try:
    from .leg_baidu import LegAcupointsDetector as BaiduDetector
    from .leg_yolo import LegAcupointsDetector as YoloDetector
    from .leg_manual import LegAcupointsDetector as ManualDetector
    from .config import Config
except ImportError:
    from leg_baidu import LegAcupointsDetector as BaiduDetector
    from leg_yolo import LegAcupointsDetector as YoloDetector
    from leg_manual import LegAcupointsDetector as ManualDetector
    from config import Config
import os

class LegDetector:
    """腿部穴位检测器，整合了Baidu自动检测和手动标注两种方法"""
    
    def __init__(self):
        """
        初始化检测器，同时加载Baidu检测器和手动检测器
        """
        self.baidu = BaiduDetector()
        self.yolo = YoloDetector()
        self.manual = ManualDetector()
    def detect_by_yolo(self, image_path, output_path=None):
        """
        使用百度API进行自动检测

        参数:
        image_path (str): 输入图片路径
        output_path (str, optional): 输出图片路径，如果不指定则自动生成

        返回:
        dict: 包含穴位坐标的字典 {"穴位名称": (x, y), ...}
        """
        if output_path is None:
            # 从输入图片名生成输出图片名
            base_name = os.path.basename(image_path)
            name, ext = os.path.splitext(base_name)
            output_path = Config.get_output_path(f"{name}_yolo{ext}")

        return self.yolo.process_image(image_path, output_path)
        
    def detect_by_baidu(self, image_path, output_path=None):
        """
        使用百度API进行自动检测

        参数:
        image_path (str): 输入图片路径
        output_path (str, optional): 输出图片路径，如果不指定则自动生成

        返回:
        dict: 包含穴位坐标的字典 {"穴位名称": (x, y), ...}
        """
        if output_path is None:
            # 从输入图片名生成输出图片名
            base_name = os.path.basename(image_path)
            name, ext = os.path.splitext(base_name)
            output_path = Config.get_output_path(f"{name}_baidu{ext}")
            
        return self.baidu.process_image(image_path, output_path)
    
    def detect_by_manual(self, image_path, json_data, output_path=None):
        """
        使用手动标注数据进行检测

        参数:
        image_path (str): 输入图片路径
        json_data (dict): JSON数据
        output_path (str, optional): 输出图片路径，如果不指定则自动生成

        返回:
        dict: 包含穴位坐标的字典 {"穴位名称": (x, y), ...}
        """
        if output_path is None:
            # 从输入图片名生成输出图片名
            base_name = os.path.basename(image_path)
            name, ext = os.path.splitext(base_name)
            output_path = Config.get_output_path(f"{name}_manual{ext}")
            
        self.manual.load_data(json_data)
        return self.manual.process_image(image_path, output_path)

if __name__ == "__main__":
    # 示例用法
    sample_json = {
        "shapes": [
            {
                "label": "C1",
                "points": [
                [
                258,
                2.0
                ],
                [
                265,
                130
                ],
                [
                281,
                315
                ]
            ],
                "curvatures": {
                    "thigh": 10,
                    "calf": -10
                },
                "shape_type": "linestrip"
            },
            {
                "label": "C2",
                "points": [
                    [
                    350,
                    1.55
                    ],
                    [
                    362,
                    110
                    ],
                    [
                    401,
                    302
                    ]
                ],
                "curvatures": {
                    "thigh": -10,
                    "calf": 20
                },
                "shape_type": "linestrip"
            }
        ]
    }
    
    # 创建检测器实例
    detector = LegDetector()
    
    # 测试图片路径
    test_image = Config.get_image_path("leg.png")
    
    # yolo检测示例
    yolo_results = detector.detect_by_yolo(test_image)
    print("yolo检测结果：")
    print(yolo_results)

    # baidu检测示例
    baidu_results = detector.detect_by_baidu(test_image)
    print("baidu检测结果：")
    print(baidu_results)
    
    # 手动标注检测示例
    manual_results = detector.detect_by_manual(test_image, sample_json)
    print("\n手动标注检测结果：")
    print(manual_results)