152 lines
4.7 KiB
Python
152 lines
4.7 KiB
Python
try:
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from .leg_baidu import LegAcupointsDetector as BaiduDetector
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from .leg_yolo import LegAcupointsDetector as YoloDetector
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from .leg_manual import LegAcupointsDetector as ManualDetector
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from .config import Config
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except ImportError:
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from leg_baidu import LegAcupointsDetector as BaiduDetector
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from leg_yolo import LegAcupointsDetector as YoloDetector
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from leg_manual import LegAcupointsDetector as ManualDetector
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from config import Config
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import os
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class LegDetector:
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"""腿部穴位检测器，整合了Baidu自动检测和手动标注两种方法"""
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def __init__(self):
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"""
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初始化检测器，同时加载Baidu检测器和手动检测器
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"""
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self.baidu = BaiduDetector()
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self.yolo = YoloDetector()
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self.manual = ManualDetector()
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def detect_by_yolo(self, image_path, output_path=None):
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"""
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使用百度API进行自动检测
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参数:
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image_path (str): 输入图片路径
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output_path (str, optional): 输出图片路径，如果不指定则自动生成
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返回:
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dict: 包含穴位坐标的字典 {"穴位名称": (x, y), ...}
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"""
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if output_path is None:
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# 从输入图片名生成输出图片名
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base_name = os.path.basename(image_path)
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name, ext = os.path.splitext(base_name)
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output_path = Config.get_output_path(f"{name}_yolo{ext}")
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return self.yolo.process_image(image_path, output_path)
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def detect_by_baidu(self, image_path, output_path=None):
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"""
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使用百度API进行自动检测
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参数:
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image_path (str): 输入图片路径
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output_path (str, optional): 输出图片路径，如果不指定则自动生成
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返回:
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dict: 包含穴位坐标的字典 {"穴位名称": (x, y), ...}
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"""
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if output_path is None:
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# 从输入图片名生成输出图片名
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base_name = os.path.basename(image_path)
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name, ext = os.path.splitext(base_name)
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output_path = Config.get_output_path(f"{name}_baidu{ext}")
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return self.baidu.process_image(image_path, output_path)
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def detect_by_manual(self, image_path, json_data, output_path=None):
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"""
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使用手动标注数据进行检测
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参数:
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image_path (str): 输入图片路径
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json_data (dict): JSON数据
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output_path (str, optional): 输出图片路径，如果不指定则自动生成
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返回:
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dict: 包含穴位坐标的字典 {"穴位名称": (x, y), ...}
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"""
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if output_path is None:
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# 从输入图片名生成输出图片名
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base_name = os.path.basename(image_path)
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name, ext = os.path.splitext(base_name)
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output_path = Config.get_output_path(f"{name}_manual{ext}")
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self.manual.load_data(json_data)
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return self.manual.process_image(image_path, output_path)
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if __name__ == "__main__":
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# 示例用法
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sample_json = {
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"shapes": [
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{
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"label": "C1",
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"points": [
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[
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258,
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2.0
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],
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[
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265,
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130
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],
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[
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281,
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315
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]
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],
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"curvatures": {
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"thigh": 10,
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"calf": -10
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},
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"shape_type": "linestrip"
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},
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{
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"label": "C2",
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"points": [
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[
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350,
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1.55
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],
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[
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362,
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110
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],
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[
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401,
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302
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]
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],
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"curvatures": {
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"thigh": -10,
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"calf": 20
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},
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"shape_type": "linestrip"
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}
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]
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}
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# 创建检测器实例
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detector = LegDetector()
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# 测试图片路径
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test_image = Config.get_image_path("leg.png")
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# yolo检测示例
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yolo_results = detector.detect_by_yolo(test_image)
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print("yolo检测结果：")
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print(yolo_results)
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# baidu检测示例
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baidu_results = detector.detect_by_baidu(test_image)
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print("baidu检测结果：")
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print(baidu_results)
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# 手动标注检测示例
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manual_results = detector.detect_by_manual(test_image, sample_json)
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print("\n手动标注检测结果：")
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print(manual_results) |