# -*- coding: utf-8 -*-
import cv2
import numpy as np

class GreenLaserDetector:
    def __init__(self):
        """初始化绿色激光检测器"""
        # 针对短曝光激光点优化：降低最小识别面积
        self.min_area = 50
        self.max_area = 5000
        
        # 默认HSV参数
        self.h_low = 35
        self.h_high = 85
        self.s_low = 80
        self.s_high = 255
        self.v_low = 80
        self.v_high = 255
    
    def set_hsv_range(self, h_low, h_high, s_low, s_high, v_low, v_high):
        """设置HSV颜色范围"""
        self.h_low = h_low
        self.h_high = h_high
        self.s_low = s_low
        self.s_high = s_high
        self.v_low = v_low
        self.v_high = v_high
    
    def detect(self, frame):
        """
        检测绿色激光点
        
        Args:
            frame: BGR格式的图像
            
        Returns:
            results: 检测结果列表，每个元素为(cx, cy, w, h, area, circularity)
            mask: 二值掩码图像
        """
        # 转HSV
        hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
        
        # 绿色范围（需根据实际激光调整）
        lower_green = np.array([self.h_low, self.s_low, self.v_low])
        upper_green = np.array([self.h_high, self.s_high, self.v_high])
        mask = cv2.inRange(hsv, lower_green, upper_green)
        
        # 形态学去噪
        kernel = np.ones((5,5), np.uint8)
        mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)
        mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)
        
        # 查找轮廓
        contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
        
        results = []
        for cnt in contours:
            area = cv2.contourArea(cnt)
            if self.min_area < area < self.max_area:
                # 圆形度检测
                perimeter = cv2.arcLength(cnt, True)
                if perimeter > 0:
                    circularity = 4 * np.pi * area / (perimeter ** 2)
                    if circularity > 0.7:  # 圆度阈值
                        x, y, w, h = cv2.boundingRect(cnt)
                        cx, cy = x + w//2, y + h//2
                        results.append((cx, cy, w, h, area, circularity))
        return results, mask