//! End-to-end reconstruction pipeline skeleton.
//!
//! This mirrors the full-program example of the reference `colmap` crate, using
//! this crate's actual API. The implemented step (camera inference) runs for
//! real; the scaffolded steps report that they are not ported yet instead of
//! aborting, so you can see the intended flow end to end.
//!
//! ```text
//! cargo run --example reconstruct -- ../images
//! ```

use std::path::{Path, PathBuf};

use colmap::feature::{FeatureExtractionOptions, FeatureMatchingOptions};
use colmap::mvs::{patch_match_stereo, stereo_fusion, PatchMatchOptions, StereoFusionOptions};
use colmap::sfm::{incremental_mapping, IncrementalPipelineOptions};

fn report(step: &str, result: colmap::Result<()>) {
    match result {
        Ok(()) => println!("  ✓ {step}"),
        Err(err) => println!("  … {step}: {err}"),
    }
}

fn main() {
    let image_dir: PathBuf = std::env::args()
        .nth(1)
        .map(PathBuf::from)
        .unwrap_or_else(|| PathBuf::from(concat!(env!("CARGO_MANIFEST_DIR"), "/../images")));
    let database = Path::new("/tmp/colmap-rs/database.db");
    let workspace = Path::new("/tmp/colmap-rs/sparse");

    println!("Reconstructing from {}", image_dir.display());

    // 1. Camera inference from image headers (implemented).
    match colmap::image::infer_shared_cameras_in_dir(&image_dir) {
        Ok((cameras, assignment)) => println!(
            "  ✓ inferred {} camera(s) for {} images",
            cameras.len(),
            assignment.len()
        ),
        Err(err) => {
            eprintln!("  ✗ camera inference failed: {err}");
            return;
        }
    }

    // 2. Feature extraction & matching (scaffolded).
    report(
        "feature extraction",
        colmap::feature::extract_features(database, &image_dir, &FeatureExtractionOptions::default()),
    );
    report(
        "exhaustive matching",
        colmap::feature::match_exhaustive(database, &FeatureMatchingOptions::default()),
    );

    // 3. Sparse SfM reconstruction (scaffolded).
    match incremental_mapping(database, &image_dir, workspace, &IncrementalPipelineOptions::default()) {
        Ok(recs) => println!("  ✓ sparse reconstruction: {} model(s)", recs.len()),
        Err(err) => println!("  … sparse SfM: {err}"),
    }

    // 4. Dense MVS reconstruction (scaffolded).
    report("patch-match stereo", patch_match_stereo(workspace, &PatchMatchOptions::default()));
    report("stereo fusion", stereo_fusion(workspace, &StereoFusionOptions::default()));
}