use std::{path::Path, sync::Arc};

use imsearch::{
    image::Image,
    search_index::{Database, FeatureGenerator, FeatureResult},
};

fn average_brightness(image: Arc<Image<f32>>) -> (String, FeatureResult) {
    let bright = image
        .pixels()
        .iter()
        .map(|(r, g, b, _)| (r + g + b) / 3.0 / 255.0)
        .sum::<f32>()
        / image.pixels().len() as f32;

    (
        String::from("average_brightness"),
        FeatureResult::Percent(bright),
    )
}

#[test]
fn test_database_basic() {
    let files: Vec<std::path::PathBuf> = std::fs::read_dir("res/integration/")
        .unwrap()
        .map(|f| f.unwrap().path())
        .collect();

    let feats: Vec<FeatureGenerator> = vec![average_brightness];

    let db = Database::new(&files, feats).unwrap();

    for results in db
        .search(
            std::path::Path::new("res/integration/gray_image.png"),
            average_brightness,
        )
        .unwrap()
    {
        println!(
            "path: {} similarity: {}",
            results.0.as_os_str().to_str().unwrap(),
            results.1
        );
    }
}

#[test]
fn test_database_files() {
    let json = Path::new("db.json");

    {
        let files: Vec<std::path::PathBuf> = std::fs::read_dir("res/integration/")
            .unwrap()
            .map(|f| f.unwrap().path())
            .collect();

        let feats: Vec<FeatureGenerator> = vec![average_brightness];

        let db = Database::new(&files, feats).unwrap();

        db.write_to_file(json);
    }

    {
        let db = Database::from_file(json);

        for results in db
            .search(
                std::path::Path::new("res/integration/gray_image.png"),
                average_brightness,
            )
            .unwrap()
        {
            println!(
                "path: {} similarity: {}",
                results.0.as_os_str().to_str().unwrap(),
                results.1
            );
        }
    }
}