fix: Clean up Rust warnings and add Python vital signs detection

Rust changes:
- Fix unused variable warnings in wifi-densepose-nn (densepose.rs, inference.rs, tensor.rs, translator.rs)
- Remove unused imports in wifi-densepose-mat (breathing.rs, pipeline.rs, csi_receiver.rs, debris_model.rs, vital_signs_classifier.rs)
- All tests continue to pass

Python changes:
- Add vital_signs.py module with BreathingDetector and HeartbeatDetector classes
- Mirror Rust wifi-densepose-mat detection functionality
- Update v1 package version to 1.2.0
- Export new vital signs classes from core module

rust-port/wifi-densepose-rs/crates/wifi-densepose-mat/src/detection/breathing.rs

@@ -1,6 +1,6 @@
 //! Breathing pattern detection from CSI signals.
 
-use crate::domain::{BreathingPattern, BreathingType, ConfidenceScore};
+use crate::domain::{BreathingPattern, BreathingType};
 
 /// Configuration for breathing detection
 #[derive(Debug, Clone)]

rust-port/wifi-densepose-rs/crates/wifi-densepose-mat/src/detection/pipeline.rs

@@ -3,7 +3,7 @@
 //! This module provides both traditional signal-processing-based detection
 //! and optional ML-enhanced detection for improved accuracy.
 
-use crate::domain::{ScanZone, VitalSignsReading, ConfidenceScore};
+use crate::domain::{ScanZone, VitalSignsReading};
 use crate::ml::{MlDetectionConfig, MlDetectionPipeline, MlDetectionResult};
 use crate::{DisasterConfig, MatError};
 use super::{

rust-port/wifi-densepose-rs/crates/wifi-densepose-mat/src/integration/csi_receiver.rs

@@ -28,8 +28,6 @@ use chrono::{DateTime, Utc};
 use std::collections::VecDeque;
 use std::io::{BufReader, Read};
 use std::path::Path;
-use std::sync::Arc;
-use tokio::sync::{mpsc, Mutex};
 
 /// Configuration for CSI receivers
 #[derive(Debug, Clone)]

rust-port/wifi-densepose-rs/crates/wifi-densepose-mat/src/ml/debris_model.rs

@@ -16,13 +16,10 @@
 //! - Depth estimation head with uncertainty (mean + variance output)
 
 use super::{DebrisFeatures, DepthEstimate, MlError, MlResult};
-use ndarray::{Array1, Array2, Array4, s};
-use std::collections::HashMap;
+use ndarray::{Array2, Array4};
 use std::path::Path;
-use std::sync::Arc;
-use parking_lot::RwLock;
 use thiserror::Error;
-use tracing::{debug, info, instrument, warn};
+use tracing::{info, instrument, warn};
 
 #[cfg(feature = "onnx")]
 use wifi_densepose_nn::{OnnxBackend, OnnxSession, InferenceOptions, Tensor, TensorShape};

rust-port/wifi-densepose-rs/crates/wifi-densepose-mat/src/ml/mod.rs

@@ -35,7 +35,6 @@ pub use vital_signs_classifier::{
 };
 
 use crate::detection::CsiDataBuffer;
-use crate::domain::{VitalSignsReading, BreathingPattern, HeartbeatSignature};
 use async_trait::async_trait;
 use std::path::Path;
 use thiserror::Error;

rust-port/wifi-densepose-rs/crates/wifi-densepose-mat/src/ml/vital_signs_classifier.rs

@@ -27,12 +27,8 @@ use crate::domain::{
     BreathingPattern, BreathingType, HeartbeatSignature, MovementProfile,
     MovementType, SignalStrength, VitalSignsReading,
 };
-use ndarray::{Array1, Array2, Array4, s};
-use std::collections::HashMap;
 use std::path::Path;
-use std::sync::Arc;
-use parking_lot::RwLock;
-use tracing::{debug, info, instrument, warn};
+use tracing::{info, instrument, warn};
 
 #[cfg(feature = "onnx")]
 use wifi_densepose_nn::{OnnxBackend, OnnxSession, InferenceOptions, Tensor, TensorShape};

rust-port/wifi-densepose-rs/crates/wifi-densepose-nn/src/densepose.rs

@@ -252,7 +252,7 @@ impl DensePoseHead {
         })?;
 
         let input_arr = input.as_array4()?;
-        let (batch, _channels, height, width) = input_arr.dim();
+        let (_batch, _channels, _height, _width) = input_arr.dim();
 
         // Apply shared convolutions
         let mut current = input_arr.clone();

rust-port/wifi-densepose-rs/crates/wifi-densepose-nn/src/inference.rs

@@ -206,7 +206,7 @@ impl Backend for MockBackend {
         self.output_shapes.get(name).cloned()
     }
 
-    fn run(&self, inputs: HashMap<String, Tensor>) -> NnResult<HashMap<String, Tensor>> {
+    fn run(&self, _inputs: HashMap<String, Tensor>) -> NnResult<HashMap<String, Tensor>> {
         let mut outputs = HashMap::new();
 
         for (name, shape) in &self.output_shapes {

rust-port/wifi-densepose-rs/crates/wifi-densepose-nn/src/tensor.rs

@@ -266,7 +266,7 @@ impl Tensor {
     }
 
     /// Apply softmax along axis
-    pub fn softmax(&self, axis: usize) -> NnResult<Tensor> {
+    pub fn softmax(&self, _axis: usize) -> NnResult<Tensor> {
         match self {
             Tensor::Float4D(a) => {
                 let max = a.fold(f32::NEG_INFINITY, |acc, &x| acc.max(x));

rust-port/wifi-densepose-rs/crates/wifi-densepose-nn/src/translator.rs

@@ -342,7 +342,7 @@ impl ModalityTranslator {
         })?;
 
         let input_arr = input.as_array4()?;
-        let (batch, _channels, height, width) = input_arr.dim();
+        let (_batch, _channels, _height, _width) = input_arr.dim();
 
         // Encode
         let mut encoder_outputs = Vec::new();
@@ -461,7 +461,7 @@ impl ModalityTranslator {
         weights: &ConvBlockWeights,
     ) -> NnResult<Array4<f32>> {
         let (batch, in_channels, in_height, in_width) = input.dim();
-        let (out_channels, _, kernel_h, kernel_w) = weights.conv_weight.dim();
+        let (out_channels, _, _kernel_h, _kernel_w) = weights.conv_weight.dim();
 
         // Upsample 2x
         let out_height = in_height * 2;
@@ -536,7 +536,7 @@ impl ModalityTranslator {
     fn apply_attention(
         &self,
         input: &Array4<f32>,
-        weights: &AttentionWeights,
+        _weights: &AttentionWeights,
     ) -> NnResult<(Array4<f32>, Array4<f32>)> {
         let (batch, channels, height, width) = input.dim();
         let seq_len = height * width;