"""
PaddleOCR Engine

High-accuracy OCR using PaddleOCR.
Supports detection, recognition, and angle classification.
"""

import time
from typing import List, Optional, Tuple
import numpy as np
from loguru import logger

from .base import OCREngine, OCRConfig, OCRResult
from ..schemas.core import BoundingBox, OCRRegion

# Try to import PaddleOCR
try:
    from paddleocr import PaddleOCR
    HAS_PADDLEOCR = True
except ImportError:
    HAS_PADDLEOCR = False
    logger.warning(
        "PaddleOCR not installed. Install with: "
        "pip install paddleocr paddlepaddle-gpu (or paddlepaddle for CPU)"
    )


class PaddleOCREngine(OCREngine):
    """
    OCR engine using PaddleOCR.

    Features:
    - High accuracy text detection and recognition
    - Multi-language support
    - GPU acceleration
    - Angle classification for rotated text
    """

    # Language code mapping (PaddleOCR uses different codes)
    LANGUAGE_MAP = {
        "en": "en",
        "ch": "ch",
        "chinese_cht": "chinese_cht",
        "fr": "french",
        "german": "german",
        "es": "es",
        "it": "it",
        "pt": "pt",
        "ru": "ru",
        "japan": "japan",
        "korean": "korean",
        "ar": "ar",
        "hi": "hi",
        "latin": "latin",
    }

    def __init__(self, config: Optional[OCRConfig] = None):
        """Initialize PaddleOCR engine."""
        super().__init__(config)
        self._ocr: Optional[PaddleOCR] = None

    def initialize(self):
        """Initialize PaddleOCR model."""
        if not HAS_PADDLEOCR:
            raise RuntimeError(
                "PaddleOCR not installed. Install with: "
                "pip install paddleocr paddlepaddle-gpu"
            )

        if self._initialized:
            return

        logger.info("Initializing PaddleOCR engine...")

        # Map language codes
        lang = self.config.languages[0] if self.config.languages else "en"
        paddle_lang = self.LANGUAGE_MAP.get(lang, "en")

        try:
            self._ocr = PaddleOCR(
                use_angle_cls=self.config.use_angle_cls,
                lang=paddle_lang,
                use_gpu=self.config.use_gpu,
                gpu_mem=500,  # GPU memory limit in MB
                det_db_thresh=self.config.det_db_thresh,
                det_db_box_thresh=self.config.det_db_box_thresh,
                rec_batch_num=self.config.rec_batch_num,
                drop_score=self.config.drop_score,
                show_log=False,  # Suppress verbose logging
            )
            self._initialized = True
            logger.info(f"PaddleOCR initialized (lang={paddle_lang}, gpu={self.config.use_gpu})")

        except Exception as e:
            logger.error(f"Failed to initialize PaddleOCR: {e}")
            raise

    def recognize(
        self,
        image: np.ndarray,
        page_number: int = 0,
    ) -> OCRResult:
        """
        Perform OCR on an image using PaddleOCR.

        Args:
            image: Image as numpy array (RGB, HWC format)
            page_number: Page number for multi-page documents

        Returns:
            OCRResult with recognized text and regions
        """
        if not self._initialized:
            self.initialize()

        start_time = time.time()

        try:
            # Run OCR
            results = self._ocr.ocr(image, cls=self.config.use_angle_cls)

            # Process results
            regions = []
            all_texts = []
            total_confidence = 0.0

            # Results format: [[[box], (text, confidence)], ...]
            if results and results[0]:
                for idx, line in enumerate(results[0]):
                    if line is None:
                        continue

                    box_points = line[0]  # [[x1,y1], [x2,y2], [x3,y3], [x4,y4]]
                    text, confidence = line[1]

                    # Skip low confidence results
                    if confidence < self.config.min_confidence:
                        continue

                    # Convert polygon to bounding box
                    bbox = self._polygon_to_bbox(box_points, image.shape[:2])

                    # Create polygon points
                    polygon = [(float(p[0]), float(p[1])) for p in box_points]

                    region = OCRRegion(
                        text=text,
                        confidence=float(confidence),
                        bbox=bbox,
                        polygon=polygon,
                        page=page_number,
                        line_id=idx,
                        engine="paddleocr",
                    )
                    regions.append(region)
                    all_texts.append(text)
                    total_confidence += confidence

            processing_time = (time.time() - start_time) * 1000

            return OCRResult(
                regions=regions,
                full_text="\n".join(all_texts),
                confidence_avg=total_confidence / len(regions) if regions else 0.0,
                processing_time_ms=processing_time,
                engine="paddleocr",
                success=True,
            )

        except Exception as e:
            logger.error(f"PaddleOCR recognition failed: {e}")
            return OCRResult(
                regions=[],
                full_text="",
                confidence_avg=0.0,
                processing_time_ms=(time.time() - start_time) * 1000,
                engine="paddleocr",
                success=False,
                error=str(e),
            )

    def _polygon_to_bbox(
        self,
        points: List[List[float]],
        image_shape: Tuple[int, int],
    ) -> BoundingBox:
        """Convert polygon points to bounding box."""
        x_coords = [p[0] for p in points]
        y_coords = [p[1] for p in points]

        height, width = image_shape

        return BoundingBox(
            x_min=max(0, min(x_coords)),
            y_min=max(0, min(y_coords)),
            x_max=min(width, max(x_coords)),
            y_max=min(height, max(y_coords)),
            normalized=False,
            page_width=width,
            page_height=height,
        )

    def get_supported_languages(self) -> List[str]:
        """Return list of supported language codes."""
        return list(self.LANGUAGE_MAP.keys())

    def recognize_with_structure(
        self,
        image: np.ndarray,
        page_number: int = 0,
    ) -> Tuple[OCRResult, Optional[dict]]:
        """
        Perform OCR with structure analysis (tables, layout).

        Args:
            image: Image as numpy array
            page_number: Page number

        Returns:
            Tuple of (OCRResult, structure_info)
        """
        # First do regular OCR
        ocr_result = self.recognize(image, page_number)

        # PaddleOCR can also do table structure recognition
        # This would require ppstructure which we can add later
        structure_info = None

        return ocr_result, structure_info