original image
expands the image outwards according to the pixel value of the image boundary, expanding 50 pixels in each direction.
a = cv2. CopyMakeBorder (img, 50,50,50,50, cv2. BORDER_REPLICATE)
near the boundary of the 50 pixels fold out (axisymmetric) :
a = cv2. CopyMakeBorder (img, 50,50,50,50, cv2 BORDER_REFLECT)
constant fill:
a = cv2.copymakeborder (img,50,50,50, cv2.border_constant,value=[0,255,0])
Directly on the command line, enter
PIP install torch = 1.2.0 torchvision = 0.4.0 -f https://download.pytorch.org/whl/torch_stable.html
successfully solved
“AttributeError: ‘DataFrame’ object has no attribute ‘ix'”
recently reported when using the ix method of DataFrame after searching on the Internet, is removed from the series.ix and dataframe.ix method at the beginning of pandas’ 1.0.0 version.
my solution: use the loc method of DataFrame or the iloc method instead.
check pandas
for details
reference: https://hacpai.com/article/1581255121678
docker official website address https://www.docker.com/
docker start command,docker restart command,docker close command
start systemctl start docker
daemon restart sudo systemctl daemon-reload
Docker docker
docker
sudo service docker restart
Docker stop service docker stop
Docker
P> question:
did you register the component?For recursive components, make sure to provid the "name" option
For recursive components, make sure to provid the “name” option
import ComponentA from './ComponentA.vue'
import ComponentB from './ComponentB.vue'
export default {
component: {
ComponentA,ComponentB
},
// ...
}
solution:
to correct component
import ComponentA from './ComponentA.vue'
import ComponentB from './ComponentB.vue'
export default {
components: {
ComponentA,ComponentB
},
// ...
}
from the perspective of language, java.util.List is an interface, under which there are multiple N implementations, the most commonly used are ArrayList and LinkedList and its various inheritance or synchronization implementation (such as Vector/Queue/Stack)
ArrayList inside is to take the array storage, then the upper limit is Integer.MAX_VALUE
LinkedList inside is a LinkedList, theoretically infinite
also, everything in the List is in memory (although you can implement one yourself), so how much you can put depends on the size and type of stuff you’re putting. The
size aspect is easy to calculate, if one object is 1K, then 400,000 will take up at least 400M memory (not counting other usage).
virtual machine memory classification, if it is a common object, generally use the Heap space, if it is a constant or something like string.intern (), then use the Permanent Generation.
in actual development, the default memory size of virtual machine varies according to different virtual machine implementations. The maximum heap size can be adjusted with -xmx when the application is launched, such as adjusting the maximum heap size to 2G:
java -Xmx2048m cn.gefostudio.App
adjust the maximum size of the immortal band to 1G:
java -XX:MaxPermSize=1024m cn.gefostudio.App
mouse hover display text, HTML use title attribute can achieve the effect of text display, this attribute is more practical, the need for friends can refer to
< A href=# title=” here is the text displayed “> hello< /a>
when we hover over hello last time we will have text and here is the text that is displayed.
extract: https://ansible-book.gitbooks.io/ansible-first-book/content/yong_ming_ling_xing_chuan_di_can_shu.html
= ansible-books.io/ansible-first-book/content/yong_ming_ling_xing_chuan_di_can_shu.html
from the command line
in the release.yml file, hosts and user are defined as variables that need to be passed from the command line.
hosts: ‘{{host}}
remote_user:’ {{user}}
the tasks:
ansible-playbook e33_var_in_command.yml --extra-vars "hosts=web user=root" The
parameter can also be passed in json format:
ansible-playbook e33_var_in_command.yml --extra-vars "{'hosts':'vm-rhel7-1', 'user':'root'}" can also put parameters in the file:
ansible-playbook e33_var_in_command.yml --extra-vars "@vars.json"Linux driver module_platform_driver macro learning
It is common to see this macro module_platform_driver on Linux devices. The following figure shows a character device driver. Today we’re going to learn about this macro.
2, the macro is in kernel/include/Linux/platform_device. H defined inside. We find that this calls another macro, module_driver.
. So where is the module_driver macro defined?For once, the macro is in kernel/include/Linux/device. The definition of h.
The macro module_platform_driver can be used to write much less code. The purpose of the macro is to define the platform driver registration function and the platform driver unregistration function with the specified name, and to register and unregister the platform driver within the function body with the functions platform_driver_register() and Platform_driver_unregister (), respectively.
static int x_init(void)
{
return platform_driver_register(& xxx);
}
module_init(xxx_init);
static void __exit xxx_init(void)
{
return platform_driver_unregister(& xxx);
}
module_exit(xxx_exit);
The most common
time.time() returns a floating point number in seconds. But the type that strfTime handles is time.struct_time, which is actually a tuple. Both strpTime and localTime will return this type.
>>> import time
>>> t = time.time()
>>> t
1202872416.4920001
>>> type(t)
<type 'float'>
>>> t = time.localtime()
>>> t
(2008, 2, 13, 10, 56, 44, 2, 44, 0)
>>> type(t)
<type 'time.struct_time'>
>>> time.strftime('%Y-%m-%d', t)
'2008-02-13'
>>> time.strptime('2008-02-14', '%Y-%m-%d')
(2008, 2, 14, 0, 0, 0, 3, 45, -1)strftime can be used to get the current time, you can format the time as a string, and so on, which is pretty handy. However, it should be noted that the acquired time is the time of the server, and pay attention to the time zone issues, such as GAE lying that the time is the 0 time zone of GMT, which needs to be converted by itself.
Strftime ()
strftime ()
we can use the strftime () function to format the time in the desired format
#!/usr/bin/python
import time
t = (2009, 2, 17, 17, 3, 38, 1, 48, 0)
t = time.mktime(t)
print time.strftime("%b %d %Y %H:%M:%S", time.gmtime(t))
#输出：Feb 17 2009 09:03:38Python time strptime() function parses a time string into a time tuple according to the specified format.
python time date formatting symbol:
0
3% m minutes (00=59)
4
0
0
2
4
5
instance:
#!/usr/bin/python
import time
struct_time = time.strptime("30 Nov 00", "%d %b %y")
print "returned tuple: %s " % struct_time
#输出：returned tuple: (2000, 11, 30, 0, 0, 0, 3, 335, -1)project more and more, using eclipse felt too card, decided to try the idea.
under multiple modules, system.getproperty (“user.dir”) gets the path to the module when you run the project.
to set the default Working Directory
setting method:
Run -> Edit Configurations -> Working directory
Defaults-> Application
set Working directory to $MODULE_DIR$so that each module gets its own project root path
CentOS 7.0 defaults to firewall as a firewall
view firewall status
firewall-cmd --stateStop is firewall
systemctl stop firewalld.servicefirewall is prohibited to turn on
systemctl disable firewalld.service turn off from CentOS 6 and CentOS 7 firewall
close selinux
into /etc/selinux/config file
vi /etc/selinux/configthe SELINUX = instead of enforcing the SELINUX = disabled
confers the non-secret login command
ssh-keygen -t rsa
ssh-copy-id root@masterscp -P 22 /Users/che/Downloads/jdk-8u161-linux-x64.rpm [email protected]:/software/
安装: yum install -y jdk-8u161-linux-x64.rpm
设置环境变量
cd /usr/java/
/usr/java/jdk1.8.0_161
vi /etc/profile
export JAVA_HOME=/usr/java/jdk1.8.0_161
export PATH=$JAVA_HOME/bin:$PATH
install hadoop
download installation package
hadoop-26.5.tar.gz
cd /usr/
mv /software/hadoop-2.6.5.tar.gz ./
解压
tar -xzvf ./hadoop-2.6.5.tar.gz
创建目录
namenode目录：/data/hadoop/namenode
data目录： /data/hadoop/data
tmp目录： /data/hadoop/tmp
mkdir -p /data/hadoop/namenode
配制
core-site.xml
hdfs-site.xml
mapred-site.xml.template mapred-site.xml
cp mapred-site.xml.template mapred-site.xml
yarn-site.xml
slaves (slave1,slave2)
masters (master)
hadoop-env.sh
export JAVA_HOME=/usr/java/jdk1.8.0_161
将master的配制copy到slave1、slave2
scp -r ./* root@slave1:/software/hadoop-2.6.5/etc/hadoop/
格式化
cd hadoop-2.6.5/bin
./hdfs namenode -format
启动
cd ../sbin/
./start-dfs.sh
ssh-copy-id root@master
jps(检查一下)
./start-yarn.sh
cd ../bin
hadoop fs -ls /
hadoop fs -mkdir /user
/software/hadoop-2.6.5/bin
vi/etc/profile
export HADOOP_HOME=/software/hadoop-2.6.5
export PATH=$JAVA_HOME/bin:$HADOOP_HOME/bin:$PATH
source /etc/profile
hadoop fs -put /software/hadoop-2.6.5.tar.gz /user
测试2：
cd share/hadoop/mapreduce
hadoop jar ./hadoop-mapreduce-examples-2.6.5.jar pi 5 10
192.168.1.100:50070
192.168.1.100:8088
修改ssh端口
vim /etc/ssh/sshd_config
set NTP time synchronization service
, install NTP
yum install -y NTP
2, set NTP service startup
chkconfig NTPD on
service NPTD start