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

eventcv_core/
lib.rs
