<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[u010454261的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/u010454261</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; u010454261]]></copyright><item><title><![CDATA[pytorch tensor 获取指定值的indices]]></title><link>https://blog.youkuaiyun.com/u010454261/article/details/76860986</link><guid>https://blog.youkuaiyun.com/u010454261/article/details/76860986</guid><author>u010454261</author><pubDate>Wed, 01 Dec 2021 16:29:46 +0800</pubDate><description><![CDATA[pytorch tensor 获取指定值的indices]]></description><category></category></item><item><title><![CDATA[高斯衰减方案汇总]]></title><link>https://blog.youkuaiyun.com/u010454261/article/details/121150142</link><guid>https://blog.youkuaiyun.com/u010454261/article/details/121150142</guid><author>u010454261</author><pubDate>Thu, 04 Nov 2021 20:24:32 +0800</pubDate><description><![CDATA[3篇检测方法的文章中均包含高斯衰减相关的内容，记录一下，有问题再来看。

CSP论文:

GitHub - liuwei16/CSP: High-level Semantic Feature Detection: A New Perspective for Pedestrian Detection, CVPR, 2019High-level Semantic Feature Detection: A New Perspective for Pedestrian Detection, CVPR, 2019 -]]></description><category></category></item><item><title><![CDATA[python 小数值规范化显示]]></title><link>https://blog.youkuaiyun.com/u010454261/article/details/118820272</link><guid>https://blog.youkuaiyun.com/u010454261/article/details/118820272</guid><author>u010454261</author><pubDate>Fri, 16 Jul 2021 20:10:24 +0800</pubDate><description><![CDATA[小数固定显示2位数值:
 print("{:.2f}".format(3.1415926))


]]></description><category></category></item><item><title><![CDATA[时间戳转化]]></title><link>https://blog.youkuaiyun.com/u010454261/article/details/118027124</link><guid>https://blog.youkuaiyun.com/u010454261/article/details/118027124</guid><author>u010454261</author><pubDate>Fri, 18 Jun 2021 15:18:50 +0800</pubDate><description><![CDATA[#!/usr/bin/python3
# -*- coding: utf-8 -*

import time


def str_to_stamp(time_str):
  # 转换显示格式
  time1 = time.strptime(time_str, '%Y-%m-%d %H:%M:%S')
  # 转为时间戳
  time2 = int(time.mktime(time1))
  print(time2)
  return time2

def stamp_to_str(...]]></description><category></category></item><item><title><![CDATA[pytorch dataloader is killed by signal or unexpected segmentation fault]]></title><link>https://blog.youkuaiyun.com/u010454261/article/details/117951705</link><guid>https://blog.youkuaiyun.com/u010454261/article/details/117951705</guid><author>u010454261</author><pubDate>Wed, 16 Jun 2021 11:11:18 +0800</pubDate><description><![CDATA[tui jia

https://www.zywvvd.com/2020/12/03/deep_learning/pytorch/dataloader_segmentation_fault/dataloader_segmentation_fault/
]]></description><category></category></item><item><title><![CDATA[matplotlib显示图像翻转坐标]]></title><link>https://blog.youkuaiyun.com/u010454261/article/details/116100840</link><guid>https://blog.youkuaiyun.com/u010454261/article/details/116100840</guid><author>u010454261</author><pubDate>Sat, 24 Apr 2021 19:15:05 +0800</pubDate><description><![CDATA[最近使用matplotlib显示数组发现了一个问题, matplotlib默认是y轴向右，x轴向下，导致输出的数组旋转了90°。

修正方法: 使用xlim, ylim就好了，记一下，之后遇到类似的问题还可以来查。

from matplotlib import pyplot as plt
import numpy as np

# ax = plt.gca() # 没起作用，set_ticks_position的方法只能将x轴在上下变换，y轴在左右变换
# ax.xaxis.set_ticks_posit]]></description><category></category></item><item><title><![CDATA[3D坐标-常用角度]]></title><link>https://blog.youkuaiyun.com/u010454261/article/details/115874340</link><guid>https://blog.youkuaiyun.com/u010454261/article/details/115874340</guid><author>u010454261</author><pubDate>Mon, 19 Apr 2021 20:56:08 +0800</pubDate><description><![CDATA[yaw: 偏航角

pitch：俯仰角

roll：滚转角


]]></description><category></category></item><item><title><![CDATA[不同版本pytorch训的模型之间的转化]]></title><link>https://blog.youkuaiyun.com/u010454261/article/details/114936724</link><guid>https://blog.youkuaiyun.com/u010454261/article/details/114936724</guid><author>u010454261</author><pubDate>Wed, 17 Mar 2021 16:44:10 +0800</pubDate><description><![CDATA[写在开头: 本文仅记录自己遇到的问题，方便之后查阅。



最近用不同版本的pytorch训了一些模型，但使用pytorch1.3加载pytorch1.6训练的模型失败，显示如下所示等一些乱七八糟的错误。



但是没关系，因为本宝想到了一个好的解决办法，hiahiahia~



1. pytorch1.6 加载它自身生成的模型是没问题的，然后把加载后的模型dict生成pickle文件, 代码如下:

importpickleaspkl...]]></description><category></category></item><item><title><![CDATA[linux 挂载硬盘]]></title><link>https://blog.youkuaiyun.com/u010454261/article/details/113774732</link><guid>https://blog.youkuaiyun.com/u010454261/article/details/113774732</guid><author>u010454261</author><pubDate>Tue, 09 Feb 2021 19:39:09 +0800</pubDate><description><![CDATA[1 查看可用的硬盘：fdisk -l

2 格式化为指定文件格式：mkfs -t ext4 /dev/xxx

3 挂载硬盘到指定目录：mount /dev/xxx/data
]]></description><category></category></item><item><title><![CDATA[python pytorch 释放显存资源]]></title><link>https://blog.youkuaiyun.com/u010454261/article/details/109999475</link><guid>https://blog.youkuaiyun.com/u010454261/article/details/109999475</guid><author>u010454261</author><pubDate>Mon, 23 Nov 2020 16:10:03 +0800</pubDate><description><![CDATA[今天评测时，总莫名出现GPU OOM的问题。

参考https://cloud.tencent.com/developer/article/1626387， 发现了一种在变量使用完之后释放显存资源的方法.


torch.cuda.empty_cache()



]]></description><category></category></item><item><title><![CDATA[常用screen 命令]]></title><link>https://blog.youkuaiyun.com/u010454261/article/details/106944118</link><guid>https://blog.youkuaiyun.com/u010454261/article/details/106944118</guid><author>u010454261</author><pubDate>Wed, 24 Jun 2020 15:06:58 +0800</pubDate><description><![CDATA[新建screen命令：screen -S name

查看screen列表：screen -ls

恢复指定screen：screen -r name

删除screen: screen -S name-X quit


]]></description><category></category></item><item><title><![CDATA[多进程同步]]></title><link>https://blog.youkuaiyun.com/u010454261/article/details/89477005</link><guid>https://blog.youkuaiyun.com/u010454261/article/details/89477005</guid><author>u010454261</author><pubDate>Tue, 23 Apr 2019 17:22:39 +0800</pubDate><description><![CDATA[from multiprocessing import Process
import os
import time
def func(name):
    print('Run child process %s (%s)...' % (name, os.getpid()))
    time.sleep(3)    
if __name__=='__main__':
    print('Par...]]></description><category></category></item><item><title><![CDATA[获取subprocess输出并转化为数字]]></title><link>https://blog.youkuaiyun.com/u010454261/article/details/89385561</link><guid>https://blog.youkuaiyun.com/u010454261/article/details/89385561</guid><author>u010454261</author><pubDate>Thu, 18 Apr 2019 18:59:23 +0800</pubDate><description><![CDATA[vimprint_num.py


print(111)



vim test.py


import subprocess

cmd = ['python', 'print_num.py']

p = subprocess.Popen(cmd, stdin=subprocess.PIPE, stdout=subprocess.PIPE)
p.wait()
out = p.stdout.re...]]></description><category></category></item><item><title><![CDATA[[转载]python 字符数字转换]]></title><link>https://blog.youkuaiyun.com/u010454261/article/details/89229905</link><guid>https://blog.youkuaiyun.com/u010454261/article/details/89229905</guid><author>u010454261</author><pubDate>Fri, 12 Apr 2019 11:54:00 +0800</pubDate><description><![CDATA[本文参考自https://www.cnblogs.com/wuxiangli/p/6046800.html

比如现在有字符串:
x = '[[5], [6, 11], [0, 8, 9], [7, 13, 0, 1]]'

想根据该字符串得到一个list，使用x_list = eval(x)即可

以下内容转载自原博主文章:https://www.cnblogs.com/wuxiangli/p/...]]></description><category></category></item><item><title><![CDATA[SyntaxError: non-default argument follows default argument]]></title><link>https://blog.youkuaiyun.com/u010454261/article/details/85938654</link><guid>https://blog.youkuaiyun.com/u010454261/article/details/85938654</guid><author>u010454261</author><pubDate>Sun, 06 Jan 2019 17:43:25 +0800</pubDate><description><![CDATA[错误信息:

def avg_pool(self, inputs, op_type, output_channel=None, pooling_size):

                ^

SyntaxError: non-default argument follows default argument

 

解决办法：

python中函数中的所有默认参数的字段均应该写在不含默认值参...]]></description><category></category></item><item><title><![CDATA[pickle 序列化与反序列化]]></title><link>https://blog.youkuaiyun.com/u010454261/article/details/85283283</link><guid>https://blog.youkuaiyun.com/u010454261/article/details/85283283</guid><author>u010454261</author><pubDate>Thu, 27 Dec 2018 15:00:18 +0800</pubDate><description><![CDATA[废话不多说，直接上代码


import pickle

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

    def work(self):
        print(self.name)
...]]></description><category></category></item><item><title><![CDATA[pytorch指定使用的gpu设备]]></title><link>https://blog.youkuaiyun.com/u010454261/article/details/85274900</link><guid>https://blog.youkuaiyun.com/u010454261/article/details/85274900</guid><author>u010454261</author><pubDate>Thu, 27 Dec 2018 11:26:29 +0800</pubDate><description><![CDATA[最近在使用pytorch写程序，想在指定的GPU设备上执行。

假设函数func( )使用到了GPU设备：

则在func()函数内部或者调用func()的地方加上:


os.environ[&quot;CUDA_VISIBLE_DEVICES&quot;] = str(gpu_id)

我之前尝试在此处添加torch.cuda.set_device(self.gpu_id)，没作用，记录下。...]]></description><category></category></item><item><title><![CDATA[python 在一个py文件中调用另一个文件夹下py文件模块]]></title><link>https://blog.youkuaiyun.com/u010454261/article/details/85253686</link><guid>https://blog.youkuaiyun.com/u010454261/article/details/85253686</guid><author>u010454261</author><pubDate>Tue, 25 Dec 2018 20:33:26 +0800</pubDate><description><![CDATA[假设现在的文件夹结构如下：

-- src
    |-- dir1
    |    -- file1.py
    |-- dir2
    |    -- file2.py

若要在src文件夹下执行dir2文件夹下的file2.py，python ./dir2/file2.py

但file2.py中import dir1.file1

此时，未避免出现 No module named '...]]></description><category></category></item><item><title><![CDATA[conda 使用]]></title><link>https://blog.youkuaiyun.com/u010454261/article/details/83616002</link><guid>https://blog.youkuaiyun.com/u010454261/article/details/83616002</guid><author>u010454261</author><pubDate>Thu, 01 Nov 2018 12:17:23 +0800</pubDate><description><![CDATA[下载Anacondahttps://www.anaconda.com/download/#macos; 选择系统，python版本等

linux下sh anaconda.sh进行安装

创建名为pytorch的环境，

conda create -n pytorch pip python=2.7

environment location: /home/gaosiqi/anaconda2/env...]]></description><category></category></item><item><title><![CDATA[批量删除某文件夹下指定文件]]></title><link>https://blog.youkuaiyun.com/u010454261/article/details/83615923</link><guid>https://blog.youkuaiyun.com/u010454261/article/details/83615923</guid><author>u010454261</author><pubDate>Thu, 01 Nov 2018 10:10:32 +0800</pubDate><description><![CDATA[find ./ -name index.html -exec rm -f {} \;

 ]]></description><category></category></item></channel></rss>