#!/usr/bin/env python3
"""
City3D-MultiGen — pipeline runner.

This runs the reconstruction stages for one city in order. It does NOT host any
data: it drives the same scripts documented in the README to rebuild the aligned
multi-modal tiles locally from (1) source 3D data you downloaded yourself and
(2) live Google Maps Static API calls made under your own key.

Manual prerequisites (NOT automated here — see README.md):
  1. Download the source 3D data:
       - Melbourne: City of Melbourne 3D Point Cloud 2018 (LAS).
       - HoliCity (London): FBX meshes, then sample a point cloud to LAS with
         CloudCompare, and georeference it with holicity/convert_coord.py and
         holicity/add_coord_head.py.
  2. Install PDAL (conda install -c conda-forge pdal) — the tiler calls it.
  3. Export your Google credentials:
       GOOGLE_MAPS_API_KEY, GOOGLE_MAPS_URL_SIGNING_SECRET, GOOGLE_MAPS_STYLE_MAP_ID
  4. Set the input/output paths at the top of each stage script (the tilers read
     their LAS input dir and output dir from module-level constants).

Stages run by this script (per city):
  A. <city>/export_las_blocks_noKML.py  -> tiles + per-tile DSM + BEV
  B. <city>/Obtain_corresponding_map_signed.py -> satellite + 6 semantic masks
  C. make_splits.py                     -> train/val/test tile lists

Usage:
  python scripts/build_dataset.py --city melbourne
  python scripts/build_dataset.py --city holicity --data_root ./output --skip_splits
"""
import argparse
import os
import shutil
import subprocess
import sys

HERE = os.path.dirname(os.path.abspath(__file__))
ENV_VARS = ("GOOGLE_MAPS_API_KEY", "GOOGLE_MAPS_URL_SIGNING_SECRET", "GOOGLE_MAPS_STYLE_MAP_ID")


def check_prereqs():
    missing = [k for k in ENV_VARS if not os.environ.get(k)]
    if missing:
        sys.exit(f"[error] Missing environment variables: {', '.join(missing)}. See README.md.")
    if shutil.which("pdal") is None:
        sys.exit("[error] PDAL not found on PATH. Install it: conda install -c conda-forge pdal")


def run(script_rel, *cli_args):
    path = os.path.join(HERE, script_rel)
    cmd = [sys.executable, path, *cli_args]
    print(f"\n>>> {' '.join(cmd)}", flush=True)
    subprocess.run(cmd, check=True)


def main():
    ap = argparse.ArgumentParser(description="Run the City3D-MultiGen reconstruction stages.")
    ap.add_argument("--city", choices=["melbourne", "holicity"], required=True)
    ap.add_argument("--data_root", default="./output",
                    help="Directory holding the assembled tiles (used for the split step).")
    ap.add_argument("--skip_splits", action="store_true", help="Do not run make_splits.py.")
    args = ap.parse_args()

    check_prereqs()
    print(f"[info] Running the {args.city} pipeline. Ensure the manual prerequisites in this "
          f"script's docstring are done and paths are configured at the top of each stage script.")

    # Stage A — tile the (already downloaded / sampled) source point clouds.
    run(f"{args.city}/export_las_blocks_noKML.py")

    # Stage B — fetch satellite + semantic maps for the tiles produced in Stage A.
    if args.city == "melbourne":
        run("melbourne/Obtain_corresponding_map_signed.py", "--folder", args.data_root)
    else:
        run("holicity/Obtain_corresponding_map_signed.py")

    # Stage C — generate the train/val/test split lists.
    if not args.skip_splits:
        run("make_splits.py", "--data_root", args.data_root,
            "--out_dir", os.path.join(HERE, "..", "metadata", "splits"))

    print("\n[done] Reminder: Google Maps imagery is subject to the Google Maps Platform ToS; "
          "do not redistribute the fetched *_sat.png / *_map.png / *_<Class>.png files.")


if __name__ == "__main__":
    main()