# coding=utf-8
import easyocr
import numpy as np
import cv2
import logging

logger = logging.getLogger(__name__)

class EasyOcrKit:
    _instance = None
    _reader = None

    def __new__(cls, *args, **kwargs):
        if cls._instance is None:
            cls._instance = super(EasyOcrKit, cls).__new__(cls)
        return cls._instance

    def __init__(self, langs=['ch_sim', 'en'], gpu=True):
        """
        初始化 EasyOCR Reader
        :param langs: 识别语言列表
        :param gpu: 是否使用 GPU
        """
        # 检查是否需要重新初始化（例如从 GPU 切换到 CPU）
        if self._reader is not None:
            if hasattr(self, '_using_gpu') and self._using_gpu != gpu:
                logger.info(f"检测到 GPU 模式变更 ({self._using_gpu} -> {gpu})，重新初始化 Reader...")
                self._reader = None

        if self._reader is None:
            try:
                self._reader = easyocr.Reader(langs, gpu=gpu)
                self._using_gpu = gpu # 记录当前使用的模式
                logger.info(f"EasyOCR Reader 初始化成功 (gpu={gpu})")
            except Exception as e:
                logger.error(f"EasyOCR Reader 初始化失败: {e}")
                # 如果 GPU 失败，尝试回退到 CPU
                if gpu:
                    logger.warning("尝试回退到 CPU 模式...")
                    try:
                        self._reader = easyocr.Reader(langs, gpu=False)
                        self._using_gpu = False
                    except Exception as ex:
                        logger.error(f"EasyOCR CPU 模式回退也失败: {ex}")

    def read_text(self, image):
        """
        识别图片中的文字
        :param image: 图片路径或 OpenCV 图像对象
        :return: EasyOCR 识别结果列表
        """
        if self._reader is None:
            return []
        return self._reader.readtext(image)

    def find_text_position(self, image, target_text, threshold=0.5):
        """
        在图片中查找特定文本的位置
        :param image: 图片路径或 OpenCV 图像对象
        :param target_text: 目标文本
        :param threshold: 置信度阈值
        :return: (found_text, quad, probability) 如果没找到则返回 None
        """
        results = self.read_text(image)
        for (quad, text, prob) in results:
            if target_text in text and prob >= threshold:
                return text, quad, prob
        return None

    def get_normalized_rect(self, quad, width, height):
        """
        获取归一化的矩形坐标 [x1, y1, x2, y2] (0-1000)
        :param quad: EasyOCR 返回的四个顶点坐标
        :param width: 图片宽度
        :param height: 图片高度
        :return: [x1, y1, x2, y2]
        """
        pts = np.array(quad).astype(int)
        x_min = np.min(pts[:, 0])
        y_min = np.min(pts[:, 1])
        x_max = np.max(pts[:, 0])
        y_max = np.max(pts[:, 1])
        
        return [
            int(max(0, x_min) * 1000 / width),
            int(max(0, y_min) * 1000 / height),
            int(min(width, x_max) * 1000 / width),
            int(min(height, y_max) * 1000 / height)
        ]

# 便捷函数
def get_easyocr_reader(gpu=True):
    return EasyOcrKit(gpu=gpu)