eventcv_core/
lib.rs

1//! # eventcv-core
2//!
3//! The Rust core of **EventCV** — "OpenCV for event-based vision".
4//!
5//! Everything is built around [`EventStream`], a struct-of-arrays container of events
6//! (`xs`, `ys`, `ts`, `ps` columns plus sensor size and timestamp scale). Streams are
7//! constructed only through [`EventStreamBuilder`], which drops out-of-bounds events.
8//!
9//! The crate is organised into focused modules:
10//!
11//! - [`io`] — readers/writers for `.npz`, `.txt`, `.bag`, `.h5`, `.aedat`, `.dat`, plus the
12//!   [`io::load`] extension dispatcher and lazy [`io::SliceSource`] indexing for large files.
13//! - [`representation`] — event → dense tensor ([`representation::Representation`], e.g. voxel
14//!   grids and time surfaces).
15//! - [`transform`] — chainable event-domain geometry/temporal/polarity ops on streams.
16//! - [`camera`] — intrinsics and `undistort`.
17//! - [`features`], [`flow`], [`cluster`] — corner detection, optical flow, connected components.
18//! - [`feast`] — unsupervised online feature learning (FEAST adaptive-threshold clustering).
19//! - [`filter`], [`image`], [`viz`] — hot-pixel filtering, frame-domain resize, colormapped export.
20//! - [`bias`] — the adaptive-biasing control law that holds a live camera's event rate steady.
21//! - `device` — live USB event-camera capture into [`EventStream`] windows (`camera` feature).
22//!
23//! The `hdf5` feature (off by default to keep `cargo test` fast) enables the `.h5`/`.hdf5`
24//! reader by building libhdf5 from source. The `camera` feature (also off by default) enables the
25//! `device` module, pulling in the `neuromorphic-drivers` crate and a vendored libusb.
26
27use ndarray::Array2;
28
29pub mod bias;
30pub mod camera;
31pub mod cluster;
32#[cfg(feature = "camera")]
33pub mod device;
34pub mod feast;
35pub mod features;
36pub mod filter;
37pub mod flow;
38pub mod image;
39pub mod io;
40pub mod representation;
41pub mod transform;
42pub mod viz;
43
44const COLUMN_COUNT: usize = 4;
45
46/// A stream of events stored column-wise (struct-of-arrays). Columns compress and
47/// transform far better than interleaved rows, and timestamps use `i64` (µs) so
48/// real multi-second recordings fit. See `TASKS.md` §3.
49#[derive(Clone, Debug)]
50pub struct EventStream {
51    xs: Vec<u16>,
52    ys: Vec<u16>,
53    ts: Vec<i64>,
54    ps: Vec<bool>,
55    width: usize,
56    height: usize,
57    timestamp_scale_ms: f64,
58}
59
60#[derive(Clone, Copy, Debug, PartialEq, Eq)]
61pub struct Event {
62    pub x: usize,
63    pub y: usize,
64    pub timestamp: u64,
65    pub polarity: bool,
66}
67
68impl EventStream {
69    pub fn len(&self) -> usize {
70        self.xs.len()
71    }
72
73    pub fn is_empty(&self) -> bool {
74        self.xs.is_empty()
75    }
76
77    pub fn sensor_size(&self) -> (usize, usize) {
78        (self.width, self.height)
79    }
80
81    pub fn timestamp_scale_ms(&self) -> f64 {
82        self.timestamp_scale_ms
83    }
84
85    pub fn xs(&self) -> &[u16] {
86        &self.xs
87    }
88
89    pub fn ys(&self) -> &[u16] {
90        &self.ys
91    }
92
93    pub fn ts(&self) -> &[i64] {
94        &self.ts
95    }
96
97    pub fn ps(&self) -> &[bool] {
98        &self.ps
99    }
100
101    pub fn iter(&self) -> impl Iterator<Item = Event> + '_ {
102        (0..self.len()).map(move |index| Event {
103            x: self.xs[index] as usize,
104            y: self.ys[index] as usize,
105            timestamp: self.ts[index] as u64,
106            polarity: self.ps[index],
107        })
108    }
109
110    /// Materialises an owned `(N, 4)` array of `[x, y, t, p]` rows for numpy interop.
111    pub fn to_array2(&self) -> Array2<u64> {
112        let mut values = Vec::with_capacity(self.len() * COLUMN_COUNT);
113        for index in 0..self.len() {
114            values.push(u64::from(self.xs[index]));
115            values.push(u64::from(self.ys[index]));
116            values.push(self.ts[index] as u64);
117            values.push(u64::from(self.ps[index]));
118        }
119        Array2::from_shape_vec((self.len(), COLUMN_COUNT), values)
120            .expect("columns share a length by construction")
121    }
122
123    /// Test-only constructor from an `(N, 4)` `[x, y, t, p]` array. Preserves every
124    /// row verbatim (no bounds filtering) so fixtures can exercise error paths.
125    #[cfg(test)]
126    pub(crate) fn from_array2(
127        events: Array2<u64>,
128        width: usize,
129        height: usize,
130        timestamp_scale_ms: f64,
131    ) -> Self {
132        Self {
133            xs: events.column(0).iter().map(|&value| value as u16).collect(),
134            ys: events.column(1).iter().map(|&value| value as u16).collect(),
135            ts: events.column(2).iter().map(|&value| value as i64).collect(),
136            ps: events.column(3).iter().map(|&value| value != 0).collect(),
137            width,
138            height,
139            timestamp_scale_ms,
140        }
141    }
142}
143
144/// Builds an [`EventStream`] one event at a time, dropping events outside the
145/// sensor. The single construction path shared by readers and (future) transforms.
146#[derive(Clone, Debug)]
147pub struct EventStreamBuilder {
148    xs: Vec<u16>,
149    ys: Vec<u16>,
150    ts: Vec<i64>,
151    ps: Vec<bool>,
152    width: usize,
153    height: usize,
154    timestamp_scale_ms: f64,
155}
156
157impl EventStreamBuilder {
158    pub fn new(width: usize, height: usize, timestamp_scale_ms: f64) -> Self {
159        Self::with_capacity(width, height, timestamp_scale_ms, 0)
160    }
161
162    pub fn with_capacity(
163        width: usize,
164        height: usize,
165        timestamp_scale_ms: f64,
166        capacity: usize,
167    ) -> Self {
168        Self {
169            xs: Vec::with_capacity(capacity),
170            ys: Vec::with_capacity(capacity),
171            ts: Vec::with_capacity(capacity),
172            ps: Vec::with_capacity(capacity),
173            width,
174            height,
175            timestamp_scale_ms,
176        }
177    }
178
179    /// Appends an event, returning `false` if it lies outside the sensor and was
180    /// dropped. Callers that treat out-of-bounds events as errors inspect the result.
181    pub fn push(&mut self, x: u16, y: u16, timestamp: i64, polarity: bool) -> bool {
182        if usize::from(x) >= self.width || usize::from(y) >= self.height {
183            return false;
184        }
185        self.xs.push(x);
186        self.ys.push(y);
187        self.ts.push(timestamp);
188        self.ps.push(polarity);
189        true
190    }
191
192    pub fn len(&self) -> usize {
193        self.xs.len()
194    }
195
196    pub fn is_empty(&self) -> bool {
197        self.xs.is_empty()
198    }
199
200    pub fn build(self) -> EventStream {
201        EventStream {
202            xs: self.xs,
203            ys: self.ys,
204            ts: self.ts,
205            ps: self.ps,
206            width: self.width,
207            height: self.height,
208            timestamp_scale_ms: self.timestamp_scale_ms,
209        }
210    }
211}
212
213#[cfg(test)]
214mod tests {
215    use std::path::PathBuf;
216
217    use crate::io::{load, LoadOptions};
218
219    use super::{EventStream, EventStreamBuilder};
220
221    #[test]
222    fn loads_n_imagenet_events() {
223        let path = PathBuf::from(env!("CARGO_MANIFEST_DIR")).join("../../data/test/example.npz");
224        let stream = load(path, LoadOptions::default()).unwrap();
225        let events = stream.to_array2();
226
227        assert!(!stream.is_empty());
228        assert_eq!(stream.sensor_size(), (640, 480));
229        assert_eq!(events.dim(), (stream.len(), 4));
230        assert!(events.column(0).iter().all(|&x| x < 640));
231        assert!(events.column(1).iter().all(|&y| y < 480));
232        assert!(events.column(3).iter().all(|&polarity| polarity <= 1));
233    }
234
235    #[test]
236    fn builder_drops_out_of_bounds_events_and_keeps_columns_aligned() {
237        let mut builder = EventStreamBuilder::new(4, 3, 0.001);
238
239        assert!(builder.push(1, 2, 10, true));
240        assert!(!builder.push(4, 0, 20, false)); // x == width -> dropped
241        assert!(!builder.push(0, 3, 30, true)); // y == height -> dropped
242        assert!(builder.push(3, 0, 40, false));
243
244        let stream = builder.build();
245        assert_eq!(stream.len(), 2);
246        assert_eq!(stream.xs(), &[1, 3]);
247        assert_eq!(stream.ys(), &[2, 0]);
248        assert_eq!(stream.ts(), &[10, 40]);
249        assert_eq!(stream.ps(), &[true, false]);
250        assert_eq!(stream.sensor_size(), (4, 3));
251    }
252
253    #[test]
254    fn to_array2_round_trips_columns_in_xytp_order() {
255        let stream =
256            EventStream::from_array2(ndarray::array![[1, 2, 100, 1], [3, 0, 250, 0]], 4, 3, 0.001);
257        let events = stream.to_array2();
258
259        assert_eq!(events.dim(), (2, 4));
260        assert_eq!(events.row(0).to_vec(), vec![1, 2, 100, 1]);
261        assert_eq!(events.row(1).to_vec(), vec![3, 0, 250, 0]);
262    }
263}
eventcv_core/lib.rs

eventcv_core/
lib.rs
