Struct DetectorContext 

pub struct DetectorContext { /* private fields */ }

Reusable owner of every buffer the Shi-Tomasi detector touches: gradient planes, structure-tensor row buffers, the score plane, the candidate list, the spacing grid and the result vector.

Keep one per detection thread and call detect or detect_grid each time. Buffers grow on demand and are reused. To keep allocation out of the per-frame path, create the context with with_capacity: calls within its DetectorCapacity then perform no heap allocation, whatever the image content. Without a reservation, the first call allocates, and a later image with more candidates than any before can still grow a buffer. The free functions good_features_to_track and good_features_to_track_grid create a context per call.

Implementations

impl DetectorContext

pub fn new() -> Self

Creates an empty context. Buffers grow to fit on the first detection and are reused thereafter.

pub fn with_capacity(capacity: DetectorCapacity) -> Self

Creates a context with every buffer allocated for capacity.

pub fn reserve(&mut self, capacity: DetectorCapacity)

Allocates every buffer for capacity now, so that later calls within it do not allocate. Existing capacity is kept.

pub fn detect( &mut self, image: &GrayImage, quality_level: f32, min_distance: u32, ) -> &[Corner]

Detects corners as good_features_to_track does, returning them from the context’s own result buffer. The slice is valid until the next call.

pub fn detect_grid( &mut self, image: &GrayImage, grid: Grid, quality_level: f32, min_distance: u32, existing_points: &[(f32, f32)], ) -> &[Corner]

Detects corners per grid cell as good_features_to_track_grid does, returning them from the context’s own result buffer. The slice is valid until the next call.

Panics

Panics if grid.cols or grid.rows is zero.

Trait Implementations

impl Default for DetectorContext

fn default() -> Self

Returns the “default value” for a type.