use crate::{Embedding, MinOptMax, Ops, Options, OrtEngine, X, Y};
use anyhow::Result;
use image::DynamicImage;
// use std::path::PathBuf;
// use usearch::ffi::{IndexOptions, MetricKind, ScalarKind};

#[derive(Debug)]
pub enum Model {
    S,
    B,
}

#[derive(Debug)]
pub struct Dinov2 {
    engine: OrtEngine,
    pub height: MinOptMax,
    pub width: MinOptMax,
    pub batch: MinOptMax,
    pub hidden_size: usize,
}

impl Dinov2 {
    pub fn new(options: Options) -> Result<Self> {
        let mut engine = OrtEngine::new(&options)?;
        let (batch, height, width) = (
            engine.inputs_minoptmax()[0][0].to_owned(),
            engine.inputs_minoptmax()[0][2].to_owned(),
            engine.inputs_minoptmax()[0][3].to_owned(),
        );
        let which = match options.onnx_path {
            s if s.contains("b14") => Model::B,
            s if s.contains("s14") => Model::S,
            _ => todo!(),
        };
        let hidden_size = match which {
            Model::S => 384,
            Model::B => 768,
        };
        engine.dry_run()?;

        Ok(Self {
            engine,
            height,
            width,
            batch,
            hidden_size,
        })
    }

    pub fn run(&mut self, xs: &[DynamicImage]) -> Result<Y> {
        let xs_ = X::apply(&[
            Ops::Resize(
                xs,
                self.height.opt as u32,
                self.width.opt as u32,
                "Lanczos3",
            ),
            Ops::Normalize(0., 255.),
            Ops::Standardize(
                &[0.48145466, 0.4578275, 0.40821073],
                &[0.26862954, 0.2613026, 0.2757771],
                3,
            ),
            Ops::Nhwc2nchw,
        ])?;
        let ys = self.engine.run(vec![xs_])?;
        Ok(Y::default().with_embedding(Embedding::from(ys[0].to_owned())))
    }

    // pub fn build_index(&self, metric: Metric) -> Result<usearch::Index> {
    //     let metric = match metric {
    //         Metric::IP => MetricKind::IP,
    //         Metric::L2 => MetricKind::L2sq,
    //         Metric::Cos => MetricKind::Cos,
    //     };
    //     let options = IndexOptions {
    //         metric,
    //         dimensions: self.hidden_size,
    //         quantization: ScalarKind::F16,
    //         ..Default::default()
    //     };
    //     Ok(usearch::new_index(&options)?)
    // }

    // pub fn query_from_folder(
    //     &mut self,
    //     qurey: &str,
    //     gallery: &str,
    //     metric: Metric,
    // ) -> Result<Vec<(usize, f32, PathBuf)>> {
    //     // load query
    //     let query = DataLoader::try_read(qurey)?;
    //     let query = self.run(&[query])?;

    //     // build index & gallery
    //     let index = self.build_index(metric)?;
    //     let dl = DataLoader::default()
    //         .with_batch(self.batch.opt as usize)
    //         .load(gallery)?;
    //     let paths = dl.paths().to_owned();
    //     index.reserve(paths.len())?;

    //     // load feats
    //     for (idx, (x, _path)) in dl.enumerate() {
    //         let y = self.run(&x)?;
    //         index.add(idx as u64, &y.into_raw_vec())?;
    //     }

    //     // output
    //     let matches = index.search(&query.into_raw_vec(), index.size())?;
    //     let mut results: Vec<(usize, f32, PathBuf)> = Vec::new();
    //     matches
    //         .keys
    //         .into_iter()
    //         .zip(matches.distances)
    //         .for_each(|(k, score)| {
    //             results.push((k as usize, score, paths[k as usize].to_owned()));
    //         });

    //     Ok(results)
    // }

    // pub fn query_from_vec(
    //     &mut self,
    //     qurey: &str,
    //     gallery: &[&str],
    //     metric: Metric,
    // ) -> Result<Vec<(usize, f32, PathBuf)>> {
    //     // load query
    //     let query = DataLoader::try_read(qurey)?;
    //     let query = self.run(&[query])?;

    //     // build index & gallery
    //     let index = self.build_index(metric)?;
    //     index.reserve(gallery.len())?;
    //     let mut dl = DataLoader::default().with_batch(self.batch.opt as usize);
    //     gallery.iter().for_each(|x| {
    //         dl.load(x).unwrap();
    //     });

    //     // load feats
    //     let paths = dl.paths().to_owned();
    //     for (idx, (x, _path)) in dl.enumerate() {
    //         let y = self.run(&x)?;
    //         index.add(idx as u64, &y.into_raw_vec())?;
    //     }

    //     // output
    //     let matches = index.search(&query.into_raw_vec(), index.size())?;
    //     let mut results: Vec<(usize, f32, PathBuf)> = Vec::new();
    //     matches
    //         .keys
    //         .into_iter()
    //         .zip(matches.distances)
    //         .for_each(|(k, score)| {
    //             results.push((k as usize, score, paths[k as usize].to_owned()));
    //         });

    //     Ok(results)
    // }
}