[pytorch] csv转tensor，tensor转图片

最新推荐文章于 2023-07-26 18:38:50 发布

尼古拉斯喵呜

最新推荐文章于 2023-07-26 18:38:50 发布

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文章标签： pytorch 深度学习 python 数据分析计算机视觉

本文链接：https://blog.youkuaiyun.com/Elm_Forest/article/details/124598016

该博客介绍了如何将CSV数据转换为PyTorch张量，并展示了将张量转换为PIL图像、在TensorBoard中展示以及保存为指定格式图片的流程。主要涉及数据处理和深度学习的辅助工具使用。

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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)