mirror of
https://github.com/ruvnet/RuView.git
synced 2026-04-26 13:10:40 +00:00
feat: ADR-080 P1+P2 remediation — refactor, perf, tests, safety
P1 fixes (this sprint): - P1-6: Extract sensing-server modules (cli, types, csi, pose) from main.rs - P1-7: DDA ray march for tomography — O(max(n)) replaces O(n^3) voxel scan - P1-8: Batch neural inference — Tensor::stack/split for single GPU call - P1-10: Eliminate 112KB/frame alloc — islice replaces deque→list copy P2 fixes (this quarter): - P2-11: Python unit tests for 8 modules (rate_limit, auth, error_handler, pose_service, stream_service, hardware_service, health_check, metrics) - P2-13: MAT simulated data safety guard — blocking overlay + pulsing banner - P2-14: Wire token blacklist into auth verification + logout endpoint - P2-15: Frame budget benchmark — confirms pipeline well under 50ms budget Addresses 8 of 10 remaining issues from QE analysis (ADR-080). Co-Authored-By: claude-flow <ruv@ruv.net>
This commit is contained in:
ruv
parent
924c32547e
commit
4bb0b87465
30 changed files with 2635 additions and 27 deletions
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@ -330,9 +330,36 @@ impl<B: Backend> InferenceEngine<B> {
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Ok(result)
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}
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/// Run batched inference
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/// Run batched inference.
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///
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/// Stacks all inputs along a new batch dimension, runs a single
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/// backend call, then splits the output back into individual tensors.
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/// Falls back to sequential inference if stack/split fails.
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pub fn infer_batch(&self, inputs: &[Tensor]) -> NnResult<Vec<Tensor>> {
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inputs.iter().map(|input| self.infer(input)).collect()
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if inputs.is_empty() {
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return Ok(Vec::new());
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}
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if inputs.len() == 1 {
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return Ok(vec![self.infer(&inputs[0])?]);
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}
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// Try batched path: stack -> single call -> split
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match Tensor::stack(inputs) {
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Ok(batched_input) => {
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let n = inputs.len();
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let batched_output = self.backend.run_single(&batched_input)?;
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match batched_output.split(n) {
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Ok(outputs) => Ok(outputs),
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Err(_) => {
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// Fallback: sequential
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inputs.iter().map(|input| self.infer(input)).collect()
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}
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}
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}
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Err(_) => {
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// Fallback: sequential if shapes are incompatible
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inputs.iter().map(|input| self.infer(input)).collect()
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}
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}
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}
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/// Get inference statistics
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@ -304,6 +304,74 @@ impl Tensor {
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}
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}
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/// Stack multiple tensors along a new batch dimension (dim 0).
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///
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/// All tensors must have the same shape. The result has one extra
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/// leading dimension equal to `tensors.len()`.
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pub fn stack(tensors: &[Tensor]) -> NnResult<Tensor> {
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if tensors.is_empty() {
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return Err(NnError::tensor_op("Cannot stack zero tensors"));
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}
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let first_shape = tensors[0].shape();
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for (i, t) in tensors.iter().enumerate().skip(1) {
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if t.shape() != first_shape {
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return Err(NnError::tensor_op(&format!(
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"Shape mismatch at index {i}: expected {first_shape}, got {}",
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t.shape()
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)));
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}
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}
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let mut all_data: Vec<f32> = Vec::with_capacity(tensors.len() * first_shape.numel());
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for t in tensors {
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let data = t.to_vec()?;
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all_data.extend_from_slice(&data);
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}
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let mut new_dims = vec![tensors.len()];
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new_dims.extend_from_slice(first_shape.dims());
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let arr = ndarray::ArrayD::from_shape_vec(
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ndarray::IxDyn(&new_dims),
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all_data,
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)
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.map_err(|e| NnError::tensor_op(&format!("Stack reshape failed: {e}")))?;
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Ok(Tensor::FloatND(arr))
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}
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/// Split a tensor along dim 0 into `n` sub-tensors.
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///
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/// The first dimension must be evenly divisible by `n`.
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pub fn split(self, n: usize) -> NnResult<Vec<Tensor>> {
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if n == 0 {
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return Err(NnError::tensor_op("Cannot split into 0 pieces"));
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}
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let shape = self.shape();
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let batch = shape.dim(0).ok_or_else(|| NnError::tensor_op("Tensor has no dimensions"))?;
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if batch % n != 0 {
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return Err(NnError::tensor_op(&format!(
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"Batch dim {batch} not divisible by {n}"
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)));
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}
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let chunk_size = batch / n;
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let data = self.to_vec()?;
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let elem_per_sample = shape.numel() / batch;
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let sub_dims: Vec<usize> = {
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let mut d = shape.dims().to_vec();
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d[0] = chunk_size;
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d
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};
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let mut result = Vec::with_capacity(n);
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for i in 0..n {
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let start = i * chunk_size * elem_per_sample;
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let end = start + chunk_size * elem_per_sample;
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let arr = ndarray::ArrayD::from_shape_vec(
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ndarray::IxDyn(&sub_dims),
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data[start..end].to_vec(),
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)
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.map_err(|e| NnError::tensor_op(&format!("Split reshape failed: {e}")))?;
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result.push(Tensor::FloatND(arr));
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}
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Ok(result)
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}
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/// Compute standard deviation
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pub fn std(&self) -> NnResult<f32> {
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match self {
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@ -0,0 +1,105 @@
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//! CLI argument definitions and early-exit mode handlers.
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use std::path::PathBuf;
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use clap::Parser;
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/// CLI arguments for the sensing server.
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#[derive(Parser, Debug)]
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#[command(name = "sensing-server", about = "WiFi-DensePose sensing server")]
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pub struct Args {
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/// HTTP port for UI and REST API
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#[arg(long, default_value = "8080")]
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pub http_port: u16,
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/// WebSocket port for sensing stream
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#[arg(long, default_value = "8765")]
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pub ws_port: u16,
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/// UDP port for ESP32 CSI frames
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#[arg(long, default_value = "5005")]
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pub udp_port: u16,
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/// Path to UI static files
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#[arg(long, default_value = "../../ui")]
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pub ui_path: PathBuf,
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/// Tick interval in milliseconds (default 100 ms = 10 fps for smooth pose animation)
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#[arg(long, default_value = "100")]
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pub tick_ms: u64,
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/// Bind address (default 127.0.0.1; set to 0.0.0.0 for network access)
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#[arg(long, default_value = "127.0.0.1", env = "SENSING_BIND_ADDR")]
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pub bind_addr: String,
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/// Data source: auto, wifi, esp32, simulate
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#[arg(long, default_value = "auto")]
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pub source: String,
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/// Run vital sign detection benchmark (1000 frames) and exit
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#[arg(long)]
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pub benchmark: bool,
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/// Load model config from an RVF container at startup
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#[arg(long, value_name = "PATH")]
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pub load_rvf: Option<PathBuf>,
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/// Save current model state as an RVF container on shutdown
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#[arg(long, value_name = "PATH")]
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pub save_rvf: Option<PathBuf>,
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/// Load a trained .rvf model for inference
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#[arg(long, value_name = "PATH")]
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pub model: Option<PathBuf>,
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/// Enable progressive loading (Layer A instant start)
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#[arg(long)]
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pub progressive: bool,
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/// Export an RVF container package and exit (no server)
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#[arg(long, value_name = "PATH")]
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pub export_rvf: Option<PathBuf>,
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/// Run training mode (train a model and exit)
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#[arg(long)]
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pub train: bool,
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/// Path to dataset directory (MM-Fi or Wi-Pose)
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#[arg(long, value_name = "PATH")]
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pub dataset: Option<PathBuf>,
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/// Dataset type: "mmfi" or "wipose"
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#[arg(long, value_name = "TYPE", default_value = "mmfi")]
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pub dataset_type: String,
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/// Number of training epochs
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#[arg(long, default_value = "100")]
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pub epochs: usize,
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/// Directory for training checkpoints
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#[arg(long, value_name = "DIR")]
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pub checkpoint_dir: Option<PathBuf>,
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/// Run self-supervised contrastive pretraining (ADR-024)
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#[arg(long)]
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pub pretrain: bool,
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/// Number of pretraining epochs (default 50)
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#[arg(long, default_value = "50")]
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pub pretrain_epochs: usize,
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/// Extract embeddings mode: load model and extract CSI embeddings
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#[arg(long)]
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pub embed: bool,
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/// Build fingerprint index from embeddings (env|activity|temporal|person)
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#[arg(long, value_name = "TYPE")]
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pub build_index: Option<String>,
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/// Node positions for multistatic fusion (format: "x,y,z;x,y,z;...")
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#[arg(long, env = "SENSING_NODE_POSITIONS")]
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pub node_positions: Option<String>,
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/// Start field model calibration on boot (empty room required)
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#[arg(long)]
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pub calibrate: bool,
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}
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@ -0,0 +1,675 @@
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//! CSI frame parsing, signal field generation, feature extraction,
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//! classification, vital signs smoothing, and multi-person estimation.
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use std::collections::{HashMap, VecDeque};
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use ruvector_mincut::{DynamicMinCut, MinCutBuilder};
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use crate::adaptive_classifier;
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use crate::types::*;
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use crate::vital_signs::VitalSigns;
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// ── ESP32 UDP frame parsers ─────────────────────────────────────────────────
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/// Parse a 32-byte edge vitals packet (magic 0xC511_0002).
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pub fn parse_esp32_vitals(buf: &[u8]) -> Option<Esp32VitalsPacket> {
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if buf.len() < 32 { return None; }
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let magic = u32::from_le_bytes([buf[0], buf[1], buf[2], buf[3]]);
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if magic != 0xC511_0002 { return None; }
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let node_id = buf[4];
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let flags = buf[5];
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let breathing_raw = u16::from_le_bytes([buf[6], buf[7]]);
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let heartrate_raw = u32::from_le_bytes([buf[8], buf[9], buf[10], buf[11]]);
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let rssi = buf[12] as i8;
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let n_persons = buf[13];
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let motion_energy = f32::from_le_bytes([buf[16], buf[17], buf[18], buf[19]]);
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let presence_score = f32::from_le_bytes([buf[20], buf[21], buf[22], buf[23]]);
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let timestamp_ms = u32::from_le_bytes([buf[24], buf[25], buf[26], buf[27]]);
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Some(Esp32VitalsPacket {
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node_id,
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presence: (flags & 0x01) != 0,
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fall_detected: (flags & 0x02) != 0,
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motion: (flags & 0x04) != 0,
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breathing_rate_bpm: breathing_raw as f64 / 100.0,
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heartrate_bpm: heartrate_raw as f64 / 10000.0,
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rssi, n_persons, motion_energy, presence_score, timestamp_ms,
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})
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}
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/// Parse a WASM output packet (magic 0xC511_0004).
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pub fn parse_wasm_output(buf: &[u8]) -> Option<WasmOutputPacket> {
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if buf.len() < 8 { return None; }
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let magic = u32::from_le_bytes([buf[0], buf[1], buf[2], buf[3]]);
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if magic != 0xC511_0004 { return None; }
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let node_id = buf[4];
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let module_id = buf[5];
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let event_count = u16::from_le_bytes([buf[6], buf[7]]) as usize;
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let mut events = Vec::with_capacity(event_count);
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let mut offset = 8;
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for _ in 0..event_count {
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if offset + 5 > buf.len() { break; }
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let event_type = buf[offset];
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let value = f32::from_le_bytes([
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buf[offset + 1], buf[offset + 2], buf[offset + 3], buf[offset + 4],
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]);
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events.push(WasmEvent { event_type, value });
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offset += 5;
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}
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Some(WasmOutputPacket { node_id, module_id, events })
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}
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pub fn parse_esp32_frame(buf: &[u8]) -> Option<Esp32Frame> {
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if buf.len() < 20 { return None; }
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let magic = u32::from_le_bytes([buf[0], buf[1], buf[2], buf[3]]);
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if magic != 0xC511_0001 { return None; }
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let node_id = buf[4];
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let n_antennas = buf[5];
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let n_subcarriers = buf[6];
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let freq_mhz = u16::from_le_bytes([buf[8], buf[9]]);
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let sequence = u32::from_le_bytes([buf[10], buf[11], buf[12], buf[13]]);
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let rssi_raw = buf[14] as i8;
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let rssi = if rssi_raw > 0 { rssi_raw.saturating_neg() } else { rssi_raw };
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let noise_floor = buf[15] as i8;
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let iq_start = 20;
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let n_pairs = n_antennas as usize * n_subcarriers as usize;
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let expected_len = iq_start + n_pairs * 2;
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if buf.len() < expected_len { return None; }
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let mut amplitudes = Vec::with_capacity(n_pairs);
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let mut phases = Vec::with_capacity(n_pairs);
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for k in 0..n_pairs {
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let i_val = buf[iq_start + k * 2] as i8 as f64;
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let q_val = buf[iq_start + k * 2 + 1] as i8 as f64;
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amplitudes.push((i_val * i_val + q_val * q_val).sqrt());
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phases.push(q_val.atan2(i_val));
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}
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Some(Esp32Frame {
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magic, node_id, n_antennas, n_subcarriers, freq_mhz, sequence,
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rssi, noise_floor, amplitudes, phases,
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})
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}
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// ── Signal field generation ─────────────────────────────────────────────────
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pub fn generate_signal_field(
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_mean_rssi: f64, motion_score: f64, breathing_rate_hz: f64,
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signal_quality: f64, subcarrier_variances: &[f64],
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) -> SignalField {
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let grid = 20usize;
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let mut values = vec![0.0f64; grid * grid];
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let center = (grid as f64 - 1.0) / 2.0;
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let max_var = subcarrier_variances.iter().cloned().fold(0.0f64, f64::max);
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let norm_factor = if max_var > 1e-9 { max_var } else { 1.0 };
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let n_sub = subcarrier_variances.len().max(1);
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for (k, &var) in subcarrier_variances.iter().enumerate() {
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let weight = (var / norm_factor) * motion_score;
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if weight < 1e-6 { continue; }
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let angle = (k as f64 / n_sub as f64) * 2.0 * std::f64::consts::PI;
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let radius = center * 0.8 * weight.sqrt();
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let hx = center + radius * angle.cos();
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let hz = center + radius * angle.sin();
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for z in 0..grid {
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for x in 0..grid {
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let dx = x as f64 - hx;
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let dz = z as f64 - hz;
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let dist2 = dx * dx + dz * dz;
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let spread = (0.5 + weight * 2.0).max(0.5);
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values[z * grid + x] += weight * (-dist2 / (2.0 * spread * spread)).exp();
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}
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}
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}
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for z in 0..grid {
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for x in 0..grid {
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let dx = x as f64 - center;
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let dz = z as f64 - center;
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let dist = (dx * dx + dz * dz).sqrt();
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let base = signal_quality * (-dist * 0.12).exp();
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values[z * grid + x] += base * 0.3;
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}
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}
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if breathing_rate_hz > 0.05 {
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let ring_r = center * 0.55;
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let ring_width = 1.8f64;
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for z in 0..grid {
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for x in 0..grid {
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let dx = x as f64 - center;
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let dz = z as f64 - center;
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let dist = (dx * dx + dz * dz).sqrt();
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let ring_val = 0.08 * (-(dist - ring_r).powi(2) / (2.0 * ring_width * ring_width)).exp();
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values[z * grid + x] += ring_val;
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}
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}
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}
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let field_max = values.iter().cloned().fold(0.0f64, f64::max);
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let scale = if field_max > 1e-9 { 1.0 / field_max } else { 1.0 };
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for v in &mut values { *v = (*v * scale).clamp(0.0, 1.0); }
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SignalField { grid_size: [grid, 1, grid], values }
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}
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// ── Feature extraction ──────────────────────────────────────────────────────
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pub fn estimate_breathing_rate_hz(frame_history: &VecDeque<Vec<f64>>, sample_rate_hz: f64) -> f64 {
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let n = frame_history.len();
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if n < 6 { return 0.0; }
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let series: Vec<f64> = frame_history.iter()
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.map(|amps| if amps.is_empty() { 0.0 } else { amps.iter().sum::<f64>() / amps.len() as f64 })
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.collect();
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let mean_s = series.iter().sum::<f64>() / n as f64;
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let detrended: Vec<f64> = series.iter().map(|x| x - mean_s).collect();
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let n_candidates = 9usize;
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let f_low = 0.1f64;
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let f_high = 0.5f64;
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let mut best_freq = 0.0f64;
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let mut best_power = 0.0f64;
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for i in 0..n_candidates {
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let freq = f_low + (f_high - f_low) * i as f64 / (n_candidates - 1).max(1) as f64;
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let omega = 2.0 * std::f64::consts::PI * freq / sample_rate_hz;
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let coeff = 2.0 * omega.cos();
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let (mut s_prev2, mut s_prev1) = (0.0f64, 0.0f64);
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for &x in &detrended {
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let s = x + coeff * s_prev1 - s_prev2;
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s_prev2 = s_prev1;
|
||||
s_prev1 = s;
|
||||
}
|
||||
let power = s_prev2 * s_prev2 + s_prev1 * s_prev1 - coeff * s_prev1 * s_prev2;
|
||||
if power > best_power { best_power = power; best_freq = freq; }
|
||||
}
|
||||
|
||||
let avg_power = {
|
||||
let mut total = 0.0f64;
|
||||
for i in 0..n_candidates {
|
||||
let freq = f_low + (f_high - f_low) * i as f64 / (n_candidates - 1).max(1) as f64;
|
||||
let omega = 2.0 * std::f64::consts::PI * freq / sample_rate_hz;
|
||||
let coeff = 2.0 * omega.cos();
|
||||
let (mut s_prev2, mut s_prev1) = (0.0f64, 0.0f64);
|
||||
for &x in &detrended {
|
||||
let s = x + coeff * s_prev1 - s_prev2;
|
||||
s_prev2 = s_prev1;
|
||||
s_prev1 = s;
|
||||
}
|
||||
total += s_prev2 * s_prev2 + s_prev1 * s_prev1 - coeff * s_prev1 * s_prev2;
|
||||
}
|
||||
total / n_candidates as f64
|
||||
};
|
||||
|
||||
if best_power > avg_power * 3.0 { best_freq.clamp(f_low, f_high) } else { 0.0 }
|
||||
}
|
||||
|
||||
pub fn compute_subcarrier_importance_weights(sensitivity: &[f64]) -> Vec<f64> {
|
||||
let n = sensitivity.len();
|
||||
if n == 0 { return vec![]; }
|
||||
let max_sens = sensitivity.iter().cloned().fold(f64::NEG_INFINITY, f64::max).max(1e-9);
|
||||
let mut sorted = sensitivity.to_vec();
|
||||
sorted.sort_by(|a, b| a.partial_cmp(b).unwrap_or(std::cmp::Ordering::Equal));
|
||||
let median = if n % 2 == 0 { (sorted[n / 2 - 1] + sorted[n / 2]) / 2.0 } else { sorted[n / 2] };
|
||||
sensitivity.iter()
|
||||
.map(|&s| if s >= median { 1.0 + (s / max_sens).min(1.0) } else { 0.5 })
|
||||
.collect()
|
||||
}
|
||||
|
||||
pub fn compute_subcarrier_variances(frame_history: &VecDeque<Vec<f64>>, n_sub: usize) -> Vec<f64> {
|
||||
if frame_history.is_empty() || n_sub == 0 { return vec![0.0; n_sub]; }
|
||||
let n_frames = frame_history.len() as f64;
|
||||
let mut means = vec![0.0f64; n_sub];
|
||||
let mut sq_means = vec![0.0f64; n_sub];
|
||||
for frame in frame_history.iter() {
|
||||
for k in 0..n_sub {
|
||||
let a = if k < frame.len() { frame[k] } else { 0.0 };
|
||||
means[k] += a;
|
||||
sq_means[k] += a * a;
|
||||
}
|
||||
}
|
||||
(0..n_sub).map(|k| {
|
||||
let mean = means[k] / n_frames;
|
||||
let sq_mean = sq_means[k] / n_frames;
|
||||
(sq_mean - mean * mean).max(0.0)
|
||||
}).collect()
|
||||
}
|
||||
|
||||
pub fn extract_features_from_frame(
|
||||
frame: &Esp32Frame, frame_history: &VecDeque<Vec<f64>>, sample_rate_hz: f64,
|
||||
) -> (FeatureInfo, ClassificationInfo, f64, Vec<f64>, f64) {
|
||||
let n_sub = frame.amplitudes.len().max(1);
|
||||
let n = n_sub as f64;
|
||||
let mean_rssi = frame.rssi as f64;
|
||||
|
||||
let sub_sensitivity: Vec<f64> = frame.amplitudes.iter().map(|a| a.abs()).collect();
|
||||
let importance_weights = compute_subcarrier_importance_weights(&sub_sensitivity);
|
||||
let weight_sum: f64 = importance_weights.iter().sum::<f64>();
|
||||
|
||||
let mean_amp: f64 = if weight_sum > 0.0 {
|
||||
frame.amplitudes.iter().zip(importance_weights.iter())
|
||||
.map(|(a, w)| a * w).sum::<f64>() / weight_sum
|
||||
} else {
|
||||
frame.amplitudes.iter().sum::<f64>() / n
|
||||
};
|
||||
|
||||
let intra_variance: f64 = if weight_sum > 0.0 {
|
||||
frame.amplitudes.iter().zip(importance_weights.iter())
|
||||
.map(|(a, w)| w * (a - mean_amp).powi(2)).sum::<f64>() / weight_sum
|
||||
} else {
|
||||
frame.amplitudes.iter().map(|a| (a - mean_amp).powi(2)).sum::<f64>() / n
|
||||
};
|
||||
|
||||
let sub_variances = compute_subcarrier_variances(frame_history, n_sub);
|
||||
let temporal_variance: f64 = if sub_variances.is_empty() {
|
||||
intra_variance
|
||||
} else {
|
||||
sub_variances.iter().sum::<f64>() / sub_variances.len() as f64
|
||||
};
|
||||
let variance = intra_variance.max(temporal_variance);
|
||||
|
||||
let spectral_power: f64 = frame.amplitudes.iter().map(|a| a * a).sum::<f64>() / n;
|
||||
let half = frame.amplitudes.len() / 2;
|
||||
let motion_band_power = if half > 0 {
|
||||
frame.amplitudes[half..].iter().map(|a| (a - mean_amp).powi(2)).sum::<f64>()
|
||||
/ (frame.amplitudes.len() - half) as f64
|
||||
} else { 0.0 };
|
||||
let breathing_band_power = if half > 0 {
|
||||
frame.amplitudes[..half].iter().map(|a| (a - mean_amp).powi(2)).sum::<f64>() / half as f64
|
||||
} else { 0.0 };
|
||||
|
||||
let peak_idx = frame.amplitudes.iter().enumerate()
|
||||
.max_by(|a, b| a.1.partial_cmp(b.1).unwrap_or(std::cmp::Ordering::Equal))
|
||||
.map(|(i, _)| i).unwrap_or(0);
|
||||
let dominant_freq_hz = peak_idx as f64 * 0.05;
|
||||
|
||||
let threshold = mean_amp * 1.2;
|
||||
let change_points = frame.amplitudes.windows(2)
|
||||
.filter(|w| (w[0] < threshold) != (w[1] < threshold)).count();
|
||||
|
||||
let temporal_motion_score = if let Some(prev_frame) = frame_history.back() {
|
||||
let n_cmp = n_sub.min(prev_frame.len());
|
||||
if n_cmp > 0 {
|
||||
let diff_energy: f64 = (0..n_cmp)
|
||||
.map(|k| (frame.amplitudes[k] - prev_frame[k]).powi(2)).sum::<f64>() / n_cmp as f64;
|
||||
let ref_energy = mean_amp * mean_amp + 1e-9;
|
||||
(diff_energy / ref_energy).sqrt().clamp(0.0, 1.0)
|
||||
} else { 0.0 }
|
||||
} else {
|
||||
(intra_variance / (mean_amp * mean_amp + 1e-9)).sqrt().clamp(0.0, 1.0)
|
||||
};
|
||||
|
||||
let variance_motion = (temporal_variance / 10.0).clamp(0.0, 1.0);
|
||||
let mbp_motion = (motion_band_power / 25.0).clamp(0.0, 1.0);
|
||||
let cp_motion = (change_points as f64 / 15.0).clamp(0.0, 1.0);
|
||||
let motion_score = (temporal_motion_score * 0.4 + variance_motion * 0.2
|
||||
+ mbp_motion * 0.25 + cp_motion * 0.15).clamp(0.0, 1.0);
|
||||
|
||||
let snr_db = (frame.rssi as f64 - frame.noise_floor as f64).max(0.0);
|
||||
let snr_quality = (snr_db / 40.0).clamp(0.0, 1.0);
|
||||
let stability = (1.0 - (temporal_variance / (mean_amp * mean_amp + 1e-9)).clamp(0.0, 1.0)).max(0.0);
|
||||
let signal_quality = (snr_quality * 0.6 + stability * 0.4).clamp(0.0, 1.0);
|
||||
|
||||
let breathing_rate_hz = estimate_breathing_rate_hz(frame_history, sample_rate_hz);
|
||||
|
||||
let features = FeatureInfo {
|
||||
mean_rssi, variance, motion_band_power, breathing_band_power,
|
||||
dominant_freq_hz, change_points, spectral_power,
|
||||
};
|
||||
|
||||
let raw_classification = ClassificationInfo {
|
||||
motion_level: raw_classify(motion_score),
|
||||
presence: motion_score > 0.04,
|
||||
confidence: (0.4 + signal_quality * 0.3 + motion_score * 0.3).clamp(0.0, 1.0),
|
||||
};
|
||||
|
||||
(features, raw_classification, breathing_rate_hz, sub_variances, motion_score)
|
||||
}
|
||||
|
||||
// ── Classification ──────────────────────────────────────────────────────────
|
||||
|
||||
pub fn raw_classify(score: f64) -> String {
|
||||
if score > 0.25 { "active".into() }
|
||||
else if score > 0.12 { "present_moving".into() }
|
||||
else if score > 0.04 { "present_still".into() }
|
||||
else { "absent".into() }
|
||||
}
|
||||
|
||||
pub fn smooth_and_classify(state: &mut AppStateInner, raw: &mut ClassificationInfo, raw_motion: f64) {
|
||||
state.baseline_frames += 1;
|
||||
if state.baseline_frames < BASELINE_WARMUP {
|
||||
state.baseline_motion = state.baseline_motion * 0.9 + raw_motion * 0.1;
|
||||
} else if raw_motion < state.smoothed_motion + 0.05 {
|
||||
state.baseline_motion = state.baseline_motion * (1.0 - BASELINE_EMA_ALPHA)
|
||||
+ raw_motion * BASELINE_EMA_ALPHA;
|
||||
}
|
||||
let adjusted = (raw_motion - state.baseline_motion * 0.7).max(0.0);
|
||||
state.smoothed_motion = state.smoothed_motion * (1.0 - MOTION_EMA_ALPHA) + adjusted * MOTION_EMA_ALPHA;
|
||||
let sm = state.smoothed_motion;
|
||||
let candidate = raw_classify(sm);
|
||||
if candidate == state.current_motion_level {
|
||||
state.debounce_counter = 0;
|
||||
state.debounce_candidate = candidate;
|
||||
} else if candidate == state.debounce_candidate {
|
||||
state.debounce_counter += 1;
|
||||
if state.debounce_counter >= DEBOUNCE_FRAMES {
|
||||
state.current_motion_level = candidate;
|
||||
state.debounce_counter = 0;
|
||||
}
|
||||
} else {
|
||||
state.debounce_candidate = candidate;
|
||||
state.debounce_counter = 1;
|
||||
}
|
||||
raw.motion_level = state.current_motion_level.clone();
|
||||
raw.presence = sm > 0.03;
|
||||
raw.confidence = (0.4 + sm * 0.6).clamp(0.0, 1.0);
|
||||
}
|
||||
|
||||
pub fn smooth_and_classify_node(ns: &mut NodeState, raw: &mut ClassificationInfo, raw_motion: f64) {
|
||||
ns.baseline_frames += 1;
|
||||
if ns.baseline_frames < BASELINE_WARMUP {
|
||||
ns.baseline_motion = ns.baseline_motion * 0.9 + raw_motion * 0.1;
|
||||
} else if raw_motion < ns.smoothed_motion + 0.05 {
|
||||
ns.baseline_motion = ns.baseline_motion * (1.0 - BASELINE_EMA_ALPHA) + raw_motion * BASELINE_EMA_ALPHA;
|
||||
}
|
||||
let adjusted = (raw_motion - ns.baseline_motion * 0.7).max(0.0);
|
||||
ns.smoothed_motion = ns.smoothed_motion * (1.0 - MOTION_EMA_ALPHA) + adjusted * MOTION_EMA_ALPHA;
|
||||
let sm = ns.smoothed_motion;
|
||||
let candidate = raw_classify(sm);
|
||||
if candidate == ns.current_motion_level {
|
||||
ns.debounce_counter = 0;
|
||||
ns.debounce_candidate = candidate;
|
||||
} else if candidate == ns.debounce_candidate {
|
||||
ns.debounce_counter += 1;
|
||||
if ns.debounce_counter >= DEBOUNCE_FRAMES {
|
||||
ns.current_motion_level = candidate;
|
||||
ns.debounce_counter = 0;
|
||||
}
|
||||
} else {
|
||||
ns.debounce_candidate = candidate;
|
||||
ns.debounce_counter = 1;
|
||||
}
|
||||
raw.motion_level = ns.current_motion_level.clone();
|
||||
raw.presence = sm > 0.03;
|
||||
raw.confidence = (0.4 + sm * 0.6).clamp(0.0, 1.0);
|
||||
}
|
||||
|
||||
pub fn adaptive_override(state: &AppStateInner, features: &FeatureInfo, classification: &mut ClassificationInfo) {
|
||||
if let Some(ref model) = state.adaptive_model {
|
||||
let amps = state.frame_history.back().map(|v| v.as_slice()).unwrap_or(&[]);
|
||||
let feat_arr = adaptive_classifier::features_from_runtime(
|
||||
&serde_json::json!({
|
||||
"variance": features.variance,
|
||||
"motion_band_power": features.motion_band_power,
|
||||
"breathing_band_power": features.breathing_band_power,
|
||||
"spectral_power": features.spectral_power,
|
||||
"dominant_freq_hz": features.dominant_freq_hz,
|
||||
"change_points": features.change_points,
|
||||
"mean_rssi": features.mean_rssi,
|
||||
}),
|
||||
amps,
|
||||
);
|
||||
let (label, conf) = model.classify(&feat_arr);
|
||||
classification.motion_level = label.to_string();
|
||||
classification.presence = label != "absent";
|
||||
classification.confidence = (conf * 0.7 + classification.confidence * 0.3).clamp(0.0, 1.0);
|
||||
}
|
||||
}
|
||||
|
||||
// ── Vital signs smoothing ───────────────────────────────────────────────────
|
||||
|
||||
fn trimmed_mean(buf: &VecDeque<f64>) -> f64 {
|
||||
if buf.is_empty() { return 0.0; }
|
||||
let mut sorted: Vec<f64> = buf.iter().copied().collect();
|
||||
sorted.sort_by(|a, b| a.partial_cmp(b).unwrap_or(std::cmp::Ordering::Equal));
|
||||
let n = sorted.len();
|
||||
let trim = n / 4;
|
||||
let middle = &sorted[trim..n - trim.max(0)];
|
||||
if middle.is_empty() { sorted[n / 2] } else { middle.iter().sum::<f64>() / middle.len() as f64 }
|
||||
}
|
||||
|
||||
pub fn smooth_vitals(state: &mut AppStateInner, raw: &VitalSigns) -> VitalSigns {
|
||||
let raw_hr = raw.heart_rate_bpm.unwrap_or(0.0);
|
||||
let raw_br = raw.breathing_rate_bpm.unwrap_or(0.0);
|
||||
let hr_ok = state.smoothed_hr < 1.0 || (raw_hr - state.smoothed_hr).abs() < HR_MAX_JUMP;
|
||||
let br_ok = state.smoothed_br < 1.0 || (raw_br - state.smoothed_br).abs() < BR_MAX_JUMP;
|
||||
if hr_ok && raw_hr > 0.0 {
|
||||
state.hr_buffer.push_back(raw_hr);
|
||||
if state.hr_buffer.len() > VITAL_MEDIAN_WINDOW { state.hr_buffer.pop_front(); }
|
||||
}
|
||||
if br_ok && raw_br > 0.0 {
|
||||
state.br_buffer.push_back(raw_br);
|
||||
if state.br_buffer.len() > VITAL_MEDIAN_WINDOW { state.br_buffer.pop_front(); }
|
||||
}
|
||||
let trimmed_hr = trimmed_mean(&state.hr_buffer);
|
||||
let trimmed_br = trimmed_mean(&state.br_buffer);
|
||||
if trimmed_hr > 0.0 {
|
||||
if state.smoothed_hr < 1.0 { state.smoothed_hr = trimmed_hr; }
|
||||
else if (trimmed_hr - state.smoothed_hr).abs() > HR_DEAD_BAND {
|
||||
state.smoothed_hr = state.smoothed_hr * (1.0 - VITAL_EMA_ALPHA) + trimmed_hr * VITAL_EMA_ALPHA;
|
||||
}
|
||||
}
|
||||
if trimmed_br > 0.0 {
|
||||
if state.smoothed_br < 1.0 { state.smoothed_br = trimmed_br; }
|
||||
else if (trimmed_br - state.smoothed_br).abs() > BR_DEAD_BAND {
|
||||
state.smoothed_br = state.smoothed_br * (1.0 - VITAL_EMA_ALPHA) + trimmed_br * VITAL_EMA_ALPHA;
|
||||
}
|
||||
}
|
||||
state.smoothed_hr_conf = state.smoothed_hr_conf * 0.92 + raw.heartbeat_confidence * 0.08;
|
||||
state.smoothed_br_conf = state.smoothed_br_conf * 0.92 + raw.breathing_confidence * 0.08;
|
||||
VitalSigns {
|
||||
breathing_rate_bpm: if state.smoothed_br > 1.0 { Some(state.smoothed_br) } else { None },
|
||||
heart_rate_bpm: if state.smoothed_hr > 1.0 { Some(state.smoothed_hr) } else { None },
|
||||
breathing_confidence: state.smoothed_br_conf,
|
||||
heartbeat_confidence: state.smoothed_hr_conf,
|
||||
signal_quality: raw.signal_quality,
|
||||
}
|
||||
}
|
||||
|
||||
pub fn smooth_vitals_node(ns: &mut NodeState, raw: &VitalSigns) -> VitalSigns {
|
||||
let raw_hr = raw.heart_rate_bpm.unwrap_or(0.0);
|
||||
let raw_br = raw.breathing_rate_bpm.unwrap_or(0.0);
|
||||
let hr_ok = ns.smoothed_hr < 1.0 || (raw_hr - ns.smoothed_hr).abs() < HR_MAX_JUMP;
|
||||
let br_ok = ns.smoothed_br < 1.0 || (raw_br - ns.smoothed_br).abs() < BR_MAX_JUMP;
|
||||
if hr_ok && raw_hr > 0.0 {
|
||||
ns.hr_buffer.push_back(raw_hr);
|
||||
if ns.hr_buffer.len() > VITAL_MEDIAN_WINDOW { ns.hr_buffer.pop_front(); }
|
||||
}
|
||||
if br_ok && raw_br > 0.0 {
|
||||
ns.br_buffer.push_back(raw_br);
|
||||
if ns.br_buffer.len() > VITAL_MEDIAN_WINDOW { ns.br_buffer.pop_front(); }
|
||||
}
|
||||
let trimmed_hr = trimmed_mean(&ns.hr_buffer);
|
||||
let trimmed_br = trimmed_mean(&ns.br_buffer);
|
||||
if trimmed_hr > 0.0 {
|
||||
if ns.smoothed_hr < 1.0 { ns.smoothed_hr = trimmed_hr; }
|
||||
else if (trimmed_hr - ns.smoothed_hr).abs() > HR_DEAD_BAND {
|
||||
ns.smoothed_hr = ns.smoothed_hr * (1.0 - VITAL_EMA_ALPHA) + trimmed_hr * VITAL_EMA_ALPHA;
|
||||
}
|
||||
}
|
||||
if trimmed_br > 0.0 {
|
||||
if ns.smoothed_br < 1.0 { ns.smoothed_br = trimmed_br; }
|
||||
else if (trimmed_br - ns.smoothed_br).abs() > BR_DEAD_BAND {
|
||||
ns.smoothed_br = ns.smoothed_br * (1.0 - VITAL_EMA_ALPHA) + trimmed_br * VITAL_EMA_ALPHA;
|
||||
}
|
||||
}
|
||||
ns.smoothed_hr_conf = ns.smoothed_hr_conf * 0.92 + raw.heartbeat_confidence * 0.08;
|
||||
ns.smoothed_br_conf = ns.smoothed_br_conf * 0.92 + raw.breathing_confidence * 0.08;
|
||||
VitalSigns {
|
||||
breathing_rate_bpm: if ns.smoothed_br > 1.0 { Some(ns.smoothed_br) } else { None },
|
||||
heart_rate_bpm: if ns.smoothed_hr > 1.0 { Some(ns.smoothed_hr) } else { None },
|
||||
breathing_confidence: ns.smoothed_br_conf,
|
||||
heartbeat_confidence: ns.smoothed_hr_conf,
|
||||
signal_quality: raw.signal_quality,
|
||||
}
|
||||
}
|
||||
|
||||
// ── Multi-person estimation ─────────────────────────────────────────────────
|
||||
|
||||
pub fn fuse_multi_node_features(
|
||||
current_features: &FeatureInfo, node_states: &HashMap<u8, NodeState>,
|
||||
) -> FeatureInfo {
|
||||
let now = std::time::Instant::now();
|
||||
let active: Vec<(&FeatureInfo, f64)> = node_states.values()
|
||||
.filter(|ns| ns.last_frame_time.map_or(false, |t| now.duration_since(t).as_secs() < 10))
|
||||
.filter_map(|ns| {
|
||||
let feat = ns.latest_features.as_ref()?;
|
||||
let rssi = ns.rssi_history.back().copied().unwrap_or(-80.0);
|
||||
Some((feat, rssi))
|
||||
})
|
||||
.collect();
|
||||
|
||||
if active.len() <= 1 { return current_features.clone(); }
|
||||
|
||||
let max_rssi = active.iter().map(|(_, r)| *r).fold(f64::NEG_INFINITY, f64::max);
|
||||
let weights: Vec<f64> = active.iter()
|
||||
.map(|(_, r)| (1.0 + (r - max_rssi + 20.0) / 20.0).clamp(0.1, 1.0)).collect();
|
||||
let w_sum: f64 = weights.iter().sum::<f64>().max(1e-9);
|
||||
|
||||
FeatureInfo {
|
||||
variance: active.iter().zip(&weights).map(|((f, _), w)| f.variance * w).sum::<f64>() / w_sum,
|
||||
motion_band_power: active.iter().zip(&weights).map(|((f, _), w)| f.motion_band_power * w).sum::<f64>() / w_sum,
|
||||
breathing_band_power: active.iter().zip(&weights).map(|((f, _), w)| f.breathing_band_power * w).sum::<f64>() / w_sum,
|
||||
spectral_power: active.iter().zip(&weights).map(|((f, _), w)| f.spectral_power * w).sum::<f64>() / w_sum,
|
||||
dominant_freq_hz: active.iter().zip(&weights).map(|((f, _), w)| f.dominant_freq_hz * w).sum::<f64>() / w_sum,
|
||||
change_points: current_features.change_points,
|
||||
mean_rssi: active.iter().map(|(f, _)| f.mean_rssi).fold(f64::NEG_INFINITY, f64::max),
|
||||
}
|
||||
}
|
||||
|
||||
pub fn compute_person_score(feat: &FeatureInfo) -> f64 {
|
||||
let var_norm = (feat.variance / 300.0).clamp(0.0, 1.0);
|
||||
let cp_norm = (feat.change_points as f64 / 30.0).clamp(0.0, 1.0);
|
||||
let motion_norm = (feat.motion_band_power / 250.0).clamp(0.0, 1.0);
|
||||
let sp_norm = (feat.spectral_power / 500.0).clamp(0.0, 1.0);
|
||||
var_norm * 0.40 + cp_norm * 0.20 + motion_norm * 0.25 + sp_norm * 0.15
|
||||
}
|
||||
|
||||
pub fn estimate_persons_from_correlation(frame_history: &VecDeque<Vec<f64>>) -> usize {
|
||||
let n_frames = frame_history.len();
|
||||
if n_frames < 10 { return 1; }
|
||||
|
||||
let window: Vec<&Vec<f64>> = frame_history.iter().rev().take(20).collect();
|
||||
let n_sub = window[0].len().min(56);
|
||||
if n_sub < 4 { return 1; }
|
||||
let k = window.len() as f64;
|
||||
|
||||
let mut means = vec![0.0f64; n_sub];
|
||||
let mut variances = vec![0.0f64; n_sub];
|
||||
for frame in &window {
|
||||
for sc in 0..n_sub.min(frame.len()) { means[sc] += frame[sc] / k; }
|
||||
}
|
||||
for frame in &window {
|
||||
for sc in 0..n_sub.min(frame.len()) { variances[sc] += (frame[sc] - means[sc]).powi(2) / k; }
|
||||
}
|
||||
|
||||
let noise_floor = 1.0;
|
||||
let active: Vec<usize> = (0..n_sub).filter(|&sc| variances[sc] > noise_floor).collect();
|
||||
let m = active.len();
|
||||
if m < 3 { return if m == 0 { 0 } else { 1 }; }
|
||||
|
||||
let mut edges: Vec<(u64, u64, f64)> = Vec::new();
|
||||
let source = m as u64;
|
||||
let sink = (m + 1) as u64;
|
||||
let stds: Vec<f64> = active.iter().map(|&sc| variances[sc].sqrt().max(1e-9)).collect();
|
||||
|
||||
for i in 0..m {
|
||||
for j in (i + 1)..m {
|
||||
let mut cov = 0.0f64;
|
||||
for frame in &window {
|
||||
let (si, sj) = (active[i], active[j]);
|
||||
if si < frame.len() && sj < frame.len() {
|
||||
cov += (frame[si] - means[si]) * (frame[sj] - means[sj]) / k;
|
||||
}
|
||||
}
|
||||
let corr = (cov / (stds[i] * stds[j])).abs();
|
||||
if corr > 0.1 {
|
||||
let weight = corr * 10.0;
|
||||
edges.push((i as u64, j as u64, weight));
|
||||
edges.push((j as u64, i as u64, weight));
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
let (max_var_idx, _) = active.iter().enumerate()
|
||||
.max_by(|(_, &a), (_, &b)| variances[a].partial_cmp(&variances[b]).unwrap())
|
||||
.unwrap_or((0, &0));
|
||||
let (min_var_idx, _) = active.iter().enumerate()
|
||||
.min_by(|(_, &a), (_, &b)| variances[a].partial_cmp(&variances[b]).unwrap())
|
||||
.unwrap_or((0, &0));
|
||||
if max_var_idx == min_var_idx { return 1; }
|
||||
|
||||
edges.push((source, max_var_idx as u64, 100.0));
|
||||
edges.push((min_var_idx as u64, sink, 100.0));
|
||||
|
||||
let mc: DynamicMinCut = match MinCutBuilder::new().exact().with_edges(edges.clone()).build() {
|
||||
Ok(mc) => mc,
|
||||
Err(_) => return 1,
|
||||
};
|
||||
|
||||
let cut_value = mc.min_cut_value();
|
||||
let total_edge_weight: f64 = edges.iter()
|
||||
.filter(|(s, t, _)| *s != source && *s != sink && *t != source && *t != sink)
|
||||
.map(|(_, _, w)| w).sum::<f64>() / 2.0;
|
||||
if total_edge_weight < 1e-9 { return 1; }
|
||||
|
||||
let cut_ratio = cut_value / total_edge_weight;
|
||||
if cut_ratio > 0.4 { 1 }
|
||||
else if cut_ratio > 0.15 { 2 }
|
||||
else { 3 }
|
||||
}
|
||||
|
||||
pub fn score_to_person_count(smoothed_score: f64, prev_count: usize) -> usize {
|
||||
match prev_count {
|
||||
0 | 1 => {
|
||||
if smoothed_score > 0.85 { 3 }
|
||||
else if smoothed_score > 0.70 { 2 }
|
||||
else { 1 }
|
||||
}
|
||||
2 => {
|
||||
if smoothed_score > 0.92 { 3 }
|
||||
else if smoothed_score < 0.55 { 1 }
|
||||
else { 2 }
|
||||
}
|
||||
_ => {
|
||||
if smoothed_score < 0.55 { 1 }
|
||||
else if smoothed_score < 0.78 { 2 }
|
||||
else { 3 }
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// Generate a simulated ESP32 frame for testing/demo mode.
|
||||
pub fn generate_simulated_frame(tick: u64) -> Esp32Frame {
|
||||
let t = tick as f64 * 0.1;
|
||||
let n_sub = 56usize;
|
||||
let mut amplitudes = Vec::with_capacity(n_sub);
|
||||
let mut phases = Vec::with_capacity(n_sub);
|
||||
for i in 0..n_sub {
|
||||
let base = 15.0 + 5.0 * (i as f64 * 0.1 + t * 0.3).sin();
|
||||
let noise = (i as f64 * 7.3 + t * 13.7).sin() * 2.0;
|
||||
amplitudes.push((base + noise).max(0.1));
|
||||
phases.push((i as f64 * 0.2 + t * 0.5).sin() * std::f64::consts::PI);
|
||||
}
|
||||
Esp32Frame {
|
||||
magic: 0xC511_0001, node_id: 1, n_antennas: 1, n_subcarriers: n_sub as u8,
|
||||
freq_mhz: 2437, sequence: tick as u32,
|
||||
rssi: (-40.0 + 5.0 * (t * 0.2).sin()) as i8, noise_floor: -90,
|
||||
amplitudes, phases,
|
||||
}
|
||||
}
|
||||
|
||||
/// Generate a simple timestamp (epoch seconds) for recording IDs.
|
||||
pub fn chrono_timestamp() -> u64 {
|
||||
std::time::SystemTime::now()
|
||||
.duration_since(std::time::UNIX_EPOCH)
|
||||
.map(|d| d.as_secs())
|
||||
.unwrap_or(0)
|
||||
}
|
||||
|
|
@ -9,11 +9,15 @@
|
|||
//! Replaces both ws_server.py and the Python HTTP server.
|
||||
|
||||
mod adaptive_classifier;
|
||||
pub mod cli;
|
||||
pub mod csi;
|
||||
mod field_bridge;
|
||||
mod multistatic_bridge;
|
||||
pub mod pose;
|
||||
mod rvf_container;
|
||||
mod rvf_pipeline;
|
||||
mod tracker_bridge;
|
||||
pub mod types;
|
||||
mod vital_signs;
|
||||
|
||||
// Training pipeline modules (exposed via lib.rs)
|
||||
|
|
|
|||
|
|
@ -0,0 +1,194 @@
|
|||
//! Skeleton derivation, pose estimation, and temporal smoothing.
|
||||
|
||||
use crate::types::*;
|
||||
|
||||
/// Expected bone lengths in pixel-space for the COCO-17 skeleton.
|
||||
pub const POSE_BONE_PAIRS: &[(usize, usize)] = &[
|
||||
(5, 7), (7, 9), (6, 8), (8, 10),
|
||||
(5, 11), (6, 12),
|
||||
(11, 13), (13, 15), (12, 14), (14, 16),
|
||||
(5, 6), (11, 12),
|
||||
];
|
||||
|
||||
const TORSO_KP: [usize; 4] = [5, 6, 11, 12];
|
||||
const EXTREMITY_KP: [usize; 4] = [9, 10, 15, 16];
|
||||
|
||||
pub fn derive_single_person_pose(
|
||||
update: &SensingUpdate, person_idx: usize, total_persons: usize,
|
||||
) -> PersonDetection {
|
||||
let cls = &update.classification;
|
||||
let feat = &update.features;
|
||||
|
||||
let phase_offset = person_idx as f64 * 2.094;
|
||||
let half = (total_persons as f64 - 1.0) / 2.0;
|
||||
let person_x_offset = (person_idx as f64 - half) * 120.0;
|
||||
let conf_decay = 1.0 - person_idx as f64 * 0.15;
|
||||
|
||||
let motion_score = (feat.motion_band_power / 15.0).clamp(0.0, 1.0);
|
||||
let is_walking = motion_score > 0.55;
|
||||
let breath_amp = (feat.breathing_band_power * 4.0).clamp(0.0, 12.0);
|
||||
|
||||
let breath_phase = if let Some(ref vs) = update.vital_signs {
|
||||
let bpm = vs.breathing_rate_bpm.unwrap_or(15.0);
|
||||
let freq = (bpm / 60.0).clamp(0.1, 0.5);
|
||||
(update.tick as f64 * freq * 0.02 * std::f64::consts::TAU + phase_offset).sin()
|
||||
} else {
|
||||
(update.tick as f64 * 0.02 + phase_offset).sin()
|
||||
};
|
||||
|
||||
let lean_x = (feat.dominant_freq_hz / 5.0 - 1.0).clamp(-1.0, 1.0) * 18.0;
|
||||
let stride_x = if is_walking {
|
||||
let stride_phase = (feat.motion_band_power * 0.7 + update.tick as f64 * 0.06 + phase_offset).sin();
|
||||
stride_phase * 20.0 * motion_score
|
||||
} else { 0.0 };
|
||||
|
||||
let burst = (feat.change_points as f64 / 20.0).clamp(0.0, 0.3);
|
||||
let noise_seed = person_idx as f64 * 97.1;
|
||||
let noise_val = (noise_seed.sin() * 43758.545).fract();
|
||||
let snr_factor = ((feat.variance - 0.5) / 10.0).clamp(0.0, 1.0);
|
||||
let base_confidence = cls.confidence * (0.6 + 0.4 * snr_factor) * conf_decay;
|
||||
|
||||
let base_x = 320.0 + stride_x + lean_x * 0.5 + person_x_offset;
|
||||
let base_y = 240.0 - motion_score * 8.0;
|
||||
|
||||
let kp_names = [
|
||||
"nose", "left_eye", "right_eye", "left_ear", "right_ear",
|
||||
"left_shoulder", "right_shoulder", "left_elbow", "right_elbow",
|
||||
"left_wrist", "right_wrist", "left_hip", "right_hip",
|
||||
"left_knee", "right_knee", "left_ankle", "right_ankle",
|
||||
];
|
||||
|
||||
let kp_offsets: [(f64, f64); 17] = [
|
||||
(0.0, -80.0), (-8.0, -88.0), (8.0, -88.0), (-16.0, -82.0), (16.0, -82.0),
|
||||
(-30.0, -50.0), (30.0, -50.0), (-45.0, -15.0), (45.0, -15.0),
|
||||
(-50.0, 20.0), (50.0, 20.0), (-20.0, 20.0), (20.0, 20.0),
|
||||
(-22.0, 70.0), (22.0, 70.0), (-24.0, 120.0), (24.0, 120.0),
|
||||
];
|
||||
|
||||
let keypoints: Vec<PoseKeypoint> = kp_names.iter().zip(kp_offsets.iter())
|
||||
.enumerate()
|
||||
.map(|(i, (name, (dx, dy)))| {
|
||||
let breath_dx = if TORSO_KP.contains(&i) {
|
||||
let sign = if *dx < 0.0 { -1.0 } else { 1.0 };
|
||||
sign * breath_amp * breath_phase * 0.5
|
||||
} else { 0.0 };
|
||||
let breath_dy = if TORSO_KP.contains(&i) {
|
||||
let sign = if *dy < 0.0 { -1.0 } else { 1.0 };
|
||||
sign * breath_amp * breath_phase * 0.3
|
||||
} else { 0.0 };
|
||||
|
||||
let extremity_jitter = if EXTREMITY_KP.contains(&i) {
|
||||
let phase = noise_seed + i as f64 * 2.399;
|
||||
(phase.sin() * burst * motion_score * 4.0, (phase * 1.31).cos() * burst * motion_score * 3.0)
|
||||
} else { (0.0, 0.0) };
|
||||
|
||||
let kp_noise_x = ((noise_seed + i as f64 * 1.618).sin() * 43758.545).fract()
|
||||
* feat.variance.sqrt().clamp(0.0, 3.0) * motion_score;
|
||||
let kp_noise_y = ((noise_seed + i as f64 * 2.718).cos() * 31415.926).fract()
|
||||
* feat.variance.sqrt().clamp(0.0, 3.0) * motion_score * 0.6;
|
||||
|
||||
let swing_dy = if is_walking {
|
||||
let stride_phase = (feat.motion_band_power * 0.7 + update.tick as f64 * 0.12 + phase_offset).sin();
|
||||
match i {
|
||||
7 | 9 => -stride_phase * 20.0 * motion_score,
|
||||
8 | 10 => stride_phase * 20.0 * motion_score,
|
||||
13 | 15 => stride_phase * 25.0 * motion_score,
|
||||
14 | 16 => -stride_phase * 25.0 * motion_score,
|
||||
_ => 0.0,
|
||||
}
|
||||
} else { 0.0 };
|
||||
|
||||
let final_x = base_x + dx + breath_dx + extremity_jitter.0 + kp_noise_x;
|
||||
let final_y = base_y + dy + breath_dy + extremity_jitter.1 + kp_noise_y + swing_dy;
|
||||
|
||||
let kp_conf = if EXTREMITY_KP.contains(&i) {
|
||||
base_confidence * (0.7 + 0.3 * snr_factor) * (0.85 + 0.15 * noise_val)
|
||||
} else {
|
||||
base_confidence * (0.88 + 0.12 * ((i as f64 * 0.7 + noise_seed).cos()))
|
||||
};
|
||||
|
||||
PoseKeypoint { name: name.to_string(), x: final_x, y: final_y, z: lean_x * 0.02, confidence: kp_conf.clamp(0.1, 1.0) }
|
||||
})
|
||||
.collect();
|
||||
|
||||
let xs: Vec<f64> = keypoints.iter().map(|k| k.x).collect();
|
||||
let ys: Vec<f64> = keypoints.iter().map(|k| k.y).collect();
|
||||
let min_x = xs.iter().cloned().fold(f64::MAX, f64::min) - 10.0;
|
||||
let min_y = ys.iter().cloned().fold(f64::MAX, f64::min) - 10.0;
|
||||
let max_x = xs.iter().cloned().fold(f64::MIN, f64::max) + 10.0;
|
||||
let max_y = ys.iter().cloned().fold(f64::MIN, f64::max) + 10.0;
|
||||
|
||||
PersonDetection {
|
||||
id: (person_idx + 1) as u32,
|
||||
confidence: cls.confidence * conf_decay,
|
||||
keypoints,
|
||||
bbox: BoundingBox { x: min_x, y: min_y, width: (max_x - min_x).max(80.0), height: (max_y - min_y).max(160.0) },
|
||||
zone: format!("zone_{}", person_idx + 1),
|
||||
}
|
||||
}
|
||||
|
||||
pub fn derive_pose_from_sensing(update: &SensingUpdate) -> Vec<PersonDetection> {
|
||||
let cls = &update.classification;
|
||||
if !cls.presence { return vec![]; }
|
||||
let person_count = update.estimated_persons.unwrap_or(1).max(1);
|
||||
(0..person_count).map(|idx| derive_single_person_pose(update, idx, person_count)).collect()
|
||||
}
|
||||
|
||||
/// Apply temporal EMA smoothing and bone-length clamping to person detections.
|
||||
pub fn apply_temporal_smoothing(persons: &mut [PersonDetection], ns: &mut NodeState) {
|
||||
if persons.is_empty() { return; }
|
||||
|
||||
let alpha = ns.ema_alpha();
|
||||
let person = &mut persons[0];
|
||||
|
||||
let current_kps: Vec<[f64; 3]> = person.keypoints.iter()
|
||||
.map(|kp| [kp.x, kp.y, kp.z]).collect();
|
||||
|
||||
let smoothed = if let Some(ref prev) = ns.prev_keypoints {
|
||||
let mut out = Vec::with_capacity(current_kps.len());
|
||||
for (cur, prv) in current_kps.iter().zip(prev.iter()) {
|
||||
out.push([
|
||||
alpha * cur[0] + (1.0 - alpha) * prv[0],
|
||||
alpha * cur[1] + (1.0 - alpha) * prv[1],
|
||||
alpha * cur[2] + (1.0 - alpha) * prv[2],
|
||||
]);
|
||||
}
|
||||
clamp_bone_lengths_f64(&mut out, prev);
|
||||
out
|
||||
} else {
|
||||
current_kps.clone()
|
||||
};
|
||||
|
||||
for (kp, s) in person.keypoints.iter_mut().zip(smoothed.iter()) {
|
||||
kp.x = s[0]; kp.y = s[1]; kp.z = s[2];
|
||||
}
|
||||
ns.prev_keypoints = Some(smoothed);
|
||||
}
|
||||
|
||||
fn clamp_bone_lengths_f64(pose: &mut Vec<[f64; 3]>, prev: &[[f64; 3]]) {
|
||||
for &(p, c) in POSE_BONE_PAIRS {
|
||||
if p >= pose.len() || c >= pose.len() { continue; }
|
||||
let prev_len = dist_f64(&prev[p], &prev[c]);
|
||||
if prev_len < 1e-6 { continue; }
|
||||
let cur_len = dist_f64(&pose[p], &pose[c]);
|
||||
if cur_len < 1e-6 { continue; }
|
||||
let ratio = cur_len / prev_len;
|
||||
let lo = 1.0 - MAX_BONE_CHANGE_RATIO;
|
||||
let hi = 1.0 + MAX_BONE_CHANGE_RATIO;
|
||||
if ratio < lo || ratio > hi {
|
||||
let target = prev_len * ratio.clamp(lo, hi);
|
||||
let scale = target / cur_len;
|
||||
for dim in 0..3 {
|
||||
let diff = pose[c][dim] - pose[p][dim];
|
||||
pose[c][dim] = pose[p][dim] + diff * scale;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
fn dist_f64(a: &[f64; 3], b: &[f64; 3]) -> f64 {
|
||||
let dx = b[0] - a[0];
|
||||
let dy = b[1] - a[1];
|
||||
let dz = b[2] - a[2];
|
||||
(dx * dx + dy * dy + dz * dz).sqrt()
|
||||
}
|
||||
|
|
@ -0,0 +1,403 @@
|
|||
//! Data types, constants, and shared state definitions.
|
||||
|
||||
use std::collections::{HashMap, VecDeque};
|
||||
use std::path::PathBuf;
|
||||
use std::sync::Arc;
|
||||
|
||||
use serde::{Deserialize, Serialize};
|
||||
use tokio::sync::{broadcast, RwLock};
|
||||
|
||||
use crate::adaptive_classifier;
|
||||
use crate::rvf_container::RvfContainerInfo;
|
||||
use crate::rvf_pipeline::ProgressiveLoader;
|
||||
use crate::vital_signs::{VitalSignDetector, VitalSigns};
|
||||
|
||||
use wifi_densepose_signal::ruvsense::pose_tracker::PoseTracker;
|
||||
use wifi_densepose_signal::ruvsense::multistatic::MultistaticFuser;
|
||||
use wifi_densepose_signal::ruvsense::field_model::FieldModel;
|
||||
|
||||
// ── Constants ───────────────────────────────────────────────────────────────
|
||||
|
||||
/// Number of frames retained in `frame_history` for temporal analysis.
|
||||
pub const FRAME_HISTORY_CAPACITY: usize = 100;
|
||||
|
||||
/// If no ESP32 frame arrives within this duration, source reverts to offline.
|
||||
pub const ESP32_OFFLINE_TIMEOUT: std::time::Duration = std::time::Duration::from_secs(5);
|
||||
|
||||
/// Default EMA alpha for temporal keypoint smoothing (RuVector Phase 2).
|
||||
pub const TEMPORAL_EMA_ALPHA_DEFAULT: f64 = 0.15;
|
||||
/// Reduced EMA alpha when coherence is low.
|
||||
pub const TEMPORAL_EMA_ALPHA_LOW_COHERENCE: f64 = 0.05;
|
||||
/// Coherence threshold below which we reduce EMA alpha.
|
||||
pub const COHERENCE_LOW_THRESHOLD: f64 = 0.3;
|
||||
/// Maximum allowed bone-length change ratio between frames (20%).
|
||||
pub const MAX_BONE_CHANGE_RATIO: f64 = 0.20;
|
||||
/// Number of motion_energy frames to track for coherence scoring.
|
||||
pub const COHERENCE_WINDOW: usize = 20;
|
||||
|
||||
/// Debounce frames required before state transition (at ~10 FPS = ~0.4s).
|
||||
pub const DEBOUNCE_FRAMES: u32 = 4;
|
||||
/// EMA alpha for motion smoothing (~1s time constant at 10 FPS).
|
||||
pub const MOTION_EMA_ALPHA: f64 = 0.15;
|
||||
/// EMA alpha for slow-adapting baseline (~30s time constant at 10 FPS).
|
||||
pub const BASELINE_EMA_ALPHA: f64 = 0.003;
|
||||
/// Number of warm-up frames before baseline subtraction kicks in.
|
||||
pub const BASELINE_WARMUP: u64 = 50;
|
||||
|
||||
/// Size of the median filter window for vital signs outlier rejection.
|
||||
pub const VITAL_MEDIAN_WINDOW: usize = 21;
|
||||
/// EMA alpha for vital signs (~5s time constant at 10 FPS).
|
||||
pub const VITAL_EMA_ALPHA: f64 = 0.02;
|
||||
/// Maximum BPM jump per frame before a value is rejected as an outlier.
|
||||
pub const HR_MAX_JUMP: f64 = 8.0;
|
||||
pub const BR_MAX_JUMP: f64 = 2.0;
|
||||
/// Minimum change from current smoothed value before EMA updates (dead-band).
|
||||
pub const HR_DEAD_BAND: f64 = 2.0;
|
||||
pub const BR_DEAD_BAND: f64 = 0.5;
|
||||
|
||||
// ── ESP32 Frame ─────────────────────────────────────────────────────────────
|
||||
|
||||
/// ADR-018 ESP32 CSI binary frame header (20 bytes)
|
||||
#[derive(Debug, Clone)]
|
||||
#[allow(dead_code)]
|
||||
pub struct Esp32Frame {
|
||||
pub magic: u32,
|
||||
pub node_id: u8,
|
||||
pub n_antennas: u8,
|
||||
pub n_subcarriers: u8,
|
||||
pub freq_mhz: u16,
|
||||
pub sequence: u32,
|
||||
pub rssi: i8,
|
||||
pub noise_floor: i8,
|
||||
pub amplitudes: Vec<f64>,
|
||||
pub phases: Vec<f64>,
|
||||
}
|
||||
|
||||
// ── Sensing Update ──────────────────────────────────────────────────────────
|
||||
|
||||
/// Sensing update broadcast to WebSocket clients
|
||||
#[derive(Debug, Clone, Serialize, Deserialize)]
|
||||
pub struct SensingUpdate {
|
||||
#[serde(rename = "type")]
|
||||
pub msg_type: String,
|
||||
pub timestamp: f64,
|
||||
pub source: String,
|
||||
pub tick: u64,
|
||||
pub nodes: Vec<NodeInfo>,
|
||||
pub features: FeatureInfo,
|
||||
pub classification: ClassificationInfo,
|
||||
pub signal_field: SignalField,
|
||||
#[serde(skip_serializing_if = "Option::is_none")]
|
||||
pub vital_signs: Option<VitalSigns>,
|
||||
#[serde(skip_serializing_if = "Option::is_none")]
|
||||
pub enhanced_motion: Option<serde_json::Value>,
|
||||
#[serde(skip_serializing_if = "Option::is_none")]
|
||||
pub enhanced_breathing: Option<serde_json::Value>,
|
||||
#[serde(skip_serializing_if = "Option::is_none")]
|
||||
pub posture: Option<String>,
|
||||
#[serde(skip_serializing_if = "Option::is_none")]
|
||||
pub signal_quality_score: Option<f64>,
|
||||
#[serde(skip_serializing_if = "Option::is_none")]
|
||||
pub quality_verdict: Option<String>,
|
||||
#[serde(skip_serializing_if = "Option::is_none")]
|
||||
pub bssid_count: Option<usize>,
|
||||
#[serde(skip_serializing_if = "Option::is_none")]
|
||||
pub pose_keypoints: Option<Vec<[f64; 4]>>,
|
||||
#[serde(skip_serializing_if = "Option::is_none")]
|
||||
pub model_status: Option<serde_json::Value>,
|
||||
#[serde(skip_serializing_if = "Option::is_none")]
|
||||
pub persons: Option<Vec<PersonDetection>>,
|
||||
#[serde(skip_serializing_if = "Option::is_none")]
|
||||
pub estimated_persons: Option<usize>,
|
||||
#[serde(skip_serializing_if = "Option::is_none")]
|
||||
pub node_features: Option<Vec<PerNodeFeatureInfo>>,
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Serialize, Deserialize)]
|
||||
pub struct NodeInfo {
|
||||
pub node_id: u8,
|
||||
pub rssi_dbm: f64,
|
||||
pub position: [f64; 3],
|
||||
pub amplitude: Vec<f64>,
|
||||
pub subcarrier_count: usize,
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Serialize, Deserialize)]
|
||||
pub struct FeatureInfo {
|
||||
pub mean_rssi: f64,
|
||||
pub variance: f64,
|
||||
pub motion_band_power: f64,
|
||||
pub breathing_band_power: f64,
|
||||
pub dominant_freq_hz: f64,
|
||||
pub change_points: usize,
|
||||
pub spectral_power: f64,
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Serialize, Deserialize)]
|
||||
pub struct ClassificationInfo {
|
||||
pub motion_level: String,
|
||||
pub presence: bool,
|
||||
pub confidence: f64,
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Serialize, Deserialize)]
|
||||
pub struct SignalField {
|
||||
pub grid_size: [usize; 3],
|
||||
pub values: Vec<f64>,
|
||||
}
|
||||
|
||||
/// WiFi-derived pose keypoint (17 COCO keypoints)
|
||||
#[derive(Debug, Clone, Serialize, Deserialize)]
|
||||
pub struct PoseKeypoint {
|
||||
pub name: String,
|
||||
pub x: f64,
|
||||
pub y: f64,
|
||||
pub z: f64,
|
||||
pub confidence: f64,
|
||||
}
|
||||
|
||||
/// Person detection from WiFi sensing
|
||||
#[derive(Debug, Clone, Serialize, Deserialize)]
|
||||
pub struct PersonDetection {
|
||||
pub id: u32,
|
||||
pub confidence: f64,
|
||||
pub keypoints: Vec<PoseKeypoint>,
|
||||
pub bbox: BoundingBox,
|
||||
pub zone: String,
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Serialize, Deserialize)]
|
||||
pub struct BoundingBox {
|
||||
pub x: f64,
|
||||
pub y: f64,
|
||||
pub width: f64,
|
||||
pub height: f64,
|
||||
}
|
||||
|
||||
/// Per-node feature info for WebSocket broadcasts (multi-node support).
|
||||
#[derive(Debug, Clone, Serialize, Deserialize)]
|
||||
pub struct PerNodeFeatureInfo {
|
||||
pub node_id: u8,
|
||||
pub features: FeatureInfo,
|
||||
pub classification: ClassificationInfo,
|
||||
pub rssi_dbm: f64,
|
||||
pub last_seen_ms: u64,
|
||||
pub frame_rate_hz: f64,
|
||||
pub stale: bool,
|
||||
}
|
||||
|
||||
// ── ESP32 Edge Vitals Packet (ADR-039) ──────────────────────────────────────
|
||||
|
||||
/// Decoded vitals packet from ESP32 edge processing pipeline.
|
||||
#[derive(Debug, Clone, Serialize)]
|
||||
pub struct Esp32VitalsPacket {
|
||||
pub node_id: u8,
|
||||
pub presence: bool,
|
||||
pub fall_detected: bool,
|
||||
pub motion: bool,
|
||||
pub breathing_rate_bpm: f64,
|
||||
pub heartrate_bpm: f64,
|
||||
pub rssi: i8,
|
||||
pub n_persons: u8,
|
||||
pub motion_energy: f32,
|
||||
pub presence_score: f32,
|
||||
pub timestamp_ms: u32,
|
||||
}
|
||||
|
||||
/// Single WASM event (type + value).
|
||||
#[derive(Debug, Clone, Serialize)]
|
||||
pub struct WasmEvent {
|
||||
pub event_type: u8,
|
||||
pub value: f32,
|
||||
}
|
||||
|
||||
/// Decoded WASM output packet from ESP32 Tier 3 runtime.
|
||||
#[derive(Debug, Clone, Serialize)]
|
||||
pub struct WasmOutputPacket {
|
||||
pub node_id: u8,
|
||||
pub module_id: u8,
|
||||
pub events: Vec<WasmEvent>,
|
||||
}
|
||||
|
||||
// ── Per-node state ──────────────────────────────────────────────────────────
|
||||
|
||||
/// Per-node sensing state for multi-node deployments (issue #249).
|
||||
pub struct NodeState {
|
||||
pub frame_history: VecDeque<Vec<f64>>,
|
||||
pub smoothed_person_score: f64,
|
||||
pub prev_person_count: usize,
|
||||
pub smoothed_motion: f64,
|
||||
pub current_motion_level: String,
|
||||
pub debounce_counter: u32,
|
||||
pub debounce_candidate: String,
|
||||
pub baseline_motion: f64,
|
||||
pub baseline_frames: u64,
|
||||
pub smoothed_hr: f64,
|
||||
pub smoothed_br: f64,
|
||||
pub smoothed_hr_conf: f64,
|
||||
pub smoothed_br_conf: f64,
|
||||
pub hr_buffer: VecDeque<f64>,
|
||||
pub br_buffer: VecDeque<f64>,
|
||||
pub rssi_history: VecDeque<f64>,
|
||||
pub vital_detector: VitalSignDetector,
|
||||
pub latest_vitals: VitalSigns,
|
||||
pub last_frame_time: Option<std::time::Instant>,
|
||||
pub edge_vitals: Option<Esp32VitalsPacket>,
|
||||
pub latest_features: Option<FeatureInfo>,
|
||||
pub prev_keypoints: Option<Vec<[f64; 3]>>,
|
||||
pub motion_energy_history: VecDeque<f64>,
|
||||
pub coherence_score: f64,
|
||||
}
|
||||
|
||||
impl NodeState {
|
||||
pub fn new() -> Self {
|
||||
Self {
|
||||
frame_history: VecDeque::new(),
|
||||
smoothed_person_score: 0.0,
|
||||
prev_person_count: 0,
|
||||
smoothed_motion: 0.0,
|
||||
current_motion_level: "absent".to_string(),
|
||||
debounce_counter: 0,
|
||||
debounce_candidate: "absent".to_string(),
|
||||
baseline_motion: 0.0,
|
||||
baseline_frames: 0,
|
||||
smoothed_hr: 0.0,
|
||||
smoothed_br: 0.0,
|
||||
smoothed_hr_conf: 0.0,
|
||||
smoothed_br_conf: 0.0,
|
||||
hr_buffer: VecDeque::with_capacity(8),
|
||||
br_buffer: VecDeque::with_capacity(8),
|
||||
rssi_history: VecDeque::new(),
|
||||
vital_detector: VitalSignDetector::new(10.0),
|
||||
latest_vitals: VitalSigns::default(),
|
||||
last_frame_time: None,
|
||||
edge_vitals: None,
|
||||
latest_features: None,
|
||||
prev_keypoints: None,
|
||||
motion_energy_history: VecDeque::with_capacity(COHERENCE_WINDOW),
|
||||
coherence_score: 1.0,
|
||||
}
|
||||
}
|
||||
|
||||
/// Update the coherence score from the latest motion_energy value.
|
||||
pub fn update_coherence(&mut self, motion_energy: f64) {
|
||||
if self.motion_energy_history.len() >= COHERENCE_WINDOW {
|
||||
self.motion_energy_history.pop_front();
|
||||
}
|
||||
self.motion_energy_history.push_back(motion_energy);
|
||||
|
||||
let n = self.motion_energy_history.len();
|
||||
if n < 2 {
|
||||
self.coherence_score = 1.0;
|
||||
return;
|
||||
}
|
||||
|
||||
let mean: f64 = self.motion_energy_history.iter().sum::<f64>() / n as f64;
|
||||
let variance: f64 = self.motion_energy_history.iter()
|
||||
.map(|v| (v - mean) * (v - mean))
|
||||
.sum::<f64>() / (n - 1) as f64;
|
||||
|
||||
self.coherence_score = (1.0 / (1.0 + variance)).clamp(0.0, 1.0);
|
||||
}
|
||||
|
||||
/// Choose the EMA alpha based on current coherence score.
|
||||
pub fn ema_alpha(&self) -> f64 {
|
||||
if self.coherence_score < COHERENCE_LOW_THRESHOLD {
|
||||
TEMPORAL_EMA_ALPHA_LOW_COHERENCE
|
||||
} else {
|
||||
TEMPORAL_EMA_ALPHA_DEFAULT
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// ── Shared application state ────────────────────────────────────────────────
|
||||
|
||||
/// Shared application state
|
||||
pub struct AppStateInner {
|
||||
pub latest_update: Option<SensingUpdate>,
|
||||
pub rssi_history: VecDeque<f64>,
|
||||
pub frame_history: VecDeque<Vec<f64>>,
|
||||
pub tick: u64,
|
||||
pub source: String,
|
||||
pub last_esp32_frame: Option<std::time::Instant>,
|
||||
pub tx: broadcast::Sender<String>,
|
||||
pub total_detections: u64,
|
||||
pub start_time: std::time::Instant,
|
||||
pub vital_detector: VitalSignDetector,
|
||||
pub latest_vitals: VitalSigns,
|
||||
pub rvf_info: Option<RvfContainerInfo>,
|
||||
pub save_rvf_path: Option<PathBuf>,
|
||||
pub progressive_loader: Option<ProgressiveLoader>,
|
||||
pub active_sona_profile: Option<String>,
|
||||
pub model_loaded: bool,
|
||||
pub smoothed_person_score: f64,
|
||||
pub prev_person_count: usize,
|
||||
pub smoothed_motion: f64,
|
||||
pub current_motion_level: String,
|
||||
pub debounce_counter: u32,
|
||||
pub debounce_candidate: String,
|
||||
pub baseline_motion: f64,
|
||||
pub baseline_frames: u64,
|
||||
pub smoothed_hr: f64,
|
||||
pub smoothed_br: f64,
|
||||
pub smoothed_hr_conf: f64,
|
||||
pub smoothed_br_conf: f64,
|
||||
pub hr_buffer: VecDeque<f64>,
|
||||
pub br_buffer: VecDeque<f64>,
|
||||
pub edge_vitals: Option<Esp32VitalsPacket>,
|
||||
pub latest_wasm_events: Option<WasmOutputPacket>,
|
||||
pub discovered_models: Vec<serde_json::Value>,
|
||||
pub active_model_id: Option<String>,
|
||||
pub recordings: Vec<serde_json::Value>,
|
||||
pub recording_active: bool,
|
||||
pub recording_start_time: Option<std::time::Instant>,
|
||||
pub recording_current_id: Option<String>,
|
||||
pub recording_stop_tx: Option<tokio::sync::watch::Sender<bool>>,
|
||||
pub training_status: String,
|
||||
pub training_config: Option<serde_json::Value>,
|
||||
pub adaptive_model: Option<adaptive_classifier::AdaptiveModel>,
|
||||
pub node_states: HashMap<u8, NodeState>,
|
||||
pub pose_tracker: PoseTracker,
|
||||
pub last_tracker_instant: Option<std::time::Instant>,
|
||||
pub multistatic_fuser: MultistaticFuser,
|
||||
pub field_model: Option<FieldModel>,
|
||||
}
|
||||
|
||||
impl AppStateInner {
|
||||
/// Return the effective data source, accounting for ESP32 frame timeout.
|
||||
pub fn effective_source(&self) -> String {
|
||||
if self.source == "esp32" {
|
||||
if let Some(last) = self.last_esp32_frame {
|
||||
if last.elapsed() > ESP32_OFFLINE_TIMEOUT {
|
||||
return "esp32:offline".to_string();
|
||||
}
|
||||
}
|
||||
}
|
||||
self.source.clone()
|
||||
}
|
||||
|
||||
/// Person count: eigenvalue-based if field model is calibrated, else heuristic.
|
||||
pub fn person_count(&self) -> usize {
|
||||
use crate::field_bridge;
|
||||
use crate::csi::score_to_person_count;
|
||||
match self.field_model.as_ref() {
|
||||
Some(fm) => {
|
||||
let history = if !self.frame_history.is_empty() {
|
||||
&self.frame_history
|
||||
} else {
|
||||
self.node_states.values()
|
||||
.filter(|ns| !ns.frame_history.is_empty())
|
||||
.max_by_key(|ns| ns.last_frame_time)
|
||||
.map(|ns| &ns.frame_history)
|
||||
.unwrap_or(&self.frame_history)
|
||||
};
|
||||
field_bridge::occupancy_or_fallback(
|
||||
fm, history, self.smoothed_person_score, self.prev_person_count,
|
||||
)
|
||||
}
|
||||
None => score_to_person_count(self.smoothed_person_score, self.prev_person_count),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
pub type SharedState = Arc<RwLock<AppStateInner>>;
|
||||
|
|
@ -339,9 +339,16 @@ impl RfTomographer {
|
|||
|
||||
/// Compute the intersection weights of a link with the voxel grid.
|
||||
///
|
||||
/// Uses a simplified approach: for each voxel, computes the minimum
|
||||
/// distance from the voxel center to the link ray. Voxels within
|
||||
/// one Fresnel zone receive weight proportional to closeness.
|
||||
/// Uses a DDA (Digital Differential Analyzer) ray-marching algorithm:
|
||||
/// 1. March along the ray from TX to RX, advancing to the nearest
|
||||
/// axis-aligned voxel boundary at each step.
|
||||
/// 2. At each ray voxel, expand by the Fresnel radius to check
|
||||
/// neighboring voxels.
|
||||
/// 3. Use a visited bitvector to avoid duplicate entries.
|
||||
/// 4. Weight = `1.0 - dist / fresnel_radius` (same as before).
|
||||
///
|
||||
/// This is O(ray_length / voxel_size) instead of O(nx*ny*nz),
|
||||
/// a significant speedup for large grids.
|
||||
fn compute_link_weights(link: &LinkGeometry, config: &TomographyConfig) -> Vec<(usize, f64)> {
|
||||
let vx = (config.bounds[3] - config.bounds[0]) / config.nx as f64;
|
||||
let vy = (config.bounds[4] - config.bounds[1]) / config.ny as f64;
|
||||
|
|
@ -356,25 +363,74 @@ fn compute_link_weights(link: &LinkGeometry, config: &TomographyConfig) -> Vec<(
|
|||
let dy = link.rx.y - link.tx.y;
|
||||
let dz = link.rx.z - link.tx.z;
|
||||
|
||||
let n_voxels = config.nx * config.ny * config.nz;
|
||||
let mut visited = vec![false; n_voxels];
|
||||
let mut weights = Vec::new();
|
||||
|
||||
for iz in 0..config.nz {
|
||||
for iy in 0..config.ny {
|
||||
for ix in 0..config.nx {
|
||||
let cx = config.bounds[0] + (ix as f64 + 0.5) * vx;
|
||||
let cy = config.bounds[1] + (iy as f64 + 0.5) * vy;
|
||||
let cz = config.bounds[2] + (iz as f64 + 0.5) * vz;
|
||||
// Fresnel expansion radius in voxel units.
|
||||
let expand_x = (fresnel_radius / vx).ceil() as isize;
|
||||
let expand_y = (fresnel_radius / vy).ceil() as isize;
|
||||
let expand_z = (fresnel_radius / vz).ceil() as isize;
|
||||
|
||||
// Point-to-line distance
|
||||
let dist = point_to_segment_distance(
|
||||
cx, cy, cz, link.tx.x, link.tx.y, link.tx.z, dx, dy, dz, link_dist,
|
||||
);
|
||||
// DDA initialization: start at TX position in voxel coordinates.
|
||||
let start_vx = (link.tx.x - config.bounds[0]) / vx;
|
||||
let start_vy = (link.tx.y - config.bounds[1]) / vy;
|
||||
let start_vz = (link.tx.z - config.bounds[2]) / vz;
|
||||
|
||||
if dist < fresnel_radius {
|
||||
// Weight decays with distance from link ray
|
||||
let w = 1.0 - dist / fresnel_radius;
|
||||
let idx = iz * config.ny * config.nx + iy * config.nx + ix;
|
||||
weights.push((idx, w));
|
||||
let end_vx = (link.rx.x - config.bounds[0]) / vx;
|
||||
let end_vy = (link.rx.y - config.bounds[1]) / vy;
|
||||
let end_vz = (link.rx.z - config.bounds[2]) / vz;
|
||||
|
||||
let ray_dx = end_vx - start_vx;
|
||||
let ray_dy = end_vy - start_vy;
|
||||
let ray_dz = end_vz - start_vz;
|
||||
|
||||
// Number of DDA steps: traverse the maximum voxel span.
|
||||
let steps = (ray_dx.abs().max(ray_dy.abs()).max(ray_dz.abs()).ceil() as usize).max(1);
|
||||
let inv_steps = 1.0 / steps as f64;
|
||||
|
||||
for step in 0..=steps {
|
||||
let t = step as f64 * inv_steps;
|
||||
let rx = start_vx + t * ray_dx;
|
||||
let ry = start_vy + t * ray_dy;
|
||||
let rz = start_vz + t * ray_dz;
|
||||
|
||||
let base_ix = rx.floor() as isize;
|
||||
let base_iy = ry.floor() as isize;
|
||||
let base_iz = rz.floor() as isize;
|
||||
|
||||
// Expand by Fresnel radius to check neighboring voxels.
|
||||
for diz in -expand_z..=expand_z {
|
||||
let iz = base_iz + diz;
|
||||
if iz < 0 || iz >= config.nz as isize { continue; }
|
||||
for diy in -expand_y..=expand_y {
|
||||
let iy = base_iy + diy;
|
||||
if iy < 0 || iy >= config.ny as isize { continue; }
|
||||
for dix in -expand_x..=expand_x {
|
||||
let ix = base_ix + dix;
|
||||
if ix < 0 || ix >= config.nx as isize { continue; }
|
||||
|
||||
let idx = iz as usize * config.ny * config.nx
|
||||
+ iy as usize * config.nx
|
||||
+ ix as usize;
|
||||
|
||||
if visited[idx] { continue; }
|
||||
|
||||
let cx = config.bounds[0] + (ix as f64 + 0.5) * vx;
|
||||
let cy = config.bounds[1] + (iy as f64 + 0.5) * vy;
|
||||
let cz = config.bounds[2] + (iz as f64 + 0.5) * vz;
|
||||
|
||||
let dist = point_to_segment_distance(
|
||||
cx, cy, cz,
|
||||
link.tx.x, link.tx.y, link.tx.z,
|
||||
dx, dy, dz, link_dist,
|
||||
);
|
||||
|
||||
if dist < fresnel_radius {
|
||||
let w = 1.0 - dist / fresnel_radius;
|
||||
weights.push((idx, w));
|
||||
}
|
||||
visited[idx] = true;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -76,4 +76,31 @@ describe('MATScreen', () => {
|
|||
// Simulated status maps to 'simulated' banner -> "SIMULATED DATA"
|
||||
expect(getByText('SIMULATED DATA')).toBeTruthy();
|
||||
});
|
||||
|
||||
it('shows simulation warning overlay when simulated and not acknowledged', () => {
|
||||
// Reset store to ensure overlay is shown
|
||||
const { useMatStore } = require('@/stores/matStore');
|
||||
useMatStore.setState({ dataSource: 'simulated', simulationAcknowledged: false });
|
||||
|
||||
const { MATScreen } = require('@/screens/MATScreen');
|
||||
const { getByText } = render(
|
||||
<ThemeProvider>
|
||||
<MATScreen />
|
||||
</ThemeProvider>,
|
||||
);
|
||||
expect(getByText('I UNDERSTAND')).toBeTruthy();
|
||||
});
|
||||
|
||||
it('hides overlay after acknowledgment', () => {
|
||||
const { useMatStore } = require('@/stores/matStore');
|
||||
useMatStore.setState({ dataSource: 'simulated', simulationAcknowledged: true });
|
||||
|
||||
const { MATScreen } = require('@/screens/MATScreen');
|
||||
const { queryByText } = render(
|
||||
<ThemeProvider>
|
||||
<MATScreen />
|
||||
</ThemeProvider>,
|
||||
);
|
||||
expect(queryByText('I UNDERSTAND')).toBeNull();
|
||||
});
|
||||
});
|
||||
|
|
|
|||
|
|
@ -62,6 +62,8 @@ describe('useMatStore', () => {
|
|||
survivors: [],
|
||||
alerts: [],
|
||||
selectedEventId: null,
|
||||
dataSource: 'simulated',
|
||||
simulationAcknowledged: false,
|
||||
});
|
||||
});
|
||||
|
||||
|
|
@ -195,4 +197,32 @@ describe('useMatStore', () => {
|
|||
expect(useMatStore.getState().selectedEventId).toBeNull();
|
||||
});
|
||||
});
|
||||
|
||||
describe('dataSource', () => {
|
||||
it('defaults to simulated', () => {
|
||||
expect(useMatStore.getState().dataSource).toBe('simulated');
|
||||
});
|
||||
|
||||
it('can be set to real', () => {
|
||||
useMatStore.getState().setDataSource('real');
|
||||
expect(useMatStore.getState().dataSource).toBe('real');
|
||||
});
|
||||
|
||||
it('can be set back to simulated', () => {
|
||||
useMatStore.getState().setDataSource('real');
|
||||
useMatStore.getState().setDataSource('simulated');
|
||||
expect(useMatStore.getState().dataSource).toBe('simulated');
|
||||
});
|
||||
});
|
||||
|
||||
describe('simulationAcknowledged', () => {
|
||||
it('defaults to false', () => {
|
||||
expect(useMatStore.getState().simulationAcknowledged).toBe(false);
|
||||
});
|
||||
|
||||
it('can be acknowledged', () => {
|
||||
useMatStore.getState().acknowledgeSimulation();
|
||||
expect(useMatStore.getState().simulationAcknowledged).toBe(true);
|
||||
});
|
||||
});
|
||||
});
|
||||
|
|
|
|||
49
ui/mobile/src/screens/MATScreen/SimulationBanner.tsx
Normal file
49
ui/mobile/src/screens/MATScreen/SimulationBanner.tsx
Normal file
|
|
@ -0,0 +1,49 @@
|
|||
import React, { useEffect, useRef } from 'react';
|
||||
import { Animated, StyleSheet, Text, View } from 'react-native';
|
||||
|
||||
interface Props {
|
||||
visible: boolean;
|
||||
}
|
||||
|
||||
export const SimulationBanner: React.FC<Props> = ({ visible }) => {
|
||||
const opacity = useRef(new Animated.Value(1)).current;
|
||||
|
||||
useEffect(() => {
|
||||
if (!visible) return;
|
||||
|
||||
const pulse = Animated.loop(
|
||||
Animated.sequence([
|
||||
Animated.timing(opacity, { toValue: 0.4, duration: 800, useNativeDriver: true }),
|
||||
Animated.timing(opacity, { toValue: 1.0, duration: 800, useNativeDriver: true }),
|
||||
]),
|
||||
);
|
||||
pulse.start();
|
||||
return () => pulse.stop();
|
||||
}, [visible, opacity]);
|
||||
|
||||
if (!visible) return null;
|
||||
|
||||
return (
|
||||
<Animated.View style={[styles.banner, { opacity }]}>
|
||||
<Text style={styles.text}>SIMULATED DATA - NOT CONNECTED TO REAL SENSORS</Text>
|
||||
</Animated.View>
|
||||
);
|
||||
};
|
||||
|
||||
const styles = StyleSheet.create({
|
||||
banner: {
|
||||
backgroundColor: '#e74c3c',
|
||||
paddingVertical: 6,
|
||||
paddingHorizontal: 12,
|
||||
borderRadius: 6,
|
||||
alignItems: 'center',
|
||||
marginBottom: 8,
|
||||
},
|
||||
text: {
|
||||
color: '#ffffff',
|
||||
fontWeight: '700',
|
||||
fontSize: 12,
|
||||
letterSpacing: 0.5,
|
||||
textAlign: 'center',
|
||||
},
|
||||
});
|
||||
78
ui/mobile/src/screens/MATScreen/SimulationWarningOverlay.tsx
Normal file
78
ui/mobile/src/screens/MATScreen/SimulationWarningOverlay.tsx
Normal file
|
|
@ -0,0 +1,78 @@
|
|||
import React from 'react';
|
||||
import { Modal, Pressable, StyleSheet, Text, View } from 'react-native';
|
||||
|
||||
interface Props {
|
||||
visible: boolean;
|
||||
onAcknowledge: () => void;
|
||||
}
|
||||
|
||||
export const SimulationWarningOverlay: React.FC<Props> = ({ visible, onAcknowledge }) => (
|
||||
<Modal visible={visible} transparent animationType="fade">
|
||||
<View style={styles.backdrop}>
|
||||
<View style={styles.card}>
|
||||
<Text style={styles.icon}>⚠</Text>
|
||||
<Text style={styles.title}>SIMULATED DATA</Text>
|
||||
<Text style={styles.body}>
|
||||
NOT CONNECTED TO REAL SENSORS{'\n\n'}
|
||||
All survivor detections, vital signs, and alerts displayed on this screen are
|
||||
generated from simulated data and do not reflect actual conditions.
|
||||
</Text>
|
||||
<Pressable style={styles.button} onPress={onAcknowledge}>
|
||||
<Text style={styles.buttonText}>I UNDERSTAND</Text>
|
||||
</Pressable>
|
||||
</View>
|
||||
</View>
|
||||
</Modal>
|
||||
);
|
||||
|
||||
const styles = StyleSheet.create({
|
||||
backdrop: {
|
||||
flex: 1,
|
||||
backgroundColor: 'rgba(0,0,0,0.85)',
|
||||
justifyContent: 'center',
|
||||
alignItems: 'center',
|
||||
padding: 24,
|
||||
},
|
||||
card: {
|
||||
backgroundColor: '#1a1a2e',
|
||||
borderRadius: 16,
|
||||
padding: 32,
|
||||
alignItems: 'center',
|
||||
borderWidth: 2,
|
||||
borderColor: '#e74c3c',
|
||||
maxWidth: 420,
|
||||
width: '100%',
|
||||
},
|
||||
icon: {
|
||||
fontSize: 48,
|
||||
color: '#e74c3c',
|
||||
marginBottom: 12,
|
||||
},
|
||||
title: {
|
||||
fontSize: 22,
|
||||
fontWeight: '800',
|
||||
color: '#e74c3c',
|
||||
textAlign: 'center',
|
||||
marginBottom: 16,
|
||||
letterSpacing: 1,
|
||||
},
|
||||
body: {
|
||||
fontSize: 15,
|
||||
color: '#cccccc',
|
||||
textAlign: 'center',
|
||||
lineHeight: 22,
|
||||
marginBottom: 28,
|
||||
},
|
||||
button: {
|
||||
backgroundColor: '#e74c3c',
|
||||
paddingHorizontal: 36,
|
||||
paddingVertical: 14,
|
||||
borderRadius: 8,
|
||||
},
|
||||
buttonText: {
|
||||
color: '#ffffff',
|
||||
fontWeight: '700',
|
||||
fontSize: 16,
|
||||
letterSpacing: 0.5,
|
||||
},
|
||||
});
|
||||
|
|
@ -10,6 +10,8 @@ import { type ConnectionStatus } from '@/types/sensing';
|
|||
import { Alert, type Survivor } from '@/types/mat';
|
||||
import { AlertList } from './AlertList';
|
||||
import { MatWebView } from './MatWebView';
|
||||
import { SimulationBanner } from './SimulationBanner';
|
||||
import { SimulationWarningOverlay } from './SimulationWarningOverlay';
|
||||
import { SurvivorCounter } from './SurvivorCounter';
|
||||
import { useMatBridge } from './useMatBridge';
|
||||
|
||||
|
|
@ -47,6 +49,15 @@ export const MATScreen = () => {
|
|||
const upsertSurvivor = useMatStore((state) => state.upsertSurvivor);
|
||||
const addAlert = useMatStore((state) => state.addAlert);
|
||||
const upsertEvent = useMatStore((state) => state.upsertEvent);
|
||||
const dataSource = useMatStore((state) => state.dataSource);
|
||||
const simulationAcknowledged = useMatStore((state) => state.simulationAcknowledged);
|
||||
const setDataSource = useMatStore((state) => state.setDataSource);
|
||||
const acknowledgeSimulation = useMatStore((state) => state.acknowledgeSimulation);
|
||||
|
||||
// Sync dataSource from connection status
|
||||
useEffect(() => {
|
||||
setDataSource(connectionStatus === 'connected' ? 'real' : 'simulated');
|
||||
}, [connectionStatus, setDataSource]);
|
||||
|
||||
const { webViewRef, ready, onMessage, sendFrameUpdate, postEvent } = useMatBridge({
|
||||
onSurvivorDetected: (survivor) => {
|
||||
|
|
@ -113,8 +124,13 @@ export const MATScreen = () => {
|
|||
const { height } = useWindowDimensions();
|
||||
const webHeight = Math.max(240, Math.floor(height * 0.5));
|
||||
|
||||
const showOverlay = dataSource === 'simulated' && !simulationAcknowledged;
|
||||
const showBanner = dataSource === 'simulated' && simulationAcknowledged;
|
||||
|
||||
return (
|
||||
<ThemedView style={{ flex: 1, backgroundColor: colors.bg, padding: spacing.md }}>
|
||||
<SimulationWarningOverlay visible={showOverlay} onAcknowledge={acknowledgeSimulation} />
|
||||
<SimulationBanner visible={showBanner} />
|
||||
<ConnectionBanner status={resolveBannerState(connectionStatus)} />
|
||||
<View style={{ marginTop: 20 }}>
|
||||
<SurvivorCounter survivors={survivors} />
|
||||
|
|
|
|||
|
|
@ -7,11 +7,17 @@ export interface MatState {
|
|||
survivors: Survivor[];
|
||||
alerts: Alert[];
|
||||
selectedEventId: string | null;
|
||||
/** Whether data comes from real sensors or simulation. */
|
||||
dataSource: 'real' | 'simulated';
|
||||
/** Whether the user has dismissed the simulation warning overlay. */
|
||||
simulationAcknowledged: boolean;
|
||||
upsertEvent: (event: DisasterEvent) => void;
|
||||
addZone: (zone: ScanZone) => void;
|
||||
upsertSurvivor: (survivor: Survivor) => void;
|
||||
addAlert: (alert: Alert) => void;
|
||||
setSelectedEvent: (id: string | null) => void;
|
||||
setDataSource: (source: 'real' | 'simulated') => void;
|
||||
acknowledgeSimulation: () => void;
|
||||
}
|
||||
|
||||
export const useMatStore = create<MatState>((set) => ({
|
||||
|
|
@ -20,6 +26,8 @@ export const useMatStore = create<MatState>((set) => ({
|
|||
survivors: [],
|
||||
alerts: [],
|
||||
selectedEventId: null,
|
||||
dataSource: 'simulated',
|
||||
simulationAcknowledged: false,
|
||||
|
||||
upsertEvent: (event) => {
|
||||
set((state) => {
|
||||
|
|
@ -71,4 +79,12 @@ export const useMatStore = create<MatState>((set) => ({
|
|||
setSelectedEvent: (id) => {
|
||||
set({ selectedEventId: id });
|
||||
},
|
||||
|
||||
setDataSource: (source) => {
|
||||
set({ dataSource: source });
|
||||
},
|
||||
|
||||
acknowledgeSimulation: () => {
|
||||
set({ simulationAcknowledged: true });
|
||||
},
|
||||
}));
|
||||
|
|
|
|||
|
|
@ -17,7 +17,7 @@ from starlette.exceptions import HTTPException as StarletteHTTPException
|
|||
|
||||
from src.config.settings import get_settings
|
||||
from src.config.domains import get_domain_config
|
||||
from src.api.routers import pose, stream, health
|
||||
from src.api.routers import pose, stream, health, auth
|
||||
from src.api.middleware.auth import AuthMiddleware
|
||||
from src.api.middleware.rate_limit import RateLimitMiddleware
|
||||
from src.api.dependencies import get_pose_service, get_stream_service, get_hardware_service
|
||||
|
|
@ -263,6 +263,12 @@ app.include_router(
|
|||
tags=["Streaming"]
|
||||
)
|
||||
|
||||
app.include_router(
|
||||
auth.router,
|
||||
prefix=f"{settings.api_prefix}",
|
||||
tags=["Authentication"]
|
||||
)
|
||||
|
||||
|
||||
# Root endpoint
|
||||
@app.get("/")
|
||||
|
|
|
|||
|
|
@ -189,7 +189,11 @@ class AuthMiddleware(BaseHTTPMiddleware):
|
|||
self.settings.secret_key,
|
||||
algorithms=[self.settings.jwt_algorithm]
|
||||
)
|
||||
|
||||
|
||||
# Check token blacklist (logout invalidation)
|
||||
if token_blacklist.is_blacklisted(token):
|
||||
raise ValueError("Token has been revoked")
|
||||
|
||||
# Extract user information
|
||||
user_id = payload.get("sub")
|
||||
if not user_id:
|
||||
|
|
|
|||
|
|
@ -2,6 +2,6 @@
|
|||
API routers package
|
||||
"""
|
||||
|
||||
from . import pose, stream, health
|
||||
from . import pose, stream, health, auth
|
||||
|
||||
__all__ = ["pose", "stream", "health"]
|
||||
__all__ = ["pose", "stream", "health", "auth"]
|
||||
32
v1/src/api/routers/auth.py
Normal file
32
v1/src/api/routers/auth.py
Normal file
|
|
@ -0,0 +1,32 @@
|
|||
"""
|
||||
Authentication router for WiFi-DensePose API.
|
||||
Provides logout (token blacklisting) endpoint.
|
||||
"""
|
||||
|
||||
import logging
|
||||
from typing import Optional
|
||||
|
||||
from fastapi import APIRouter, Request, HTTPException, status
|
||||
|
||||
from src.api.middleware.auth import token_blacklist
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
router = APIRouter(prefix="/auth", tags=["auth"])
|
||||
|
||||
|
||||
@router.post("/logout")
|
||||
async def logout(request: Request):
|
||||
"""Logout by blacklisting the current Bearer token."""
|
||||
auth_header = request.headers.get("authorization")
|
||||
if not auth_header or not auth_header.startswith("Bearer "):
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_401_UNAUTHORIZED,
|
||||
detail="Missing or invalid Authorization header",
|
||||
)
|
||||
|
||||
token = auth_header.split(" ", 1)[1]
|
||||
token_blacklist.add_token(token)
|
||||
logger.info("Token blacklisted via /auth/logout")
|
||||
|
||||
return {"success": True, "message": "Token revoked"}
|
||||
|
|
@ -1,6 +1,7 @@
|
|||
"""CSI data processor for WiFi-DensePose system using TDD approach."""
|
||||
|
||||
import asyncio
|
||||
import itertools
|
||||
import logging
|
||||
import numpy as np
|
||||
from datetime import datetime, timezone
|
||||
|
|
@ -293,7 +294,8 @@ class CSIProcessor:
|
|||
if count >= len(self.csi_history):
|
||||
return list(self.csi_history)
|
||||
else:
|
||||
return list(self.csi_history)[-count:]
|
||||
start = len(self.csi_history) - count
|
||||
return list(itertools.islice(self.csi_history, start, len(self.csi_history)))
|
||||
|
||||
def get_processing_statistics(self) -> Dict[str, Any]:
|
||||
"""Get processing statistics.
|
||||
|
|
@ -410,8 +412,9 @@ class CSIProcessor:
|
|||
# Use cached mean-phase values (pre-computed in add_to_history)
|
||||
# Only take the last doppler_window frames for bounded cost
|
||||
window = min(len(self._phase_cache), self._doppler_window)
|
||||
cache_list = list(self._phase_cache)
|
||||
phase_matrix = np.array(cache_list[-window:])
|
||||
start = len(self._phase_cache) - window
|
||||
cache_list = list(itertools.islice(self._phase_cache, start, len(self._phase_cache)))
|
||||
phase_matrix = np.array(cache_list)
|
||||
|
||||
# Temporal phase differences between consecutive frames
|
||||
phase_diffs = np.diff(phase_matrix, axis=0)
|
||||
|
|
|
|||
|
|
@ -56,6 +56,10 @@ class TokenManager:
|
|||
"""Verify and decode JWT token."""
|
||||
try:
|
||||
payload = jwt.decode(token, self.secret_key, algorithms=[self.algorithm])
|
||||
# Check token blacklist (logout invalidation)
|
||||
from src.api.middleware.auth import token_blacklist
|
||||
if token_blacklist.is_blacklisted(token):
|
||||
raise AuthenticationError("Token has been revoked")
|
||||
return payload
|
||||
except JWTError as e:
|
||||
logger.warning(f"JWT verification failed: {e}")
|
||||
|
|
|
|||
135
v1/tests/performance/test_frame_budget.py
Normal file
135
v1/tests/performance/test_frame_budget.py
Normal file
|
|
@ -0,0 +1,135 @@
|
|||
"""Frame budget benchmark for CSI processing pipeline.
|
||||
|
||||
Verifies that per-frame CSI processing stays within the 50 ms budget
|
||||
required for real-time sensing at 20 FPS.
|
||||
"""
|
||||
|
||||
import time
|
||||
import statistics
|
||||
import pytest
|
||||
import numpy as np
|
||||
|
||||
from src.core.csi_processor import CSIProcessor
|
||||
|
||||
|
||||
def _make_config():
|
||||
return {
|
||||
"sampling_rate": 1000,
|
||||
"window_size": 256,
|
||||
"overlap": 0.5,
|
||||
"noise_threshold": -60,
|
||||
"human_detection_threshold": 0.8,
|
||||
"smoothing_factor": 0.9,
|
||||
"max_history_size": 500,
|
||||
"num_subcarriers": 256,
|
||||
"num_antennas": 3,
|
||||
"doppler_window": 64,
|
||||
}
|
||||
|
||||
|
||||
def _make_csi_data(n_subcarriers=256, n_antennas=3, seed=None):
|
||||
"""Generate a synthetic CSI frame with complex-valued subcarriers."""
|
||||
rng = np.random.default_rng(seed)
|
||||
from unittest.mock import MagicMock
|
||||
csi = MagicMock()
|
||||
csi.amplitude = rng.random((n_antennas, n_subcarriers)).astype(np.float64) * 20.0
|
||||
csi.phase = (rng.random((n_antennas, n_subcarriers)).astype(np.float64) - 0.5) * np.pi * 2
|
||||
csi.frequency = 5.0e9
|
||||
csi.bandwidth = 80e6
|
||||
csi.num_subcarriers = n_subcarriers
|
||||
csi.num_antennas = n_antennas
|
||||
csi.snr = 25.0
|
||||
csi.timestamp = time.time()
|
||||
csi.metadata = {}
|
||||
return csi
|
||||
|
||||
|
||||
class TestSingleFrameBudget:
|
||||
"""Single-frame processing must complete in < 50 ms."""
|
||||
|
||||
def test_single_frame_under_50ms(self):
|
||||
proc = CSIProcessor(config=_make_config())
|
||||
frame = _make_csi_data(seed=42)
|
||||
|
||||
# Warm up
|
||||
proc.preprocess_csi_data(frame)
|
||||
|
||||
start = time.perf_counter()
|
||||
proc.preprocess_csi_data(frame)
|
||||
features = proc.extract_features(frame)
|
||||
if features:
|
||||
proc.detect_human_presence(features)
|
||||
elapsed_ms = (time.perf_counter() - start) * 1000
|
||||
|
||||
assert elapsed_ms < 50, f"Single frame took {elapsed_ms:.1f} ms (budget: 50 ms)"
|
||||
|
||||
|
||||
class TestSustainedFrameBudget:
|
||||
"""Sustained 100-frame processing p95 must be < 50 ms per frame."""
|
||||
|
||||
def test_sustained_100_frames_p95(self):
|
||||
proc = CSIProcessor(config=_make_config())
|
||||
rng = np.random.default_rng(123)
|
||||
n_frames = 100
|
||||
latencies = []
|
||||
|
||||
for i in range(n_frames):
|
||||
frame = _make_csi_data(seed=i)
|
||||
start = time.perf_counter()
|
||||
preprocessed = proc.preprocess_csi_data(frame)
|
||||
features = proc.extract_features(preprocessed)
|
||||
if features:
|
||||
proc.detect_human_presence(features)
|
||||
proc.add_to_history(frame)
|
||||
elapsed_ms = (time.perf_counter() - start) * 1000
|
||||
latencies.append(elapsed_ms)
|
||||
|
||||
p50 = statistics.median(latencies)
|
||||
p95 = sorted(latencies)[int(0.95 * len(latencies))]
|
||||
p99 = sorted(latencies)[int(0.99 * len(latencies))]
|
||||
|
||||
print(f"\n--- Sustained {n_frames}-frame benchmark ---")
|
||||
print(f" p50: {p50:.2f} ms")
|
||||
print(f" p95: {p95:.2f} ms")
|
||||
print(f" p99: {p99:.2f} ms")
|
||||
print(f" min: {min(latencies):.2f} ms")
|
||||
print(f" max: {max(latencies):.2f} ms")
|
||||
|
||||
assert p95 < 50, f"p95 latency {p95:.1f} ms exceeds 50 ms budget"
|
||||
|
||||
|
||||
class TestPipelineWithDoppler:
|
||||
"""Full pipeline including Doppler estimation must stay within budget."""
|
||||
|
||||
def test_doppler_pipeline(self):
|
||||
proc = CSIProcessor(config=_make_config())
|
||||
n_frames = 100
|
||||
latencies = []
|
||||
|
||||
# Fill history first
|
||||
for i in range(20):
|
||||
frame = _make_csi_data(seed=i + 1000)
|
||||
proc.add_to_history(frame)
|
||||
|
||||
for i in range(n_frames):
|
||||
frame = _make_csi_data(seed=i + 2000)
|
||||
start = time.perf_counter()
|
||||
preprocessed = proc.preprocess_csi_data(frame)
|
||||
features = proc.extract_features(preprocessed)
|
||||
if features:
|
||||
proc.detect_human_presence(features)
|
||||
proc.add_to_history(frame)
|
||||
elapsed_ms = (time.perf_counter() - start) * 1000
|
||||
latencies.append(elapsed_ms)
|
||||
|
||||
p50 = statistics.median(latencies)
|
||||
p95 = sorted(latencies)[int(0.95 * len(latencies))]
|
||||
p99 = sorted(latencies)[int(0.99 * len(latencies))]
|
||||
|
||||
print(f"\n--- Doppler pipeline benchmark ({n_frames} frames, 20 warmup) ---")
|
||||
print(f" p50: {p50:.2f} ms")
|
||||
print(f" p95: {p95:.2f} ms")
|
||||
print(f" p99: {p99:.2f} ms")
|
||||
|
||||
# Doppler adds overhead but should still be within budget
|
||||
assert p95 < 50, f"Doppler pipeline p95 {p95:.1f} ms exceeds 50 ms budget"
|
||||
56
v1/tests/unit/conftest.py
Normal file
56
v1/tests/unit/conftest.py
Normal file
|
|
@ -0,0 +1,56 @@
|
|||
"""Shared fixtures for unit tests."""
|
||||
|
||||
import os
|
||||
import pytest
|
||||
from unittest.mock import MagicMock, AsyncMock, patch
|
||||
|
||||
# Set SECRET_KEY before any settings import
|
||||
os.environ.setdefault("SECRET_KEY", "test-secret-key-for-unit-tests-only")
|
||||
os.environ.setdefault("JWT_SECRET_KEY", "test-secret-key-for-unit-tests-only")
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def mock_settings():
|
||||
"""Create a mock Settings object."""
|
||||
settings = MagicMock()
|
||||
settings.secret_key = "test-secret-key-for-unit-tests-only"
|
||||
settings.jwt_algorithm = "HS256"
|
||||
settings.jwt_expire_hours = 24
|
||||
settings.app_name = "test-app"
|
||||
settings.version = "0.1.0"
|
||||
settings.is_production = False
|
||||
settings.enable_rate_limiting = False
|
||||
settings.enable_authentication = False
|
||||
settings.rate_limit_requests = 100
|
||||
settings.rate_limit_window = 60
|
||||
settings.rate_limit_authenticated_requests = 1000
|
||||
settings.allowed_hosts = ["*"]
|
||||
settings.csi_buffer_size = 100
|
||||
settings.stream_buffer_size = 100
|
||||
settings.mock_hardware = True
|
||||
settings.mock_pose_data = True
|
||||
settings.enable_real_time_processing = False
|
||||
settings.trusted_proxies = ["127.0.0.1"]
|
||||
return settings
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def mock_domain_config():
|
||||
"""Create a mock DomainConfig object."""
|
||||
config = MagicMock()
|
||||
config.pose_estimation = MagicMock()
|
||||
config.streaming = MagicMock()
|
||||
config.hardware = MagicMock()
|
||||
return config
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def mock_redis():
|
||||
"""Provide a mock Redis client."""
|
||||
with patch("redis.Redis") as mock:
|
||||
client = MagicMock()
|
||||
client.ping.return_value = True
|
||||
client.get.return_value = None
|
||||
client.set.return_value = True
|
||||
mock.return_value = client
|
||||
yield client
|
||||
137
v1/tests/unit/test_auth_middleware.py
Normal file
137
v1/tests/unit/test_auth_middleware.py
Normal file
|
|
@ -0,0 +1,137 @@
|
|||
"""Tests for AuthMiddleware and TokenManager."""
|
||||
|
||||
import pytest
|
||||
import os
|
||||
from unittest.mock import MagicMock, AsyncMock, patch
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
|
||||
class TestTokenManager:
|
||||
def test_create_token(self, mock_settings):
|
||||
from src.middleware.auth import TokenManager
|
||||
tm = TokenManager(mock_settings)
|
||||
token = tm.create_access_token({"sub": "user1"})
|
||||
assert isinstance(token, str)
|
||||
assert len(token) > 0
|
||||
|
||||
def test_verify_valid_token(self, mock_settings):
|
||||
from src.middleware.auth import TokenManager
|
||||
tm = TokenManager(mock_settings)
|
||||
token = tm.create_access_token({"sub": "user1", "role": "admin"})
|
||||
payload = tm.verify_token(token)
|
||||
assert payload["sub"] == "user1"
|
||||
assert payload["role"] == "admin"
|
||||
|
||||
def test_verify_invalid_token(self, mock_settings):
|
||||
from src.middleware.auth import TokenManager, AuthenticationError
|
||||
tm = TokenManager(mock_settings)
|
||||
with pytest.raises(AuthenticationError):
|
||||
tm.verify_token("invalid.token.here")
|
||||
|
||||
def test_decode_claims(self, mock_settings):
|
||||
from src.middleware.auth import TokenManager
|
||||
tm = TokenManager(mock_settings)
|
||||
token = tm.create_access_token({"sub": "user1"})
|
||||
claims = tm.decode_token_claims(token)
|
||||
assert claims is not None
|
||||
assert claims["sub"] == "user1"
|
||||
|
||||
def test_decode_claims_invalid(self, mock_settings):
|
||||
from src.middleware.auth import TokenManager
|
||||
tm = TokenManager(mock_settings)
|
||||
claims = tm.decode_token_claims("bad-token")
|
||||
assert claims is None
|
||||
|
||||
def test_token_has_expiry(self, mock_settings):
|
||||
from src.middleware.auth import TokenManager
|
||||
tm = TokenManager(mock_settings)
|
||||
token = tm.create_access_token({"sub": "user1"})
|
||||
payload = tm.verify_token(token)
|
||||
assert "exp" in payload
|
||||
assert "iat" in payload
|
||||
|
||||
|
||||
class TestUserManager:
|
||||
def test_create_user(self):
|
||||
from src.middleware.auth import UserManager
|
||||
um = UserManager()
|
||||
assert um.get_user("nonexistent") is None
|
||||
|
||||
def test_hash_password(self):
|
||||
from src.middleware.auth import UserManager
|
||||
hashed = UserManager.hash_password("secret123")
|
||||
assert hashed != "secret123"
|
||||
assert len(hashed) > 20
|
||||
|
||||
def test_verify_password(self):
|
||||
from src.middleware.auth import UserManager
|
||||
hashed = UserManager.hash_password("secret123")
|
||||
assert UserManager.verify_password("secret123", hashed) is True
|
||||
assert UserManager.verify_password("wrong", hashed) is False
|
||||
|
||||
|
||||
class TestTokenBlacklist:
|
||||
def test_add_and_check(self):
|
||||
from src.api.middleware.auth import TokenBlacklist
|
||||
bl = TokenBlacklist()
|
||||
bl.add_token("tok123")
|
||||
assert bl.is_blacklisted("tok123") is True
|
||||
assert bl.is_blacklisted("tok456") is False
|
||||
|
||||
def test_blacklisted_token_rejected(self, mock_settings):
|
||||
from src.middleware.auth import TokenManager, AuthenticationError
|
||||
from src.api.middleware.auth import token_blacklist
|
||||
|
||||
tm = TokenManager(mock_settings)
|
||||
token = tm.create_access_token({"sub": "user1"})
|
||||
# Token should be valid
|
||||
tm.verify_token(token)
|
||||
# Blacklist it
|
||||
token_blacklist.add_token(token)
|
||||
with pytest.raises(AuthenticationError, match="revoked"):
|
||||
tm.verify_token(token)
|
||||
# Cleanup
|
||||
token_blacklist._blacklisted_tokens.discard(token)
|
||||
|
||||
|
||||
class TestAuthMiddleware:
|
||||
def test_public_paths(self, mock_settings):
|
||||
with patch("src.api.middleware.auth.get_settings", return_value=mock_settings):
|
||||
from src.api.middleware.auth import AuthMiddleware
|
||||
app = MagicMock()
|
||||
mw = AuthMiddleware(app)
|
||||
assert mw._is_public_path("/health") is True
|
||||
assert mw._is_public_path("/docs") is True
|
||||
assert mw._is_public_path("/api/v1/pose/analyze") is False
|
||||
|
||||
def test_protected_paths(self, mock_settings):
|
||||
with patch("src.api.middleware.auth.get_settings", return_value=mock_settings):
|
||||
from src.api.middleware.auth import AuthMiddleware
|
||||
app = MagicMock()
|
||||
mw = AuthMiddleware(app)
|
||||
assert mw._is_protected_path("/api/v1/pose/analyze") is True
|
||||
assert mw._is_protected_path("/health") is False
|
||||
|
||||
def test_extract_token_from_header(self, mock_settings):
|
||||
with patch("src.api.middleware.auth.get_settings", return_value=mock_settings):
|
||||
from src.api.middleware.auth import AuthMiddleware
|
||||
app = MagicMock()
|
||||
mw = AuthMiddleware(app)
|
||||
request = MagicMock()
|
||||
request.headers = {"authorization": "Bearer mytoken123"}
|
||||
request.query_params = {}
|
||||
request.cookies = {}
|
||||
token = mw._extract_token(request)
|
||||
assert token == "mytoken123"
|
||||
|
||||
def test_extract_token_missing(self, mock_settings):
|
||||
with patch("src.api.middleware.auth.get_settings", return_value=mock_settings):
|
||||
from src.api.middleware.auth import AuthMiddleware
|
||||
app = MagicMock()
|
||||
mw = AuthMiddleware(app)
|
||||
request = MagicMock()
|
||||
request.headers = {}
|
||||
request.query_params = {}
|
||||
request.cookies = {}
|
||||
token = mw._extract_token(request)
|
||||
assert token is None
|
||||
78
v1/tests/unit/test_error_handler.py
Normal file
78
v1/tests/unit/test_error_handler.py
Normal file
|
|
@ -0,0 +1,78 @@
|
|||
"""Tests for error handling in the API layer."""
|
||||
|
||||
import pytest
|
||||
from unittest.mock import MagicMock, patch
|
||||
from fastapi.testclient import TestClient
|
||||
|
||||
|
||||
class TestExceptionHandlers:
|
||||
"""Test the exception handlers registered on the FastAPI app."""
|
||||
|
||||
def _get_app(self):
|
||||
"""Import app lazily to avoid side effects."""
|
||||
with patch("src.api.main.get_settings") as mock_gs, \
|
||||
patch("src.api.main.get_domain_config") as mock_gdc, \
|
||||
patch("src.api.main.get_pose_service") as mock_ps, \
|
||||
patch("src.api.main.get_stream_service") as mock_ss, \
|
||||
patch("src.api.main.get_hardware_service") as mock_hs, \
|
||||
patch("src.api.main.connection_manager") as mock_cm, \
|
||||
patch("src.api.main.PoseStreamHandler") as mock_psh:
|
||||
mock_gs.return_value = MagicMock(
|
||||
app_name="test", version="0.1", environment="test",
|
||||
is_production=False, enable_rate_limiting=False,
|
||||
enable_authentication=False, docs_url="/docs",
|
||||
redoc_url="/redoc", openapi_url="/openapi.json",
|
||||
api_prefix="/api/v1",
|
||||
)
|
||||
mock_gs.return_value.get_logging_config.return_value = {
|
||||
"version": 1, "disable_existing_loggers": False,
|
||||
"handlers": {}, "loggers": {},
|
||||
}
|
||||
mock_gs.return_value.get_cors_config.return_value = {
|
||||
"allow_origins": ["*"], "allow_methods": ["*"],
|
||||
"allow_headers": ["*"],
|
||||
}
|
||||
# Re-import to pick up patches
|
||||
import importlib
|
||||
import src.api.main as m
|
||||
importlib.reload(m)
|
||||
return m.app
|
||||
|
||||
|
||||
class TestErrorResponseModel:
|
||||
def test_error_json_structure(self):
|
||||
"""Verify error JSON has code, message, type fields."""
|
||||
error = {
|
||||
"error": {
|
||||
"code": 404,
|
||||
"message": "Not found",
|
||||
"type": "http_error"
|
||||
}
|
||||
}
|
||||
assert error["error"]["code"] == 404
|
||||
assert "message" in error["error"]
|
||||
assert "type" in error["error"]
|
||||
|
||||
def test_validation_error_structure(self):
|
||||
error = {
|
||||
"error": {
|
||||
"code": 422,
|
||||
"message": "Validation error",
|
||||
"type": "validation_error",
|
||||
"details": []
|
||||
}
|
||||
}
|
||||
assert error["error"]["type"] == "validation_error"
|
||||
assert isinstance(error["error"]["details"], list)
|
||||
|
||||
def test_internal_error_masks_details(self):
|
||||
"""In production, internal errors should not leak stack traces."""
|
||||
error = {
|
||||
"error": {
|
||||
"code": 500,
|
||||
"message": "Internal server error",
|
||||
"type": "internal_error"
|
||||
}
|
||||
}
|
||||
assert "traceback" not in str(error)
|
||||
assert error["error"]["message"] == "Internal server error"
|
||||
65
v1/tests/unit/test_hardware_service.py
Normal file
65
v1/tests/unit/test_hardware_service.py
Normal file
|
|
@ -0,0 +1,65 @@
|
|||
"""Tests for HardwareService."""
|
||||
|
||||
import pytest
|
||||
from unittest.mock import MagicMock, AsyncMock, patch
|
||||
|
||||
|
||||
class TestHardwareServiceInit:
|
||||
def test_init(self, mock_settings, mock_domain_config):
|
||||
mock_settings.mock_hardware = True
|
||||
with patch("src.services.hardware_service.RouterInterface"):
|
||||
from src.services.hardware_service import HardwareService
|
||||
svc = HardwareService(mock_settings, mock_domain_config)
|
||||
assert svc.is_running is False
|
||||
assert svc.stats["total_samples"] == 0
|
||||
assert svc.stats["connected_routers"] == 0
|
||||
|
||||
def test_stats_defaults(self, mock_settings, mock_domain_config):
|
||||
mock_settings.mock_hardware = True
|
||||
with patch("src.services.hardware_service.RouterInterface"):
|
||||
from src.services.hardware_service import HardwareService
|
||||
svc = HardwareService(mock_settings, mock_domain_config)
|
||||
assert svc.stats["successful_samples"] == 0
|
||||
assert svc.stats["failed_samples"] == 0
|
||||
assert svc.stats["last_sample_time"] is None
|
||||
|
||||
|
||||
class TestHardwareServiceLifecycle:
|
||||
@pytest.mark.asyncio
|
||||
async def test_start(self, mock_settings, mock_domain_config):
|
||||
mock_settings.mock_hardware = True
|
||||
with patch("src.services.hardware_service.RouterInterface"):
|
||||
from src.services.hardware_service import HardwareService
|
||||
svc = HardwareService(mock_settings, mock_domain_config)
|
||||
svc._initialize_routers = AsyncMock()
|
||||
svc._monitoring_loop = AsyncMock()
|
||||
await svc.start()
|
||||
assert svc.is_running is True
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_double_start_idempotent(self, mock_settings, mock_domain_config):
|
||||
mock_settings.mock_hardware = True
|
||||
with patch("src.services.hardware_service.RouterInterface"):
|
||||
from src.services.hardware_service import HardwareService
|
||||
svc = HardwareService(mock_settings, mock_domain_config)
|
||||
svc._initialize_routers = AsyncMock()
|
||||
svc._monitoring_loop = AsyncMock()
|
||||
await svc.start()
|
||||
await svc.start() # idempotent
|
||||
assert svc.is_running is True
|
||||
|
||||
|
||||
class TestHardwareServiceRouter:
|
||||
def test_no_routers_on_init(self, mock_settings, mock_domain_config):
|
||||
mock_settings.mock_hardware = True
|
||||
with patch("src.services.hardware_service.RouterInterface"):
|
||||
from src.services.hardware_service import HardwareService
|
||||
svc = HardwareService(mock_settings, mock_domain_config)
|
||||
assert len(svc.router_interfaces) == 0
|
||||
|
||||
def test_max_recent_samples(self, mock_settings, mock_domain_config):
|
||||
mock_settings.mock_hardware = True
|
||||
with patch("src.services.hardware_service.RouterInterface"):
|
||||
from src.services.hardware_service import HardwareService
|
||||
svc = HardwareService(mock_settings, mock_domain_config)
|
||||
assert svc.max_recent_samples == 1000
|
||||
67
v1/tests/unit/test_health_check.py
Normal file
67
v1/tests/unit/test_health_check.py
Normal file
|
|
@ -0,0 +1,67 @@
|
|||
"""Tests for HealthCheckService."""
|
||||
|
||||
import pytest
|
||||
from unittest.mock import MagicMock
|
||||
|
||||
|
||||
class TestHealthCheckServiceInit:
|
||||
def test_init(self, mock_settings):
|
||||
from src.services.health_check import HealthCheckService
|
||||
svc = HealthCheckService(mock_settings)
|
||||
assert svc._initialized is False
|
||||
assert svc._running is False
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_initialize(self, mock_settings):
|
||||
from src.services.health_check import HealthCheckService
|
||||
svc = HealthCheckService(mock_settings)
|
||||
await svc.initialize()
|
||||
assert svc._initialized is True
|
||||
assert "api" in svc._services
|
||||
assert "database" in svc._services
|
||||
assert "hardware" in svc._services
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_double_initialize(self, mock_settings):
|
||||
from src.services.health_check import HealthCheckService
|
||||
svc = HealthCheckService(mock_settings)
|
||||
await svc.initialize()
|
||||
await svc.initialize() # idempotent
|
||||
assert svc._initialized is True
|
||||
|
||||
|
||||
class TestHealthCheckAggregation:
|
||||
@pytest.mark.asyncio
|
||||
async def test_services_registered(self, mock_settings):
|
||||
from src.services.health_check import HealthCheckService, HealthStatus
|
||||
svc = HealthCheckService(mock_settings)
|
||||
await svc.initialize()
|
||||
assert len(svc._services) == 6
|
||||
for name, sh in svc._services.items():
|
||||
assert sh.status == HealthStatus.UNKNOWN
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_service_names(self, mock_settings):
|
||||
from src.services.health_check import HealthCheckService
|
||||
svc = HealthCheckService(mock_settings)
|
||||
await svc.initialize()
|
||||
expected = {"api", "database", "redis", "hardware", "pose", "stream"}
|
||||
assert set(svc._services.keys()) == expected
|
||||
|
||||
|
||||
class TestHealthStatus:
|
||||
def test_enum_values(self):
|
||||
from src.services.health_check import HealthStatus
|
||||
assert HealthStatus.HEALTHY.value == "healthy"
|
||||
assert HealthStatus.DEGRADED.value == "degraded"
|
||||
assert HealthStatus.UNHEALTHY.value == "unhealthy"
|
||||
assert HealthStatus.UNKNOWN.value == "unknown"
|
||||
|
||||
|
||||
class TestHealthCheck:
|
||||
def test_health_check_dataclass(self):
|
||||
from src.services.health_check import HealthCheck, HealthStatus
|
||||
hc = HealthCheck(name="test", status=HealthStatus.HEALTHY, message="ok")
|
||||
assert hc.name == "test"
|
||||
assert hc.status == HealthStatus.HEALTHY
|
||||
assert hc.duration_ms == 0.0
|
||||
70
v1/tests/unit/test_metrics.py
Normal file
70
v1/tests/unit/test_metrics.py
Normal file
|
|
@ -0,0 +1,70 @@
|
|||
"""Tests for MetricsService."""
|
||||
|
||||
import pytest
|
||||
from datetime import timedelta
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
|
||||
class TestMetricSeries:
|
||||
def test_add_point(self):
|
||||
from src.services.metrics import MetricSeries
|
||||
ms = MetricSeries(name="test", description="desc", unit="ms")
|
||||
ms.add_point(42.0)
|
||||
assert len(ms.points) == 1
|
||||
assert ms.points[0].value == 42.0
|
||||
|
||||
def test_get_latest(self):
|
||||
from src.services.metrics import MetricSeries
|
||||
ms = MetricSeries(name="test", description="desc", unit="ms")
|
||||
ms.add_point(1.0)
|
||||
ms.add_point(2.0)
|
||||
latest = ms.get_latest()
|
||||
assert latest is not None
|
||||
assert latest.value == 2.0
|
||||
|
||||
def test_get_latest_empty(self):
|
||||
from src.services.metrics import MetricSeries
|
||||
ms = MetricSeries(name="test", description="desc", unit="ms")
|
||||
assert ms.get_latest() is None
|
||||
|
||||
def test_get_average(self):
|
||||
from src.services.metrics import MetricSeries
|
||||
ms = MetricSeries(name="test", description="desc", unit="ms")
|
||||
for v in [10.0, 20.0, 30.0]:
|
||||
ms.add_point(v)
|
||||
avg = ms.get_average(timedelta(minutes=5))
|
||||
assert avg == pytest.approx(20.0)
|
||||
|
||||
def test_get_average_empty(self):
|
||||
from src.services.metrics import MetricSeries
|
||||
ms = MetricSeries(name="test", description="desc", unit="ms")
|
||||
assert ms.get_average(timedelta(minutes=5)) is None
|
||||
|
||||
def test_get_max(self):
|
||||
from src.services.metrics import MetricSeries
|
||||
ms = MetricSeries(name="test", description="desc", unit="ms")
|
||||
for v in [10.0, 50.0, 30.0]:
|
||||
ms.add_point(v)
|
||||
mx = ms.get_max(timedelta(minutes=5))
|
||||
assert mx == 50.0
|
||||
|
||||
def test_labels(self):
|
||||
from src.services.metrics import MetricSeries
|
||||
ms = MetricSeries(name="test", description="desc", unit="ms")
|
||||
ms.add_point(1.0, {"region": "us-east"})
|
||||
assert ms.points[0].labels["region"] == "us-east"
|
||||
|
||||
def test_maxlen(self):
|
||||
from src.services.metrics import MetricSeries
|
||||
ms = MetricSeries(name="test", description="desc", unit="ms")
|
||||
for i in range(1100):
|
||||
ms.add_point(float(i))
|
||||
assert len(ms.points) == 1000
|
||||
|
||||
|
||||
class TestMetricsService:
|
||||
def test_init(self, mock_settings):
|
||||
with patch("src.services.metrics.psutil"):
|
||||
from src.services.metrics import MetricsService
|
||||
svc = MetricsService(mock_settings)
|
||||
assert svc._metrics is not None
|
||||
73
v1/tests/unit/test_pose_service.py
Normal file
73
v1/tests/unit/test_pose_service.py
Normal file
|
|
@ -0,0 +1,73 @@
|
|||
"""Tests for PoseService."""
|
||||
|
||||
import pytest
|
||||
import asyncio
|
||||
from unittest.mock import MagicMock, AsyncMock, patch
|
||||
from datetime import datetime
|
||||
|
||||
|
||||
class TestPoseServiceInit:
|
||||
def test_init_sets_defaults(self, mock_settings, mock_domain_config):
|
||||
with patch.dict("sys.modules", {
|
||||
"torch": MagicMock(),
|
||||
"src.models.densepose_head": MagicMock(),
|
||||
"src.models.modality_translation": MagicMock(),
|
||||
}):
|
||||
from src.services.pose_service import PoseService
|
||||
svc = PoseService(mock_settings, mock_domain_config)
|
||||
assert svc.is_initialized is False
|
||||
assert svc.is_running is False
|
||||
assert svc.stats["total_processed"] == 0
|
||||
|
||||
def test_stats_are_zero_on_init(self, mock_settings, mock_domain_config):
|
||||
with patch.dict("sys.modules", {
|
||||
"torch": MagicMock(),
|
||||
"src.models.densepose_head": MagicMock(),
|
||||
"src.models.modality_translation": MagicMock(),
|
||||
}):
|
||||
from src.services.pose_service import PoseService
|
||||
svc = PoseService(mock_settings, mock_domain_config)
|
||||
assert svc.stats["successful_detections"] == 0
|
||||
assert svc.stats["failed_detections"] == 0
|
||||
assert svc.stats["average_confidence"] == 0.0
|
||||
|
||||
|
||||
class TestPoseServiceLifecycle:
|
||||
@pytest.mark.asyncio
|
||||
async def test_initialize_sets_flag(self, mock_settings, mock_domain_config):
|
||||
with patch.dict("sys.modules", {
|
||||
"torch": MagicMock(),
|
||||
"src.models.densepose_head": MagicMock(),
|
||||
"src.models.modality_translation": MagicMock(),
|
||||
}):
|
||||
from src.services.pose_service import PoseService
|
||||
svc = PoseService(mock_settings, mock_domain_config)
|
||||
await svc.initialize()
|
||||
assert svc.is_initialized is True
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_start_stop(self, mock_settings, mock_domain_config):
|
||||
with patch.dict("sys.modules", {
|
||||
"torch": MagicMock(),
|
||||
"src.models.densepose_head": MagicMock(),
|
||||
"src.models.modality_translation": MagicMock(),
|
||||
}):
|
||||
from src.services.pose_service import PoseService
|
||||
svc = PoseService(mock_settings, mock_domain_config)
|
||||
await svc.initialize()
|
||||
await svc.start()
|
||||
assert svc.is_running is True
|
||||
await svc.stop()
|
||||
assert svc.is_running is False
|
||||
|
||||
|
||||
class TestPoseServiceStats:
|
||||
def test_initial_classification(self, mock_settings, mock_domain_config):
|
||||
with patch.dict("sys.modules", {
|
||||
"torch": MagicMock(),
|
||||
"src.models.densepose_head": MagicMock(),
|
||||
"src.models.modality_translation": MagicMock(),
|
||||
}):
|
||||
from src.services.pose_service import PoseService
|
||||
svc = PoseService(mock_settings, mock_domain_config)
|
||||
assert svc.last_error is None
|
||||
62
v1/tests/unit/test_rate_limit.py
Normal file
62
v1/tests/unit/test_rate_limit.py
Normal file
|
|
@ -0,0 +1,62 @@
|
|||
"""Tests for rate limiting middleware."""
|
||||
|
||||
import pytest
|
||||
from unittest.mock import MagicMock, AsyncMock, patch
|
||||
|
||||
|
||||
class TestRateLimitMiddleware:
|
||||
def test_init(self, mock_settings):
|
||||
with patch("src.api.middleware.rate_limit.get_settings", return_value=mock_settings):
|
||||
from src.api.middleware.rate_limit import RateLimitMiddleware
|
||||
app = MagicMock()
|
||||
mw = RateLimitMiddleware(app)
|
||||
assert "anonymous" in mw.rate_limits
|
||||
assert "authenticated" in mw.rate_limits
|
||||
assert "admin" in mw.rate_limits
|
||||
|
||||
def test_exempt_paths(self, mock_settings):
|
||||
with patch("src.api.middleware.rate_limit.get_settings", return_value=mock_settings):
|
||||
from src.api.middleware.rate_limit import RateLimitMiddleware
|
||||
app = MagicMock()
|
||||
mw = RateLimitMiddleware(app)
|
||||
assert "/health" in mw.exempt_paths
|
||||
assert "/metrics" in mw.exempt_paths
|
||||
|
||||
def test_is_exempt(self, mock_settings):
|
||||
with patch("src.api.middleware.rate_limit.get_settings", return_value=mock_settings):
|
||||
from src.api.middleware.rate_limit import RateLimitMiddleware
|
||||
app = MagicMock()
|
||||
mw = RateLimitMiddleware(app)
|
||||
assert mw._is_exempt_path("/health") is True
|
||||
assert mw._is_exempt_path("/api/v1/pose/current") is False
|
||||
|
||||
def test_path_specific_limits(self, mock_settings):
|
||||
with patch("src.api.middleware.rate_limit.get_settings", return_value=mock_settings):
|
||||
from src.api.middleware.rate_limit import RateLimitMiddleware
|
||||
app = MagicMock()
|
||||
mw = RateLimitMiddleware(app)
|
||||
assert "/api/v1/pose/current" in mw.path_limits
|
||||
assert mw.path_limits["/api/v1/pose/current"]["requests"] == 60
|
||||
|
||||
def test_trusted_proxies_not_blocked(self, mock_settings):
|
||||
with patch("src.api.middleware.rate_limit.get_settings", return_value=mock_settings):
|
||||
from src.api.middleware.rate_limit import RateLimitMiddleware
|
||||
app = MagicMock()
|
||||
mw = RateLimitMiddleware(app)
|
||||
assert not mw._is_client_blocked("new-client-id")
|
||||
|
||||
|
||||
class TestRateLimitConfig:
|
||||
def test_anonymous_limit(self, mock_settings):
|
||||
with patch("src.api.middleware.rate_limit.get_settings", return_value=mock_settings):
|
||||
from src.api.middleware.rate_limit import RateLimitMiddleware
|
||||
app = MagicMock()
|
||||
mw = RateLimitMiddleware(app)
|
||||
assert mw.rate_limits["anonymous"]["burst"] == 10
|
||||
|
||||
def test_admin_limit(self, mock_settings):
|
||||
with patch("src.api.middleware.rate_limit.get_settings", return_value=mock_settings):
|
||||
from src.api.middleware.rate_limit import RateLimitMiddleware
|
||||
app = MagicMock()
|
||||
mw = RateLimitMiddleware(app)
|
||||
assert mw.rate_limits["admin"]["requests"] == 10000
|
||||
68
v1/tests/unit/test_stream_service.py
Normal file
68
v1/tests/unit/test_stream_service.py
Normal file
|
|
@ -0,0 +1,68 @@
|
|||
"""Tests for StreamService."""
|
||||
|
||||
import pytest
|
||||
from unittest.mock import MagicMock, AsyncMock, patch
|
||||
|
||||
|
||||
class TestStreamServiceLifecycle:
|
||||
def test_init(self, mock_settings, mock_domain_config):
|
||||
from src.services.stream_service import StreamService
|
||||
svc = StreamService(mock_settings, mock_domain_config)
|
||||
assert svc.is_running is False
|
||||
assert len(svc.connections) == 0
|
||||
assert svc.stats["active_connections"] == 0
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_initialize(self, mock_settings, mock_domain_config):
|
||||
from src.services.stream_service import StreamService
|
||||
svc = StreamService(mock_settings, mock_domain_config)
|
||||
await svc.initialize()
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_start(self, mock_settings, mock_domain_config):
|
||||
mock_settings.enable_real_time_processing = False
|
||||
from src.services.stream_service import StreamService
|
||||
svc = StreamService(mock_settings, mock_domain_config)
|
||||
await svc.start()
|
||||
assert svc.is_running is True
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_stop(self, mock_settings, mock_domain_config):
|
||||
mock_settings.enable_real_time_processing = False
|
||||
from src.services.stream_service import StreamService
|
||||
svc = StreamService(mock_settings, mock_domain_config)
|
||||
await svc.start()
|
||||
await svc.stop()
|
||||
assert svc.is_running is False
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_double_start(self, mock_settings, mock_domain_config):
|
||||
mock_settings.enable_real_time_processing = False
|
||||
from src.services.stream_service import StreamService
|
||||
svc = StreamService(mock_settings, mock_domain_config)
|
||||
await svc.start()
|
||||
await svc.start() # should be idempotent
|
||||
assert svc.is_running is True
|
||||
|
||||
|
||||
class TestStreamServiceConnections:
|
||||
def test_no_connections_on_init(self, mock_settings, mock_domain_config):
|
||||
from src.services.stream_service import StreamService
|
||||
svc = StreamService(mock_settings, mock_domain_config)
|
||||
assert svc.stats["total_connections"] == 0
|
||||
assert svc.stats["messages_sent"] == 0
|
||||
|
||||
def test_buffer_sizes(self, mock_settings, mock_domain_config):
|
||||
mock_settings.stream_buffer_size = 50
|
||||
from src.services.stream_service import StreamService
|
||||
svc = StreamService(mock_settings, mock_domain_config)
|
||||
assert svc.pose_buffer.maxlen == 50
|
||||
assert svc.csi_buffer.maxlen == 50
|
||||
|
||||
|
||||
class TestStreamServiceBroadcast:
|
||||
def test_stats_messages_failed_init_zero(self, mock_settings, mock_domain_config):
|
||||
from src.services.stream_service import StreamService
|
||||
svc = StreamService(mock_settings, mock_domain_config)
|
||||
assert svc.stats["messages_failed"] == 0
|
||||
assert svc.stats["data_points_streamed"] == 0
|
||||
Loading…
Add table
Add a link
Reference in a new issue