API docs

Author: tyt2y3

visionmagic/src/aggregation.rs

@@ -1,3 +1,4 @@
+//! Processor to remove small clusters by merging into larger ones
 use std::collections::HashSet;
 use visioncortex::{Color, ColorImage};
 use visioncortex::color_clusters::Clusters;
@@ -14,12 +15,16 @@ pub struct Processor {
     counter: usize,
 }
 
+/// [`Clusters`]
 pub type Input = Clusters;
 
+/// [`ColorImage`]
 pub type Output = ColorImage;
 
 pub struct Params {
+    /// Allowed color difference between shapes in same aggregate
     pub deviation: f64,
+    /// Minimum patch size in area
     pub min_size: u32,
 }
 
@@ -29,9 +34,9 @@ struct Aggregate {
 }
 
 #[derive(Copy, Clone, Default, Eq, Ord, Hash, PartialEq, PartialOrd)]
-pub struct AggregateIndex(pub usize);
+struct AggregateIndex(pub usize);
 
-pub const ZERO: AggregateIndex = AggregateIndex(0);
+const ZERO: AggregateIndex = AggregateIndex(0);
 
 impl Default for Params {
     fn default() -> Self {
@@ -149,7 +154,7 @@ impl Processor {
         &mut self.aggregates[index.0 as usize]
     }
 
-    pub fn neighbours_of(&self, myselfi: AggregateIndex) -> Vec<AggregateIndex> {
+    fn neighbours_of(&self, myselfi: AggregateIndex) -> Vec<AggregateIndex> {
         let myself = self.get_agg(myselfi);
         let mut neighbours = HashSet::new();
 

visionmagic/src/cluster_stat.rs

@@ -1,3 +1,4 @@
+//! Processor to calculate color statistic on set of clusters
 use visioncortex::{ColorStat, ColorStatBuilder};
 use visioncortex::color_clusters::Clusters;
 use crate::pipeline::Processor as ProcessorTrait;
@@ -10,8 +11,10 @@ pub struct Processor {
     counter: usize,
 }
 
+/// [`Clusters`]
 pub type Input = Clusters;
 
+/// [`ColorStat`]
 pub type Output = ColorStat;
 
 #[derive(Default)]

visionmagic/src/clustering.rs

@@ -1,3 +1,4 @@
+//! Processor to perform clustering & hierarchical clustering on an image
 use visioncortex::ColorImage;
 use visioncortex::color_clusters::{Clusters, IncrementalBuilder, Runner, RunnerConfig, HIERARCHICAL_MAX};
 use crate::pipeline::Processor as ProcessorTrait;
@@ -8,12 +9,16 @@ pub struct Processor {
     builder: Option<IncrementalBuilder>,
 }
 
+/// [`ColorImage`]
 pub type Input = ColorImage;
 
+/// [`Clusters`]
 pub type Output = Clusters;
 
 pub struct Params {
+    /// Valid range is 1~256. More levels means finer gradient
     pub color_levels: u32,
+    /// Perform hierarchical clustering up to this size (area)
     pub hierarchical: u32,
 }
 

visionmagic/src/lib.rs

@@ -1,9 +1,10 @@
+//! Collection of vision & graphics algorithms
 pub use visioncortex;
 
 pub mod aggregation;
 pub mod cluster_stat;
 pub mod clustering;
-pub mod pipeline;
+mod pipeline;
 pub mod segmentation;
 pub mod simplification;
 

visionmagic/src/pipeline.rs

@@ -1,7 +1,11 @@
+/// Processor is an element of an image processing pipeline
 pub trait Processor {
 
+    /// Type definition of input
     type Input;
+    /// Type definition of output
     type Output;
+    /// Type definition of parameters
     type Params;
 
     /// Create a new Processor instance

visionmagic/src/segmentation.rs

@@ -1,3 +1,4 @@
+//! Processor to group clusters together by the disjoint set algorithm
 use std::collections::HashMap;
 use visioncortex::{Color, ColorImage, ColorSum};
 use visioncortex::color_clusters::{Cluster, Clusters, ClusterIndex};
@@ -12,12 +13,15 @@ pub struct Processor {
     counter: usize,
 }
 
+/// [`Clusters`]
 pub type Input = Clusters;
 
+/// [`ColorImage`]
 pub type Output = ColorImage;
 
 #[derive(Default)]
 pub struct Params {
+    /// Allowed color difference between shapes in same set
     pub deviation: f64,
 }
 

visionmagic/src/simplification.rs

@@ -1,3 +1,4 @@
+//! Processor to simplify an image by pruning the image tree
 use visioncortex::{Color, CompoundPath, PathSimplifyMode};
 use visioncortex::color_clusters::{Cluster, Clusters, ClustersView};
 use crate::pipeline::Processor as ProcessorTrait;
@@ -11,8 +12,10 @@ pub struct Processor {
     stop: usize,
 }
 
+/// [`Clusters`]
 pub type Input = Clusters;
 
+/// [`CompoundPath`] with [`Color`]
 pub type Output = Vec<OutputUnit>;
 
 pub struct OutputUnit {
@@ -21,7 +24,9 @@ pub struct OutputUnit {
 }
 
 pub struct Params {
+    /// Valid range is 0~65535. Ratio of how many nodes we retain from the image tree
     pub fidelity: u32,
+    /// Valid range is 0~65535. Ratio of how many points we use to outline each shape 
     pub shape_details: u32,
 }