csv转tensor
def csv_to_tensor(csvDate):
df = pd.read_csv(csvDate)
array = np.array(df)
tensor = torch.tensor(array, dtype=torch.float64)
return tensor
tensor转PIL
def tensor_to_PIL(tensor):
unloader = transforms.ToPILImage()
image = tensor.cpu().clone()
image = image.squeeze(0)
image = unloader(image)
return image
在tensorboard中展示
def show_in_tensorboard(tensor):
if tensor.dim() < 3:
tensor = tensor.unsqueeze(0)
writer = SummaryWriter("logs")
writer.add_image("Tensor_img", tensor)
writer.close()
return tensor
保存为指定格式的图片
def save_as_img(tensor, img_name, img_type):
tensor_to_PIL(tensor).save(img_name + '.' + img_type)
操作实例:
import numpy as np
import pandas as pd
import torch
from torch.utils.tensorboard import SummaryWriter
from torchvision import transforms
csvDateSet = './00000.csv'
def csv_to_tensor(csvDate):
df = pd.read_csv(csvDate)
array = np.array(df)
tensor = torch.tensor(array, dtype=torch.float64)
return tensor
def tensor_to_PIL(tensor):
unloader = transforms.ToPILImage()
image = tensor.cpu().clone()
image = image.squeeze(0)
image = unloader(image)
return image
def show_in_tensorboard(tensor):
if tensor.dim() < 3:
tensor = tensor.unsqueeze(0)
writer = SummaryWriter("logs")
writer.add_image("Tensor_img", tensor)
writer.close()
return tensor
def save_as_img(tensor, img_name, img_type):
tensor_to_PIL(tensor).save(img_name + '.' + img_type)
if __name__ == '__main__':
my_tensor = csv_to_tensor(csvDateSet)
save_as_img(my_tensor, 'example', 'jpg')
my_tensor = show_in_tensorboard(my_tensor)