# vision/overflow_detector.py
import sys
import os
from vision.resize_tuili_image_main import classify_image_weighted, load_global_rois, crop_and_resize

# 添加项目根目录到Python路径
sys.path.append(os.path.join(os.path.dirname(__file__), '..'))

def detect_overflow_from_image(image_array, overflow_model, roi_file_path):
    """
    通过图像检测是否溢料
    :param image_array: 图像数组
    :param overflow_model: 溢料检测模型
    :param roi_file_path: ROI文件路径
    :return: 是否检测到溢料 (True/False)
    """
    try:
        # 检查模型是否已加载
        if overflow_model is None:
            print("堆料检测模型未加载")
            return False

        # 加载ROI区域
        rois = load_global_rois(roi_file_path)

        if not rois:
            print(f"没有有效的ROI配置: {roi_file_path}")
            return False

        if image_array is None:
            print("输入图像为空")
            return False

        # 裁剪和调整图像大小
        crops = crop_and_resize(image_array, rois, 640)

        # 对每个ROI区域进行分类检测
        for roi_resized, _ in crops:
            final_class, _, _, _ = classify_image_weighted(roi_resized, overflow_model, threshold=0.4)
            if "大堆料" in final_class or "小堆料" in final_class:
                print(f"检测到溢料: {final_class}")
                return True

        return False
    except Exception as e:
        print(f"溢料检测失败: {e}")
        return False