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DarkRoom/core/dr-pano/Cargo.toml
T
dtourolle 231b4a54ab dr-pano: the geometry, from features to cameras
A new crate holding the CPU half of a merge (FR-MRG-10): the grayscale
proxy with orientation, the XFeat decoder ported step for step from the
reference detectAndCompute, mutual-nearest-neighbour matching, a robust
pairwise homography with the focal length read off it, a hand-rolled
Levenberg–Marquardt bundle adjustment over every rotation and the focal,
the three output projections, and align(), which chains it all and names
the frames it could not place rather than guessing (FR-MRG-5).

Dependency-free without the xfeat feature — linalg.rs says why the dense
algebra is hand-rolled — and tested on synthetic sweeps whose answer is
known exactly. The noise test records the single-row degeneracy: one
pixel of noise is a tenth of a percent of focal, which is a uniform
stretch of the sweep, not a misalignment.
2026-09-19 15:24:12 +02:00

38 lines
1.3 KiB
TOML

[package]
name = "dr-pano"
version.workspace = true
edition.workspace = true
rust-version.workspace = true
license.workspace = true
# Guards against a Git LFS pointer being embedded in place of the weights.
build = "build.rs"
[dependencies]
thiserror.workspace = true
log.workspace = true
# Inference for the learned keypoint detector, on the same footing as
# `dr-segment`: `ort` is the API, tract is the engine, and both are optional
# so that the geometry — matching, the rotation solve, the projections — is a
# dependency-free crate that tests without a model.
ort = { workspace = true, optional = true }
ort-tract = { workspace = true, optional = true }
ndarray = { workspace = true, optional = true }
[dev-dependencies]
# The example aligns real frames from their embedded previews.
dr-decode.workspace = true
dr-types.workspace = true
env_logger.workspace = true
[features]
default = ["xfeat", "embedded-model"]
# The XFeat detector (FR-MRG-8). Off, the crate has no model and no runtime,
# and `Detector` has no implementation — a build that only wants the geometry.
xfeat = ["dep:ort", "dep:ort-tract", "dep:ndarray"]
# Compile the weights into the binary, for the same reason `dr-segment` does:
# Android hands the app no path to read a model from (ARCH §6.9).
embedded-model = ["xfeat"]