1. ToTensor()

2. Normalize()

# 1. ToTensor  把PIL图片类型数据或ndarry numpy数据类型转换为tensor类型数据
from cv2 import imread
from torchvision import transforms
from torch.utils.tensorboard import SummaryWriterimg_path = 'hymenoptera_data/train/bees/85112639_6e860b0469.jpg'
writer = SummaryWriter('logs')
def totensor():cv2_np = imread(img_path)trans_totensor = transforms.ToTensor()cv2_tensor = trans_totensor(cv2_np)writer.add_image('totensor', cv2_tensor)# 2. normalize  用平均值和标准差对张量图像做归一化
def normalize():'''output[channel] = (input[channel] - mean[channel]) / std[channel]:return:'''cv2_np = imread(img_path)trans_totensor = transforms.ToTensor()cv2_tensor = trans_totensor(cv2_np)print(cv2_tensor[0][0][0])trans_norm = transforms.Normalize([1, 2, 1], [1, 1, 6])norm_tensor = trans_norm.forward(cv2_tensor)writer.add_image('norm totensor', norm_tensor, 2)print(norm_tensor[0][0][0])if __name__ == '__main__':totensor()normalize()writer.close()