class TrainPre(object): def __init__(self, img_mean, img_std): self.img_mean = img_mean self.img_std = img_std def __call__(self, img, hha): img = normalize(img, self.img_mean, self.img_std) hha = normalize(hha, self.img_mean, self.img_std) p_img = img.transpose(2, 0, 1) p_hha = hha.transpose(2, 0, 1) extra_dict = {'hha_img': p_hha} return p_img, extra_dict这段代码什么意思

这段代码是一个 Python 类，名为 TrainPre，用于对输入的图像和 HHA 图像进行预处理。在初始化时，传入均值和标准差作为参数。在调用时，将输入的图像和 HHA 图像进行归一化处理，并将它们转换为 PyTorch 可以处理的格式。然后将 HHA 图像存储在字典变量 extra_dict 中，并将处理后的图像和字典变量作为结果返回。

相关问题

优化代码class DeliveryRequest: def __init__(self, name, location, time): self.name = name self.location = location self.time = time class DeliveryStation: def __init__(self, location): self.location = location self.requests = [] def add_request(self, request): self.requests.append(request) def match_deliveryman(self, deliverymen): for request in self.requests: for deliveryman in deliverymen: if request.location == deliveryman.location and request.time == deliveryman.available_time: print(f"您有一个快递将送给{request.name}，请您按时送货") print(f"您的快递将由{deliveryman.name}在{request.time}送达，请您按时等候") deliverymen.remove(deliveryman) break class DeliveryMan: def __init__(self, name, location, available_time): self.name = name self.location = location self.available_time = available_time class Dispatcher: def __init__(self, delivery_stations, deliverymen): self.delivery_stations = delivery_stations self.deliverymen = deliverymen def dispatch(self): for station in self.delivery_stations: station.match_deliveryman(self.deliverymen)

可以考虑优化代码的可读性和效率，例如使用列表推导式和更好的命名：

class DeliveryRequest:
    def __init__(self, name, location, time):
        self.name = name
        self.location = location
        self.time = time

class DeliveryStation:
    def __init__(self, location):
        self.location = location
        self.requests = []

    def add_request(self, request):
        self.requests.append(request)

    def match_deliveryman(self, deliverymen):
        for request in self.requests:
            matching_deliverymen = [dm for dm in deliverymen if dm.location == request.location and dm.available_time == request.time]
            for deliveryman in matching_deliverymen:
                print(f"您有一个快递将送给{request.name}，请您按时送货")
                print(f"您的快递将由{deliveryman.name}在{request.time}送达，请您按时等候")
                deliverymen.remove(deliveryman)
                break

class DeliveryMan:
    def __init__(self, name, location, available_time):
        self.name = name
        self.location = location
        self.available_time = available_time

class Dispatcher:
    def __init__(self, delivery_stations, deliverymen):
        self.delivery_stations = delivery_stations
        self.deliverymen = deliverymen

    def dispatch(self):
        for station in self.delivery_stations:
            station.match_deliveryman(self.deliverymen)

这样，我们使用列表推导式来创建了一个匹配的快递员列表，然后使用一个 for 循环来遍历它。我们也使用更好的变量名来提高代码的可读性。

from objprint import op class Animal: def __init__(self,age): self.age = age class Person(Animal): def __init__(self, age,name): super().__init__(age) self.name = name class Male(Person): def __init__(self, age, name): super(Person,self).__init__(age) self.gender = "male" m = Male(32,"Peter") super(Male,m).__init__(32,"Peter") op(m)

这段代码也存在语法错误。在Male类中，应该使用super().__init__(age, name)来调用父类Person的构造函数，而不是使用super(Person, self).__init__(age)。同时，在Male类中，应该先调用父类的构造函数，然后再添加gender属性，否则会出现AttributeError异常。在修正这些问题之后，代码应该如下所示：

from objprint import op 

class Animal:
    def __init__(self, age):
        self.age = age

class Person(Animal):
    def __init__(self, age, name):
        super().__init__(age)
        self.name = name

class Male(Person):
    def __init__(self, age, name):
        super().__init__(age, name)
        self.gender = "male"

m = Male(32, "Peter")
super(Male, m).__init__(32, "Peter")
op(m)

这样，代码就不会出现语法错误，并且能够正常运行。注意，这里在最后一行代码中使用了op(m)来输出对象m的属性和方法，需要确保已经安装了objprint模块才能够使用op函数。