import numpy as np
import torch


class ToTensorNormalize:
    def __init__(self, mean, std):
        self.mean = torch.tensor(mean, dtype=torch.float32).view(-1, 1, 1)
        self.std = torch.tensor(std, dtype=torch.float32).view(-1, 1, 1)

    def __call__(self, image):
        image_np = np.asarray(image, dtype=np.float32) / 255.0
        tensor = torch.from_numpy(image_np).permute(2, 0, 1).contiguous()
        return (tensor - self.mean) / self.std