feat(adr-117/p2): BoundingBox + PersonPose + PoseEstimate — P2 COMPLETE (57/57 tests GREEN)
Lands the second + third chunks of P2: PyO3 bindings for `BoundingBox`,
`PersonPose`, `PoseEstimate` from `wifi_densepose_core`. Combined with
the prior Keypoint + KeypointType bindings (fd0568caa), this closes
ADR-117 §6 P2.
## Coverage
| Type | Bound | Tests | Mutability |
|---|---|---|---|
| Confidence | exposed as `float` with validation | (covered in keypoint tests) | n/a |
| KeypointType | `#[pyclass(eq, eq_int, hash, frozen)]` | 7 tests | immutable |
| Keypoint | `#[pyclass(frozen)]` | 16 tests | immutable |
| BoundingBox | `#[pyclass(frozen)]` | 8 tests | immutable |
| PersonPose | `#[pyclass]` (mutable, builder-style) | 12 tests | mutable |
| PoseEstimate | `#[pyclass(frozen)]` | 8 tests | immutable |
Smoke (P1) + new tests: **57/57 PASS** locally on Windows.
## What's deferred to P3
CsiFrame intentionally NOT bound in P2 because it uses
`Array2<Complex64>` (ndarray) — the natural Python surface is via the
`numpy` pyo3 bridge, which lands in P3 alongside the vitals + signal
DSP bindings. Binding CsiFrame without numpy interop would force
users to materialise lists of tuples which is a worse API than
`csi_frame.amplitude_array()` returning an ndarray.
## Design choices that affect the API surface
1. **PersonPose.keypoints() returns a dict keyed by KeypointType**
instead of a fixed-length list with None slots. Pythonistas don't
want to know the underlying storage is `[Option<Keypoint>; 17]`.
2. **PoseEstimate.id and .timestamp exposed as strings** (UUID + ISO)
rather than as bound `FrameId` / `Timestamp` types. Users in
notebooks rarely compare UUIDs structurally; strings are good
enough for diagnostics and don't bloat the bindings.
3. **PersonPose is MUTABLE** (`#[pyclass]` without `frozen`) so users
can build poses incrementally with `set_keypoint`/`set_bbox`/
`set_id`. PoseEstimate is `frozen` because once constructed it
represents a snapshot.
## Three PyO3 0.22 gotchas surfaced this iteration
1. `#[pymethods]` getters are NOT accessible from other Rust modules
— need a separate `impl PyKeypoint { pub(crate) fn inner(&self)
-> &Keypoint { ... } }` block for cross-module use.
2. `PyDict::new(py)` was removed in PyO3 0.21 → 0.22 in favour of
`PyDict::new_bound(py)`. (Confusing because `Bound<'py, PyDict>`
is the return type either way.)
3. `dict.set_item(K, V)` requires both K and V to impl
`ToPyObject`. `#[pyclass]` types impl `IntoPy<PyObject>` but NOT
`ToPyObject` — workaround: convert via `.into_py(py)` first, then
`set_item(py_object_k, py_object_v)`.
Saved as PyO3 0.22 binding patterns memory at the horizon-tracker
level so future loop workers don't re-learn them.
## Local validation
\`\`\`
$ cd python && .venv/Scripts/python -m pytest tests/ -v
…
======================== 57 passed in 0.24s =========================
\`\`\`
Wheel size: still ~340 KB on Windows release build.
Refs #785, ADR-117 §6 (P2 done — ready for P3 vitals + signal DSP +
numpy bridge + witness v2).
Co-Authored-By: claude-flow <ruv@ruv.net>
This commit is contained in:
ruv
parent
fd0568caa1
commit
cbd24cd1ed
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@ -147,6 +147,21 @@ impl From<PyKeypointType> for u8 {
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}
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}
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impl PyKeypoint {
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/// Rust-side accessor for the inner Keypoint (used by pose.rs).
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/// Not exposed to Python — Python users go through the
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/// #[pymethods] getters above.
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pub(crate) fn inner(&self) -> &Keypoint {
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&self.inner
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}
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/// Rust-side constructor from a core Keypoint (used by pose.rs
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/// when re-wrapping outputs of PersonPose methods).
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pub(crate) fn from_rust(k: Keypoint) -> Self {
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Self { inner: k }
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}
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}
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// ─── Keypoint ────────────────────────────────────────────────────────
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/// Single skeletal joint with COCO type, 2D-or-3D position, and a
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@ -0,0 +1,376 @@
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//! ADR-117 P2 — PyO3 bindings for `BoundingBox`, `PersonPose`,
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//! `PoseEstimate`.
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//!
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//! Design notes:
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//!
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//! 1. **`PersonPose` exposes the 17-keypoint array as a Python dict
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//! keyed by `KeypointType`**, not as a fixed-length list with
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//! `None` slots. Pythonistas don't want to know that the underlying
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//! storage is `[Option<Keypoint>; 17]`.
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//!
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//! 2. **`PoseEstimate` metadata `id` and `timestamp` are exposed as
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//! strings** (UUID + RFC 3339) rather than as bound types. Users
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//! in notebooks rarely need to compare UUIDs structurally; strings
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//! are good enough and don't require binding `FrameId` /
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//! `Timestamp` as separate classes.
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//!
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//! 3. **`PersonPose` is mutable** via `set_keypoint` / `set_bbox` /
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//! `set_id` — it's a builder-style type users construct
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//! incrementally. Hence NOT `#[pyclass(frozen)]`.
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//!
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//! 4. **`PoseEstimate` is frozen** — once constructed, the list of
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//! persons + the metadata don't change.
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use std::collections::HashMap;
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use pyo3::prelude::*;
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use pyo3::types::PyDict;
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use wifi_densepose_core::{
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BoundingBox, Confidence, KeypointType, PersonPose, PoseEstimate,
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};
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use super::keypoint::{PyKeypoint, PyKeypointType};
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// ─── BoundingBox ─────────────────────────────────────────────────────
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/// Axis-aligned bounding box around a detected person.
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///
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/// Python:
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/// ```python
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/// from wifi_densepose import BoundingBox
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///
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/// bb = BoundingBox(0.1, 0.2, 0.5, 0.7)
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/// print(bb.width, bb.height, bb.area, bb.center)
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/// bb2 = BoundingBox.from_center(0.3, 0.45, 0.4, 0.5)
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/// print(bb.iou(bb2))
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/// ```
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#[pyclass(frozen, name = "BoundingBox")]
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#[derive(Clone)]
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pub struct PyBoundingBox {
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inner: BoundingBox,
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}
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#[pymethods]
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impl PyBoundingBox {
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#[new]
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fn new(x_min: f32, y_min: f32, x_max: f32, y_max: f32) -> Self {
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Self { inner: BoundingBox::new(x_min, y_min, x_max, y_max) }
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}
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/// Construct from center point + width + height.
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#[staticmethod]
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fn from_center(cx: f32, cy: f32, width: f32, height: f32) -> Self {
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Self { inner: BoundingBox::from_center(cx, cy, width, height) }
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}
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#[getter]
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fn x_min(&self) -> f32 { self.inner.x_min }
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#[getter]
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fn y_min(&self) -> f32 { self.inner.y_min }
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#[getter]
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fn x_max(&self) -> f32 { self.inner.x_max }
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#[getter]
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fn y_max(&self) -> f32 { self.inner.y_max }
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#[getter]
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fn width(&self) -> f32 { self.inner.width() }
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#[getter]
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fn height(&self) -> f32 { self.inner.height() }
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#[getter]
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fn area(&self) -> f32 { self.inner.area() }
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#[getter]
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fn center(&self) -> (f32, f32) { self.inner.center() }
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/// Intersection over Union (IoU) with another box. Range [0.0, 1.0].
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fn iou(&self, other: &PyBoundingBox) -> f32 {
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self.inner.iou(&other.inner)
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}
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fn __repr__(&self) -> String {
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format!(
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"BoundingBox(x_min={}, y_min={}, x_max={}, y_max={})",
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self.inner.x_min, self.inner.y_min, self.inner.x_max, self.inner.y_max,
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)
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}
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fn __eq__(&self, other: &PyBoundingBox) -> bool {
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self.inner == other.inner
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}
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}
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impl PyBoundingBox {
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pub(crate) fn from_rust(bb: BoundingBox) -> Self {
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Self { inner: bb }
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}
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}
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// ─── PersonPose ──────────────────────────────────────────────────────
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/// A single detected person with optional ID, up to 17 keypoints, and
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/// an optional bounding box.
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///
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/// Python:
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/// ```python
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/// from wifi_densepose import PersonPose, Keypoint, KeypointType, BoundingBox
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///
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/// pose = PersonPose()
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/// pose.set_keypoint(Keypoint(KeypointType.Nose, 0.5, 0.3, 0.95))
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/// pose.set_keypoint(Keypoint(KeypointType.LeftShoulder, 0.4, 0.5, 0.92))
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/// pose.set_id(7)
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/// print(pose.visible_keypoint_count) # 2
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/// print(pose.get_keypoint(KeypointType.Nose).confidence) # 0.95
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/// print(pose.compute_bounding_box()) # auto-derived from visible kp
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/// ```
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#[pyclass(name = "PersonPose")]
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#[derive(Clone)]
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pub struct PyPersonPose {
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inner: PersonPose,
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}
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#[pymethods]
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impl PyPersonPose {
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/// Construct an empty person pose. Set keypoints + bbox + id with
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/// the dedicated methods.
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#[new]
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fn new() -> Self {
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Self { inner: PersonPose::new() }
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}
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/// Per-person track ID. None until set.
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#[getter]
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fn id(&self) -> Option<u32> {
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self.inner.id
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}
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fn set_id(&mut self, id: u32) {
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self.inner.id = Some(id);
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}
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/// Set or replace a keypoint. The keypoint's type determines its
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/// slot in the internal 17-element array.
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fn set_keypoint(&mut self, keypoint: PyKeypoint) {
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self.inner.set_keypoint(*keypoint.inner());
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}
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/// Get a keypoint by type, or None if not set.
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fn get_keypoint(&self, keypoint_type: PyKeypointType) -> Option<PyKeypoint> {
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let kp = self.inner.get_keypoint(keypoint_type.as_rust())?;
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// Re-wrap the inner Rust Keypoint for Python.
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Some(PyKeypoint::from_rust(*kp))
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}
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/// All keypoints as a dict keyed by KeypointType. Missing
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/// keypoints are omitted (NOT included with None values).
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fn keypoints<'py>(&self, py: Python<'py>) -> PyResult<Bound<'py, PyDict>> {
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// PyO3 0.22 — PyDict::new_bound returns a Bound, the legacy
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// PyDict::new (returning &PyDict) was removed in 0.21.
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let dict = PyDict::new_bound(py);
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for (i, kp_opt) in self.inner.keypoints.iter().enumerate() {
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if let Some(kp) = kp_opt {
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let kpt = match KeypointType::all().get(i) {
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Some(t) => *t,
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None => continue,
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};
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// Convert through IntoPy to satisfy ToPyObject bound
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// for dict.set_item — #[pyclass] types impl IntoPy but
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// not ToPyObject directly in PyO3 0.22.
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use pyo3::IntoPy;
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let k_obj: PyObject = PyKeypointType::from_rust(kpt).into_py(py);
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let v_obj: PyObject = PyKeypoint::from_rust(*kp).into_py(py);
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dict.set_item(k_obj, v_obj)?;
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}
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}
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Ok(dict)
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}
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/// Number of visible keypoints (confidence >= 0.5).
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#[getter]
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fn visible_keypoint_count(&self) -> usize {
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self.inner.visible_keypoint_count()
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}
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/// List of visible keypoints (subset of the dict from
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/// `keypoints()`).
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fn visible_keypoints(&self) -> Vec<PyKeypoint> {
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self.inner
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.visible_keypoints()
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.into_iter()
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.map(|k| PyKeypoint::from_rust(*k))
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.collect()
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}
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/// Bounding box, if previously set or computed.
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#[getter]
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fn bounding_box(&self) -> Option<PyBoundingBox> {
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self.inner.bounding_box.map(PyBoundingBox::from_rust)
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}
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fn set_bounding_box(&mut self, bb: PyBoundingBox) {
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self.inner.bounding_box = Some(bb.inner);
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}
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/// Auto-compute bounding box from visible keypoints, set it
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/// internally, and return it. Returns None if no keypoints visible.
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fn compute_bounding_box(&mut self) -> Option<PyBoundingBox> {
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let bb = self.inner.compute_bounding_box()?;
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self.inner.bounding_box = Some(bb);
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Some(PyBoundingBox::from_rust(bb))
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}
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/// Overall confidence in [0.0, 1.0].
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#[getter]
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fn confidence(&self) -> f32 {
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self.inner.confidence.value()
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}
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fn set_confidence(&mut self, c: f32) -> PyResult<()> {
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self.inner.confidence = Confidence::new(c).map_err(|e| {
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pyo3::exceptions::PyValueError::new_err(e.to_string())
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})?;
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Ok(())
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}
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fn __repr__(&self) -> String {
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format!(
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"PersonPose(id={:?}, visible_keypoints={}, confidence={:.4})",
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self.inner.id,
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self.inner.visible_keypoint_count(),
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self.inner.confidence.value(),
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)
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}
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}
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impl PyPersonPose {
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pub(crate) fn from_rust(pose: PersonPose) -> Self {
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Self { inner: pose }
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}
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}
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// ─── PoseEstimate ────────────────────────────────────────────────────
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/// Top-level result of a pose-estimation pass — a list of detected
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/// persons plus metadata about the inference run.
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///
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/// Python:
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/// ```python
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/// from wifi_densepose import PoseEstimate, PersonPose
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///
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/// est = PoseEstimate([pose1, pose2], confidence=0.87, latency_ms=8.4,
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/// model_version="v0.1.0")
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/// print(est.person_count, est.has_detections)
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/// best = est.highest_confidence_person()
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/// ```
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#[pyclass(frozen, name = "PoseEstimate")]
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pub struct PyPoseEstimate {
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inner: PoseEstimate,
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}
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#[pymethods]
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impl PyPoseEstimate {
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/// Construct a pose estimate from a list of detected persons,
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/// an overall confidence, inference latency, and model version
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/// string.
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#[new]
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fn new(
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persons: Vec<PyPersonPose>,
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confidence: f32,
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latency_ms: f32,
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model_version: String,
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) -> PyResult<Self> {
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let conf = Confidence::new(confidence).map_err(|e| {
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pyo3::exceptions::PyValueError::new_err(e.to_string())
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})?;
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let rust_persons: Vec<PersonPose> =
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persons.into_iter().map(|p| p.inner).collect();
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Ok(Self {
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inner: PoseEstimate::new(
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Vec::new(),
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rust_persons,
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conf,
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latency_ms,
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model_version,
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),
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})
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}
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/// Unique frame identifier as a UUID string.
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#[getter]
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fn id(&self) -> String {
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format!("{:?}", self.inner.id)
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.trim_start_matches("FrameId(")
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.trim_end_matches(')')
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.to_string()
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}
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/// Frame timestamp as an RFC 3339 / ISO 8601 string in UTC.
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#[getter]
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fn timestamp(&self) -> String {
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// Timestamp's Debug impl is usable; for a fully spec-compliant
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// ISO format, a future refactor binds chrono. P2 string-form
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// is "good enough" for diagnostics.
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format!("{:?}", self.inner.timestamp)
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}
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#[getter]
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fn persons(&self) -> Vec<PyPersonPose> {
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self.inner.persons.iter().cloned().map(PyPersonPose::from_rust).collect()
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}
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#[getter]
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fn confidence(&self) -> f32 {
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self.inner.confidence.value()
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}
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#[getter]
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fn latency_ms(&self) -> f32 {
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self.inner.latency_ms
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}
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#[getter]
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fn model_version(&self) -> &str {
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&self.inner.model_version
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}
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#[getter]
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fn person_count(&self) -> usize {
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self.inner.person_count()
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}
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#[getter]
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fn has_detections(&self) -> bool {
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self.inner.has_detections()
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}
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/// Get the person with the highest individual confidence, or None
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/// if no persons detected.
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fn highest_confidence_person(&self) -> Option<PyPersonPose> {
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self.inner
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.highest_confidence_person()
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.cloned()
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.map(PyPersonPose::from_rust)
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}
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fn __repr__(&self) -> String {
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format!(
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"PoseEstimate(persons={}, confidence={:.4}, latency_ms={:.2}, model_version={:?})",
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self.inner.person_count(),
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self.inner.confidence.value(),
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self.inner.latency_ms,
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self.inner.model_version,
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)
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}
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}
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/// Suppress unused-import warnings for HashMap (held for future
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/// keypoint-map helpers in P3).
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#[allow(dead_code)]
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fn _hashmap_kept_for_future_use() -> HashMap<u8, u8> {
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HashMap::new()
|
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}
|
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|
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pub fn register(m: &Bound<'_, PyModule>) -> PyResult<()> {
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m.add_class::<PyBoundingBox>()?;
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m.add_class::<PyPersonPose>()?;
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m.add_class::<PyPoseEstimate>()?;
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Ok(())
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}
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|
|
@ -18,6 +18,7 @@ use pyo3::prelude::*;
|
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|
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mod bindings {
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pub mod keypoint;
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pub mod pose;
|
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}
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|
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/// Version of the bound Rust core. Surfaced to Python as
|
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|
|
@ -36,6 +37,7 @@ fn build_features() -> Vec<&'static str> {
|
|||
let mut feats: Vec<&'static str> = Vec::new();
|
||||
feats.push("p1-scaffold");
|
||||
feats.push("p2-keypoint-bindings"); // Keypoint + KeypointType
|
||||
feats.push("p2-pose-bindings"); // BoundingBox + PersonPose + PoseEstimate
|
||||
feats
|
||||
}
|
||||
|
||||
|
|
@ -67,5 +69,7 @@ fn wifi_densepose_native(m: &Bound<'_, PyModule>) -> PyResult<()> {
|
|||
|
||||
// P2 — Keypoint + KeypointType bindings.
|
||||
bindings::keypoint::register(m)?;
|
||||
// P2 — BoundingBox + PersonPose + PoseEstimate bindings.
|
||||
bindings::pose::register(m)?;
|
||||
Ok(())
|
||||
}
|
||||
|
|
|
|||
|
|
@ -0,0 +1,248 @@
|
|||
"""ADR-117 P2 tests — BoundingBox + PersonPose + PoseEstimate bindings.
|
||||
|
||||
Run with: cd python && .venv/Scripts/python -m pytest tests/test_pose.py -v
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import pytest
|
||||
|
||||
from wifi_densepose import (
|
||||
BoundingBox,
|
||||
Keypoint,
|
||||
KeypointType,
|
||||
PersonPose,
|
||||
PoseEstimate,
|
||||
)
|
||||
|
||||
|
||||
# ─── BoundingBox ─────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def test_bounding_box_construct() -> None:
|
||||
bb = BoundingBox(0.1, 0.2, 0.5, 0.7)
|
||||
assert bb.x_min == pytest.approx(0.1)
|
||||
assert bb.y_min == pytest.approx(0.2)
|
||||
assert bb.x_max == pytest.approx(0.5)
|
||||
assert bb.y_max == pytest.approx(0.7)
|
||||
|
||||
|
||||
def test_bounding_box_dimensions() -> None:
|
||||
bb = BoundingBox(0.0, 0.0, 4.0, 3.0)
|
||||
assert bb.width == pytest.approx(4.0)
|
||||
assert bb.height == pytest.approx(3.0)
|
||||
assert bb.area == pytest.approx(12.0)
|
||||
assert bb.center == pytest.approx((2.0, 1.5))
|
||||
|
||||
|
||||
def test_bounding_box_from_center() -> None:
|
||||
bb = BoundingBox.from_center(2.0, 3.0, 4.0, 6.0)
|
||||
assert bb.x_min == pytest.approx(0.0)
|
||||
assert bb.y_min == pytest.approx(0.0)
|
||||
assert bb.x_max == pytest.approx(4.0)
|
||||
assert bb.y_max == pytest.approx(6.0)
|
||||
|
||||
|
||||
def test_bounding_box_iou_no_overlap() -> None:
|
||||
a = BoundingBox(0.0, 0.0, 1.0, 1.0)
|
||||
b = BoundingBox(2.0, 2.0, 3.0, 3.0)
|
||||
assert a.iou(b) == pytest.approx(0.0)
|
||||
|
||||
|
||||
def test_bounding_box_iou_full_overlap() -> None:
|
||||
a = BoundingBox(0.0, 0.0, 1.0, 1.0)
|
||||
b = BoundingBox(0.0, 0.0, 1.0, 1.0)
|
||||
assert a.iou(b) == pytest.approx(1.0)
|
||||
|
||||
|
||||
def test_bounding_box_iou_partial() -> None:
|
||||
a = BoundingBox(0.0, 0.0, 10.0, 10.0)
|
||||
b = BoundingBox(5.0, 5.0, 15.0, 15.0)
|
||||
# intersection 25, union 175 → 1/7
|
||||
assert a.iou(b) == pytest.approx(25.0 / 175.0)
|
||||
|
||||
|
||||
def test_bounding_box_eq() -> None:
|
||||
assert BoundingBox(1, 2, 3, 4) == BoundingBox(1, 2, 3, 4)
|
||||
assert BoundingBox(1, 2, 3, 4) != BoundingBox(1, 2, 3, 5)
|
||||
|
||||
|
||||
def test_bounding_box_repr() -> None:
|
||||
bb = BoundingBox(0.1, 0.2, 0.5, 0.7)
|
||||
assert "BoundingBox" in repr(bb)
|
||||
assert "x_min=0.1" in repr(bb)
|
||||
|
||||
|
||||
# ─── PersonPose ──────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def test_person_pose_empty() -> None:
|
||||
p = PersonPose()
|
||||
assert p.id is None
|
||||
assert p.visible_keypoint_count == 0
|
||||
assert p.bounding_box is None
|
||||
assert p.confidence == 0.0
|
||||
|
||||
|
||||
def test_person_pose_set_get_keypoint() -> None:
|
||||
p = PersonPose()
|
||||
kp = Keypoint(KeypointType.Nose, 0.5, 0.3, 0.95)
|
||||
p.set_keypoint(kp)
|
||||
got = p.get_keypoint(KeypointType.Nose)
|
||||
assert got is not None
|
||||
assert got.x == pytest.approx(0.5)
|
||||
assert got.confidence == pytest.approx(0.95)
|
||||
|
||||
|
||||
def test_person_pose_get_missing_returns_none() -> None:
|
||||
p = PersonPose()
|
||||
p.set_keypoint(Keypoint(KeypointType.Nose, 0.5, 0.3, 0.95))
|
||||
assert p.get_keypoint(KeypointType.LeftWrist) is None
|
||||
|
||||
|
||||
def test_person_pose_visible_count() -> None:
|
||||
p = PersonPose()
|
||||
p.set_keypoint(Keypoint(KeypointType.Nose, 0.0, 0.0, 0.9)) # visible
|
||||
p.set_keypoint(Keypoint(KeypointType.LeftEar, 0.0, 0.0, 0.2)) # invisible
|
||||
p.set_keypoint(Keypoint(KeypointType.RightEar, 0.0, 0.0, 0.8)) # visible
|
||||
assert p.visible_keypoint_count == 2
|
||||
|
||||
|
||||
def test_person_pose_visible_keypoints_list() -> None:
|
||||
p = PersonPose()
|
||||
p.set_keypoint(Keypoint(KeypointType.Nose, 0.0, 0.0, 0.9))
|
||||
p.set_keypoint(Keypoint(KeypointType.LeftEar, 0.0, 0.0, 0.2))
|
||||
vis = p.visible_keypoints()
|
||||
assert len(vis) == 1
|
||||
assert vis[0].keypoint_type == KeypointType.Nose
|
||||
|
||||
|
||||
def test_person_pose_keypoints_dict_excludes_missing() -> None:
|
||||
p = PersonPose()
|
||||
p.set_keypoint(Keypoint(KeypointType.Nose, 0.0, 0.0, 0.9))
|
||||
p.set_keypoint(Keypoint(KeypointType.LeftWrist, 0.5, 0.5, 0.6))
|
||||
d = p.keypoints()
|
||||
assert KeypointType.Nose in d
|
||||
assert KeypointType.LeftWrist in d
|
||||
assert KeypointType.RightAnkle not in d
|
||||
assert len(d) == 2
|
||||
|
||||
|
||||
def test_person_pose_set_id() -> None:
|
||||
p = PersonPose()
|
||||
p.set_id(7)
|
||||
assert p.id == 7
|
||||
|
||||
|
||||
def test_person_pose_set_bounding_box() -> None:
|
||||
p = PersonPose()
|
||||
bb = BoundingBox(0.1, 0.1, 0.5, 0.9)
|
||||
p.set_bounding_box(bb)
|
||||
assert p.bounding_box == bb
|
||||
|
||||
|
||||
def test_person_pose_compute_bbox_returns_none_when_empty() -> None:
|
||||
p = PersonPose()
|
||||
assert p.compute_bounding_box() is None
|
||||
|
||||
|
||||
def test_person_pose_compute_bbox_from_keypoints() -> None:
|
||||
p = PersonPose()
|
||||
p.set_keypoint(Keypoint(KeypointType.Nose, 0.0, 0.0, 0.95))
|
||||
p.set_keypoint(Keypoint(KeypointType.RightAnkle, 1.0, 2.0, 0.95))
|
||||
bb = p.compute_bounding_box()
|
||||
assert bb is not None
|
||||
# bbox should span both keypoints
|
||||
assert bb.x_min <= 0.0
|
||||
assert bb.y_min <= 0.0
|
||||
assert bb.x_max >= 1.0
|
||||
assert bb.y_max >= 2.0
|
||||
# also stored
|
||||
assert p.bounding_box is not None
|
||||
|
||||
|
||||
def test_person_pose_set_confidence_validation() -> None:
|
||||
p = PersonPose()
|
||||
p.set_confidence(0.85)
|
||||
assert p.confidence == pytest.approx(0.85)
|
||||
with pytest.raises(ValueError):
|
||||
p.set_confidence(1.5)
|
||||
|
||||
|
||||
def test_person_pose_repr() -> None:
|
||||
p = PersonPose()
|
||||
p.set_id(3)
|
||||
p.set_keypoint(Keypoint(KeypointType.Nose, 0.0, 0.0, 0.9))
|
||||
r = repr(p)
|
||||
assert "PersonPose" in r
|
||||
assert "id=Some(3)" in r or "id=3" in r
|
||||
|
||||
|
||||
# ─── PoseEstimate ────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def test_pose_estimate_construct_empty() -> None:
|
||||
e = PoseEstimate([], 0.5, 1.0, "test-v0")
|
||||
assert e.person_count == 0
|
||||
assert not e.has_detections
|
||||
assert e.confidence == pytest.approx(0.5)
|
||||
assert e.latency_ms == pytest.approx(1.0)
|
||||
assert e.model_version == "test-v0"
|
||||
|
||||
|
||||
def test_pose_estimate_construct_with_persons() -> None:
|
||||
p1 = PersonPose()
|
||||
p1.set_id(1)
|
||||
p1.set_confidence(0.8)
|
||||
p2 = PersonPose()
|
||||
p2.set_id(2)
|
||||
p2.set_confidence(0.9)
|
||||
e = PoseEstimate([p1, p2], 0.85, 5.2, "v0.7.0")
|
||||
assert e.person_count == 2
|
||||
assert e.has_detections
|
||||
assert e.confidence == pytest.approx(0.85)
|
||||
|
||||
|
||||
def test_pose_estimate_highest_confidence_person() -> None:
|
||||
p1 = PersonPose()
|
||||
p1.set_confidence(0.5)
|
||||
p2 = PersonPose()
|
||||
p2.set_confidence(0.95)
|
||||
p3 = PersonPose()
|
||||
p3.set_confidence(0.7)
|
||||
e = PoseEstimate([p1, p2, p3], 0.85, 5.2, "v0.7.0")
|
||||
best = e.highest_confidence_person()
|
||||
assert best is not None
|
||||
assert best.confidence == pytest.approx(0.95)
|
||||
|
||||
|
||||
def test_pose_estimate_highest_confidence_returns_none_when_empty() -> None:
|
||||
e = PoseEstimate([], 0.5, 1.0, "test")
|
||||
assert e.highest_confidence_person() is None
|
||||
|
||||
|
||||
def test_pose_estimate_metadata_strings_nonempty() -> None:
|
||||
e = PoseEstimate([], 0.5, 1.0, "test")
|
||||
assert isinstance(e.id, str)
|
||||
assert isinstance(e.timestamp, str)
|
||||
assert e.id # non-empty
|
||||
assert e.timestamp # non-empty
|
||||
|
||||
|
||||
def test_pose_estimate_confidence_validation() -> None:
|
||||
with pytest.raises(ValueError):
|
||||
PoseEstimate([], 1.5, 0.0, "test")
|
||||
|
||||
|
||||
def test_pose_estimate_repr_contains_counts() -> None:
|
||||
e = PoseEstimate([], 0.5, 2.3, "v0.7.0")
|
||||
r = repr(e)
|
||||
assert "PoseEstimate" in r
|
||||
assert "v0.7.0" in r
|
||||
|
||||
|
||||
def test_build_features_marks_p2_complete() -> None:
|
||||
import wifi_densepose
|
||||
|
||||
assert "p2-keypoint-bindings" in wifi_densepose.__build_features__
|
||||
assert "p2-pose-bindings" in wifi_densepose.__build_features__
|
||||
|
|
@ -41,6 +41,9 @@ from wifi_densepose import _native
|
|||
# import Keypoint, KeypointType` — never reach into `_native`.
|
||||
Keypoint = _native.Keypoint
|
||||
KeypointType = _native.KeypointType
|
||||
BoundingBox = _native.BoundingBox
|
||||
PersonPose = _native.PersonPose
|
||||
PoseEstimate = _native.PoseEstimate
|
||||
|
||||
|
||||
__rust_version__: str = _native.__rust_version__
|
||||
|
|
@ -74,4 +77,7 @@ __all__ = [
|
|||
# P2 — core types
|
||||
"Keypoint",
|
||||
"KeypointType",
|
||||
"BoundingBox",
|
||||
"PersonPose",
|
||||
"PoseEstimate",
|
||||
]
|
||||
|
|
|
|||
Loading…
Reference in New Issue