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图片加载出错，删除文件

https://www.lfd.uci.edu/~gohlke/pythonlibs/numpy:https://www.lfd.uci.edu/~gohlke/pythonlibs/#numpypytorch:https://www.lfd.uci.edu/~gohlke/pythonlibs/#pytorch

import torcha = torch.randint(0,3,(2,3,4))print(a.size())print(a)b = torch.sum(a, 0) # 按将第一个纬度的值相加c = torch.sum(a, 1) # 按将第二个纬度的值相加print('b', b)print('c', c)

import torch.nn as nnfrom torchvision import transformsfrom PIL import Imageimport torchimg = Image.open('../data/pikachu.jpg')transform_to_tensor = transforms.ToTensor()img_ = transform_to_tensor(img)print(1, img_.size())img_ = torch.unsquee.

from PIL import Imageimg = Image.open('./testpic.jpg')w, h = img.sizeprint(w, h)w_s = int(w/2) # 长宽缩小两倍h_s = int(h/2) # 长宽缩小两倍img = img.resize((w_s, h_s),Image.ANTIALIAS)blank = (w_s - h_s)/2# img.crop((w0, h0, w1, h1)) w0，h0宽度，高度起始方向剪裁的值，为负时是.

torch.split(tensor,split_size_or_sections,dim=0)split_size_or_sections 为切分后的每块大小，不是切分为多少块import torchx = torch.randn(1, 2, 4, 4)y = torch.split(x, 1, dim=1) # 每块大小为1# print(x[0])for i in y: print(i.size())a = torch.rand(1, 4, 8, 6)b =..

import cv2import numpy as np# 腐蚀kerneldilate_kernel = np.ones((3,3))# 膨胀kernelerose_kenel = np.array([[255,255,255],[255,255,255],[255,255,255]])test_img = cv2.imread('../data/testpic.jpg')print(test_img.shape)# 膨胀或腐蚀的迭代次数test_img1 = cv2.dila.

# 卷积计算公式 D_in：输入特征图尺寸， p：padding大小，k：kernel_size卷积核大小，# s:stride 步距，D_out ：输出特征图尺寸D_out = (D_in + 2p - k) / s + 1# 反过来则得到感受野计算公式D_in = (D_out - 1) * s + k - 2p"""例 5*5 的特征图经过 3*3 的卷积核，s为1，进行卷积运算得到 3*3的特征图，那么3*3的特征图在3*3的卷积核，s为1情况下，感受野为 5*5""".

from PIL import Imageimport matplotlib.pyplot as pltimport torchimport torchvision.transforms as transformsori_img = Image.open('./dog1.jpg')# plt.imshow(ori_img)# plt.show()print(ori_img.size)my_transforms = transforms.Compose([ transforms.R.

import torch.nn as nnimport torch# 创建三维tensora = torch.randn(3,4,5)print(a.shape)print(a)# 升维，升成四维a = torch.unsqueeze(a, 0)print(a.shape)print(a)# AdaptiveAvgPool2d(X) 是将W H 使用平均池化降为X维avg = nn.AdaptiveAvgPool2d(1)b = avg(a)print(a.shape)pr.

转自：https://blog.youkuaiyun.com/grllery/article/details/102470263transform = transforms.Compose([ transforms.Grayscale(num_output_channels=1), transforms.ToTensor()])img = transform(img) print(img.size()) # img(1, 681, 1023)img = np.transpose(img,

from torchvision import transformstransform = transforms.Compose([ transforms.Grayscale(num_output_channels=1), # 彩色图像转灰度图像num_output_channels默认1 transforms.ToTensor()])

转自：https://www.jianshu.com/p/3ca870451d74torch.nn.ConvTranspose2d类输出尺寸计算方法torch.nn.ConvTranspose2d(in_channels, out_channels, kernel_size, stride=1, padding=0, output_padding=0, groups=1, bias=True, dilation=1, padding_mode='zeros')inchannels = 64out

import numpy as npdef softmax(v : [int]): l1 = list(map(lambda x: np.exp(x), v)) return list(map(lambda x: x / sum(l1), l1))

import torchimport numpy as npnp_a = np.array([[1,2,3],[4,5,6],[7,8,9]])tensor_a = torch.from_numpy(np_a.astype('float32'))print(tensor_a)# ()括号中的1/0 表示获取 行/列 的最值# []中的0,1 表示 获取的是最值 还是 最值的索引print(torch.max(tensor_a,1)[0])print(torch.max(tensor_.

import reline = '''{name:'兰州',name:'张掖', geoCoord:[103.73, 36.03]},'''city = re.findall("name:'(\w+)'",line)code = re.findall("\[\d+.\d+,\s\d+.\d+\]", line)# code = re.findall("Coord:\[(\d+.\d+)...

def search_graph(network, start): need_check = [start] expansion = [] while need_check: person = need_check.pop(-1) # -1 为深度优先 0 为广度优先 if person in expansion: continue ...

import networkx as nximport matplotlib.pyplot as pltfrom pylab import mplsocial_network = {'小张': ['老王', '小刘', '小西'], '小西': ['张三','李四','陈八'], '陈八':['小七', '王五']}mpl.rcParams['font.sans-serif'] = [...

from collections import Countertext = 'hello world hello world hello hello world hello world'print(Counter(text.split())一些Counter常用的方法 | Counter() | | Note: If a count is set to zer...

package com.heiheihaxi.demo.pojo;/** * @Author: heiheihaxi * @Date: 2020/2/12 15:20 */public class SingleDog { private static SingleDog singleDog = null; private SingleDog(){} pub...

转自：https://blog.youkuaiyun.com/z_k_h/article/details/80340451procyon-decompiler jar包地址：https://bitbucket.org/mstrobel/procyon/downloads/?tab=downloads// 反编译jar包java -jar procyon-decompiler-0.5.36....

转自：https://blog.youkuaiyun.com/weixin_35757704/article/details/76147518需要隐藏的文件一定要为压缩文件，展示图片为jpgcopy /b 展示图片.jpg + 隐藏文件.rar 展示文件名.jpg...

转自：https://blog.youkuaiyun.com/ithouse/article/details/78257418import java.util.Random;import java.util.concurrent.Callable;import java.util.concurrent.ExecutionException;import java.util.concurrent.E...

背景，需求，需要将oracle数据均分成m块，并拿其中的第n（n <= m）块使用ntile函数SELECT A.* FROM (SELECT T.*, NTILE(9) OVER (ORDER BY T.ROWID ASC) NTI FROM T_XXXX T) A WHERE A.NTI = 3此sql为把表数据分为9块，取其中的第3块，...

网上找的资料，地址具体忘了，此处作为保存，方便以后使用springboot项目，在properties配置文件中添加属性#aaaspring.datasource.aaa.jdbcUrl=jdbc:oracle:thin:@172.xx.xx.xx:1521/XXXXspring.datasource.aaa.driver-class-name=oracle.jdbc.driver....

SELECT h1.comments tabdesc, h2.column_name columnname, h2.data_type type, h2.comments desci, h2.data_length lenth, h2.DATA_PRECISION PRECISIO...

alter user xxxx identified by yyyxxx:用户名 yyy:密码

转自：https://www.cnblogs.com/liuwei6/p/6708116.html自己写的一个简单的wordcount mapreduce实例三个类自定义的mapper类继承org.apache.hadoop.mapreduce.Mapper类，并需要填写四个泛型类，分别代表key-in的数据类型，value-in的数据类型，key-out的数据类型，value...

集合中为一个类，根据类中某两种属性确定是否为同一对象，bean：Cat重写了 equals 方法和 hashCode 方法，更改确定为唯一对象的两种属性（此时为 name 和 age ），只重写 equals 方法或 hashCode 方法都不行，package com.zjxt.demo.pojo.bean;import java.util.Objects;/** * @...

转自：https://blog.youkuaiyun.com/xxssyyyyssxx/article/details/77967836package com.heiheihaxi.jszxdemo2.test;import com.alibaba.fastjson.JSONArray;import com.alibaba.fastjson.JSONObject;import com.aliba...

INSERT INTO T_DATA_RES_TABLE SELECT* FROM (SELECT * FROM T_DATA_RES_TABLE AS OF timestamp SYSDATE - 4 / 1440 MINUSSELECT * FROM T_DATA_RES_TABLE)更换表名 和 时间就行 ，现在是回复前4分钟...

网上找了很多都没有找到类似的，于是自己想办法，只能大概满足要求吧，并不能确切的定位到哪一条数据，具体的思路是：通过scan，设置timeRange，需要起始时间和结束时间，结束时间可以定为当前时间，起始时间可以定为当前时间前一天（时间粒度可以更改为小时，分钟，或者秒，粒度越细，结果越准确），然后去scan，判断是否扫描到数据，如果没有，则把起始时间再往前一天，直到扫描到数据为止。此方法只能大概...

cmd命令下进入jdk所在文件夹下的bin文件夹下输入jps命令找到正在执行的类Test的pid 23720，执行jstack命令E:\develop\Java\JDK1.8\jdk1.8.0_171\bin>jps2189224484 Jps23720 Test24872 Launcher4520 LauncherE:\develop\Java\JDK1....

pom文件： &lt;dependency&gt; &lt;groupId&gt;ch.ethz.ganymed&lt;/groupId&gt; &lt;artifactId&gt;ganymed-ssh2&lt;/artifactId&gt; &lt;version&gt;261&lt;/version&gt;

public class Test6 { public static void main(String[] args) { String str="asdadads01"; // Pattern.matches("正则表达式", "要匹配的字符串"); boolean b = Pattern.matches(".*01$", str);/...

转自：https://blog.youkuaiyun.com/qq_41027942/article/details/83149959转自：https://blog.youkuaiyun.com/wangyuanjun008/article/details/79121687服务发布：pom：&lt;dependencies&gt; &lt;dependency&gt; ...

private static void getAllFiles(File file){ if (file.exists()){ if (file.isFile()){ System.out.println("filename:"+file.getName()); }else { ...

转自：https://blog.youkuaiyun.com/zhangerqing/article/details/8194653在1package com.zjxt.demo.pojo;public class SingletonSync3 { private static SingletonSync3 instance=null; private SingletonSyn...

转自：https://blog.youkuaiyun.com/qq_34371461/article/details/80571281评论部分def generate(table, dir) {// def className = javaClassName(table.getName(), true) + "DO" def className = javaName(table.get...

//将返回的数据按key进行排序 Map&lt;String, Map&lt;String, String&gt;&gt; result = new HashMap&lt;&gt;(); // 一系列添加数据操作 // 设置排序为倒序排序，不加Comparator默认是增序排序 TreeMap&lt;String, Obje...