#!/usr/bin/env python3
"""Standalone CLI: detect main regions in a label image via Qwen VL, then crop.

Usage
-----
    python scripts/detect_regions.py <image_path> [--model MODEL] [--out OUT_DIR] [--key KEY]

Example
-------
    python scripts/detect_regions.py data/sample.png
    python scripts/detect_regions.py data/sample.png --model qwen2.5-vl-72b-instruct
"""
from __future__ import annotations

import argparse
import json
import logging
import sys
from pathlib import Path

# ── make sure the project root is on sys.path ──────────────────────────────
ROOT = Path(__file__).resolve().parent.parent
sys.path.insert(0, str(ROOT))

logging.basicConfig(
    level=logging.INFO,
    format="%(asctime)s [%(levelname)s] %(name)s – %(message)s",
)
logger = logging.getLogger("detect_regions")


def main() -> None:
    parser = argparse.ArgumentParser(
        description="Detect & crop main regions in a label image using Qwen VL"
    )
    parser.add_argument("image", help="Path to input image (PNG/JPEG)")
    parser.add_argument(
        "--model",
        default="qwen2.5-vl-7b-instruct",
        help="DashScope model ID (default: qwen2.5-vl-7b-instruct)",
    )
    parser.add_argument(
        "--out",
        default=None,
        help="Output directory for cropped regions (default: <image_dir>/regions/)",
    )
    parser.add_argument("--key", default=None, help="DASHSCOPE_API_KEY (overrides env)")
    parser.add_argument(
        "--api-max-side", type=int, default=1024,
        help="Max side length (px) of image sent to API (default: 1024). "
             "Crop is always done on the original full-res file.",
    )
    parser.add_argument("--no-crop", action="store_true", help="Only print coords, don't crop")
    parser.add_argument("--split", action="store_true",
                        help="Save each detected region separately (default: merge into one)")
    args = parser.parse_args()

    image_path = Path(args.image).expanduser().resolve()
    if not image_path.exists():
        parser.error(f"Image not found: {image_path}")

    output_dir = Path(args.out).expanduser().resolve() if args.out else image_path.parent / "regions"

    from backend.app.region_detector import detect_regions, crop_and_save, merge_regions

    logger.info("Image: %s", image_path)
    logger.info("Model: %s", args.model)

    regions, raw_response = detect_regions(
        image_path,
        api_key=args.key or None,
        model=args.model,
        api_max_side=args.api_max_side,
    )

    if not regions:
        logger.error("No regions detected. Raw model response:\n%s", raw_response)
        sys.exit(1)

    print("\n── Detected regions ──────────────────────────────────────")
    for i, r in enumerate(regions, 1):
        print(f"  {i:02d}. [{r.label}]  bbox=({r.x1},{r.y1})-({r.x2},{r.y2})  "
              f"size={r.width}×{r.height}px")
    print()

    coords_json = [
        {"label": r.label, "bbox": [r.x1, r.y1, r.x2, r.y2]}
        for r in regions
    ]
    print("JSON:")
    print(json.dumps(coords_json, ensure_ascii=False, indent=2))

    if not args.no_crop:
        if args.split:
            save_regions = regions
        else:
            merged = merge_regions(regions)
            save_regions = [merged]
            print(f"\n── Merged bbox: ({merged.x1},{merged.y1})-({merged.x2},{merged.y2})"
                  f"  size={merged.width}×{merged.height}px")

        results = crop_and_save(image_path, save_regions, output_dir)
        print(f"\n── Cropped file(s) saved to: {output_dir} ──")
        for item in results:
            print(f"  • {Path(item['path']).name}  ← {item['label']}")


if __name__ == "__main__":
    main()