decode (NEON-accelerated transpose)
• depth.sample_depth — sample depth under segmentation masks (median or mean, parallel via rayon)
  • 19× speedup on mean path vs pure Python (Jetson Orin, 480×640, 16 masks)

Colormap (kornia_rs.imgproc.apply_colormap, Image.colormap())

• 21 OpenCV-compatible colormaps (viridis, turbo, jet, …)
• NEON-accelerated LUT lookup (vqtbl4q_u8, 16 px/iter)

IO — RVL depth codec (kornia_rs.io)

• encode_image_rvl / decode_image_rvl — lossless Run-Length Variable depth compression
• write_image_rvl / read_image_rvl — file IO
• ~3–5× compression on typical depth frames; zeros (missing depth) pack to a single nibble
• NEON-accelerated delta+zigzag phase on aarch64
• Wire format: RVL1 magic + width/height header

IO — In-memory PNG-16 + PIL-parity (kornia_rs.io, Image)

• encode_image_png_{rgb8,rgba8,gray8,rgb16,rgba16,gray16} — symmetric in-memory PNG encode
• Image class natively holds uint16 (depth maps)
• Image.save(fp) accepts path or file-like (BytesIO, S3 objects)
• Image.encode(format) — in-memory bytes for JPEG and PNG

IO — Zero-copy + WebP/TIFF

• Zero-copy IO path improvements
• WebP and TIFF in encode/save/decode/load

Upgrading

pip install --upgrade kornia-rs