import numpy as np

class ModelObj: # 网络对象
    def __init__(self, ObjID, ObjType, ObjLable, ParaString, ObjX, ObjY):
        self.ObjID = ObjID  # 图元号
        self.ObjType = ObjType  # 图元类别
        self.ObjLable = ObjLable  # 对象标签
        self.ParaString = ParaString  # 参数字符串
        self.ObjX = ObjX  # 对象位置x坐标
        self.ObjY = ObjY  # 对象位置y坐标
        
class Pool_Class(ModelObj):  # 池化对象
    def __init__(self, ObjID, ObjType, ObjLable, ParaString, ObjX, ObjY):
        super().__init__(ObjID, ObjType, ObjLable, ParaString, ObjX, ObjY)
        self.MaxPoolProc = self.pool_proc  # 基本操作函数
        self.SetPollPara = self.setpool_para  # 参数设置函数

    def pool_proc(self, image, PoolPara):
        pool_mode = PoolPara["pool_mode"]
        pool_size = PoolPara["pool_size"]
        stride = PoolPara["stride"]
        c, h, w = image.shape  # 获取输入特征图的高度和宽度
        out_h = int((h - pool_size) / stride) + 1  # 计算输出特征图的高度
        out_w = int((w - pool_size) / stride) + 1  # 计算输出特征图的宽度
        out = np.zeros((c, out_h, out_w))  # 初始化输出特征图为全零数组
        for k in range(c):  # 对于输出的每一个位置上计算：
            for i in range(out_h):
                for j in range(out_w):
                    window = image[k, i * stride:i * stride + pool_size,
                             j * stride:j * stride + pool_size]
                    if pool_mode == "max":  # 最大池化
                        out[k][i][j] = np.max(window)
                    elif pool_mode == "avg":  # 平均池化
                        out[k][i][j] = np.mean(window)
                    elif pool_mode == "min":  # 最小池化
                        out[k][i][j] = np.min(window)
                    else:  # 无效的池化类型
                        raise ValueError("Invalid pooling mode")
        return out  # 返回特征图。

    def setpool_para(self):  # 定义设置池化参数的函数
        pool_mode = input("请输入池化模式（max/avg/min）: ")  # 用户输入池化模式
        pool_size = int(input("请输入池化大小: "))  # 用户输入池化大小
        stride = int(input("请输入步长: "))  # 用户输入步长
        PoolPara = {"pool_mode": pool_mode, "pool_size": pool_size,
                    "stride": stride}  # 返回PoolPara参数，这里用字典来存储
        return PoolPara  # 返回PoolPara参数

if __name__ == '__main__':
    Pool = Pool_Class("Pool1", 3, "池化1", [], 300, 400)
    PoolPara = Pool.SetPollPara()
    print(PoolPara)