[package]
name = "dr-segment"
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. `ort` is the API; **what runs it is `dr-inference-engine`'s
# business** — tract, or an ONNX Runtime the app found on disk, on whichever
# provider the device has (docs/dev/inference.md). This crate never names either.
ort = { workspace = true, optional = true }
dr-inference-engine = { workspace = true, optional = true }
ndarray = { workspace = true, optional = true }

[dev-dependencies]
# The example reads an ordinary JPEG, because the thing worth looking at is
# whether detections land on a real photograph. Pure Rust, and already in the
# tree for embedded previews.
zune-jpeg.workspace = true
env_logger.workspace = true
# The probe example drives `ort` directly to print the raw load error, and
# asks the engine for a runtime by name rather than naming one itself.
dr-inference-engine.workspace = true

[features]
# On by default: a local adjustment that cannot select a subject is half the
# feature, and the whole point of the tract backend is that enabling this costs
# no C dependency on any platform.
default = ["semantic", "embedded-model"]

# Arm B — the ONNX runtime and the instance decoder.
#
# Separable because the watershed half is genuinely independent of it: with
# this off, `dr-segment` is a pure-CPU graph algorithm crate with no model to
# carry, which is what the headless hierarchy tests want.
semantic = ["dep:ort", "dep:dr-inference-engine", "dep:ndarray"]

# Compile the weights into the binary.
#
# Separate from `semantic` because the two answer different questions. Android
# hands the app no filesystem path to read a model from (ARCH §6.9), so there
# it must be embedded; a desktop packager pointing at a system model directory,
# or a test that only needs the decoder, wants the runtime without the 11 MB.
embedded-model = ["semantic"]

# Compile the *scene* model in too, and off by default where `embedded-model`
# is on.
#
# The asymmetry is its size. At 24 MB it is more than twice the instance model,
# and Android reaches it the way it reaches the face weights — unpacked from
# APK assets at first launch — rather than by carrying it in the binary. This
# feature is for a desktop build with nowhere else to read it from, and for
# tests that want the real graph.
embedded-scene-model = ["semantic"]