Function process_basic_shapes

modules/basic_shape_processor.py:1601–1757

处理所有基本图形（SAM3结果 + CV补充检测），生成DrawIO XML。 :param image: 原始图像 (BGR) :param sam3_elements: SAM3提取的元素字典 :return: 格式化的XML字符串

(image: np.ndarray, sam3_elements: dict)

# ======================== 独立处理函数 ========================
def process_basic_shapes(image: np.ndarray, sam3_elements: dict) -> str:
    """
    处理所有基本图形（SAM3结果 + CV补充检测），生成DrawIO XML。
    
    :param image: 原始图像 (BGR)
    :param sam3_elements: SAM3提取的元素字典
    :return: 格式化的XML字符串
    """
    h, w = image.shape[:2]
    
    # 运行CV补充检测
    cv_results = detect_rectangles_robust(image, sam3_elements, {
        "min_area_ratio": 0.07,
        "max_area_ratio": 0.95
    })
    
    # 收集所有需要绘制的元素
    containers_list = []
    shapes_list = []
    
    # 来自 SAM3 的 container
    if "container" in sam3_elements:
        for item in sam3_elements["container"]:
            item_copy = item.copy()
            item_copy["_type"] = "container"
            item_copy["_source"] = "sam3"
            containers_list.append(item_copy)
            
    # 来自 CV 检测的 containers
    for item in cv_results["containers"]:
        item_copy = item.copy()
        item_copy["_type"] = "container"
        item_copy["_source"] = "cv"
        containers_list.append(item_copy)
        
    # 来自 SAM3 的其他形状
    for key, items in sam3_elements.items():
        if key in VECTOR_TYPES and key != "container":
            for item in items:
                item_copy = item.copy()
                item_copy["_type"] = key
                item_copy["_source"] = "sam3"
                shapes_list.append(item_copy)
                
    # 来自 CV 检测的 rectangles
    for item in cv_results["rectangles"]:
        item_copy = item.copy()
        item_copy["_type"] = "rectangle"
        item_copy["_source"] = "cv"
        shapes_list.append(item_copy)
    
    # 排序：面积大的在底层
    def calculate_element_area(bbox):
        return (bbox[2] - bbox[0]) * (bbox[3] - bbox[1])
    
    containers_list.sort(key=lambda x: calculate_element_area(x["bbox"]), reverse=True)
    shapes_list.sort(key=lambda x: calculate_element_area(x["bbox"]), reverse=True)