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#![feature(iterator_try_collect)]
use clap::Parser;
use priority_queue::PriorityQueue;
use std::cmp::Ordering;
use std::collections::HashMap;
use std::path::PathBuf;
use embedders::*;
mod embedders;
#[derive(Debug, Clone, Copy, clap::ValueEnum)]
enum Embedder {
Brightness,
Hue,
}
#[derive(Debug, Parser)]
struct Args {
#[arg(short, long, default_value = "hue")]
embedder: Embedder,
images: Vec<PathBuf>,
}
//#[derive(Debug)]
//struct Config {
// base_dir: xdg::BaseDirectories,
//}
//
//fn get_config() -> Result<Config, String> {
// let dirs = xdg::BaseDirectories::with_prefix("embeddings-sort")
// .map_err(|_| "oh no")?;
//
// Ok(Config{base_dir: dirs})
//}
fn process_embedder<E>(mut e: E, args: Args) -> Result<Vec<PathBuf>, String>
where E: EmbedderT
{
// wrapper struct to
// - reverse the ordering
// - implement Ord, even though the type is backed by an f64
#[repr(transparent)]
#[derive(Debug, PartialEq)]
struct DownOrd (f64);
impl Eq for DownOrd {}
impl PartialOrd for DownOrd {
fn partial_cmp(&self, other: &Self) -> Option<Ordering> {
Some(self.cmp(other))
}
}
impl Ord for DownOrd {
fn cmp(&self, other: &Self) -> Ordering {
self.0.partial_cmp(&other.0).unwrap().reverse()
}
}
let num_ims = args.images.len();
if num_ims == 0 {
return Ok(Vec::new());
}
let embeds: Vec<_> = e
.embed(&args.images)?
.into_iter()
.collect();
let mut possible_edges =
PriorityQueue::with_capacity((num_ims * num_ims - num_ims) / 2);
let mut mst = HashMap::with_capacity(num_ims);
// here, we start at 0.
// we might get a better result in the end if we started with a vertex next
// to the lowest-cost edge, but we don't know which one that is (though we
// could compute that without changing our asymptotic complexity)
mst.insert(0, Vec::new());
for i in 1..num_ims {
possible_edges.push((0, i), DownOrd(embeds[0].dist(&embeds[i])));
}
// prims algorithm or something like that
while mst.len() < num_ims {
// find the edge with the least cost that connects us to a new vertex
let (new, old) = loop {
let ((a, b), _) = possible_edges.pop().unwrap();
if !mst.contains_key(&a) {
break (a, b);
}
else if !mst.contains_key(&b) {
break (b, a);
}
};
mst.insert(new, Vec::new());
// insert all the new edges we could take
mst.entry(old).and_modify(|v|v.push(new));
for i in 0..num_ims {
// don't consider edges taking us to nodes we already visited
if mst.contains_key(&i) {
continue;
}
possible_edges.push((new, i), DownOrd(embeds[new].dist(&embeds[i])));
}
}
// find TSP approximation via DFS through the MST
fn dfs(cur: usize, t: &HashMap<usize, Vec<usize>>, into: &mut Vec<usize>) {
into.push(cur);
t.get(&cur).unwrap().iter().for_each(|c| dfs(*c, t, into));
}
let mut tsp_path = Vec::with_capacity(num_ims);
dfs(0, &mst, &mut tsp_path);
Ok(tsp_path.iter().map(|i| args.images[*i].clone()).collect())
}
fn main() -> Result<(), String> {
//let cfg = get_config()?;
let args = Args::parse();
let tsp_path = match args.embedder {
Embedder::Brightness => process_embedder(BrightnessEmbedder, args),
Embedder::Hue => process_embedder(HueEmbedder, args),
}?;
for p in tsp_path {
println!("{:?}", p);
}
Ok(())
}
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