dtourolle
84fade99ec
docs/ had 26 developer documents flat beside the manual, and the two audiences are very differently sized: most readers want the manual and the gesture reference, a few want the register, the designs and the measurements. The manual and gestures.md stay at the top; everything for someone changing the code moves to docs/dev/, and the two documents that name their own successors — the v0.1 milestone and the UI-refinement plan — go to docs/dev/archive/ rather than being deleted, since both are still cited. docs/README.md is the index, users first. Every reference follows: code comments, Cargo manifests, the workflows, the pre-commit hook, the bench and traceability tools (which locate the repo root by docs/dev/requirements.md now), packaging, the Docker READMEs, CLAUDE.md, CONTRIBUTING.md and the README. The matrix links one level deeper and is regenerated. Links out of the moved documents into the tree gain a level; a link checker over every Markdown file finds none broken.
39 lines
1.3 KiB
TOML
39 lines
1.3 KiB
TOML
[package]
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name = "dr-pano"
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version.workspace = true
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edition.workspace = true
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rust-version.workspace = true
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license.workspace = true
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# Guards against a Git LFS pointer being embedded in place of the weights.
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build = "build.rs"
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[dependencies]
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thiserror.workspace = true
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log.workspace = true
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# Inference for the learned keypoint detector, on the same footing as
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# `dr-segment`: `ort` is the API, `dr-inference-engine` decides what runs
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# it (docs/dev/inference.md), and both are optional so that the geometry —
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# matching, the rotation solve, the projections — is a dependency-free crate
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# that tests without a model.
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ort = { workspace = true, optional = true }
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dr-inference-engine = { workspace = true, optional = true }
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ndarray = { workspace = true, optional = true }
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[dev-dependencies]
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# The example aligns real frames from their embedded previews.
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dr-decode.workspace = true
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dr-types.workspace = true
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env_logger.workspace = true
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[features]
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default = ["xfeat", "embedded-model"]
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# The XFeat detector (FR-MRG-8) and the MI-GAN filler (FR-MRG-4). Off, the
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# crate has no model and no runtime — a build that only wants the geometry.
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xfeat = ["dep:ort", "dep:dr-inference-engine", "dep:ndarray"]
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# Compile the weights into the binary, for the same reason `dr-segment` does:
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# Android hands the app no path to read a model from (ARCH §6.9).
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embedded-model = ["xfeat"]
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