From da450c462335d512538eba145e23acdf1fb9c2bd Mon Sep 17 00:00:00 2001
From: test <test@>
Date: Mon, 31 Jul 2023 19:13:51 +0800
Subject: [PATCH] =?UTF-8?q?=E5=8F=98=E6=9B=B4?=
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 create mode 100644 dataset/val/ants/ants-devouring-remains-of-large-dead-insect-on-red-tile-in-Stellenbosch-South-Africa-closeup-1-DHD.jpg
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 create mode 100644 dataset_transform.py
 create mode 100644 images/7759525_1363d24e88.jpg
 create mode 100644 logs/events.out.tfevents.1690790854.DESKTOP-NPRDBA4.11540.0
 create mode 100644 logs_maxpool/events.out.tfevents.1690793100.DESKTOP-NPRDBA4.20196.0
 create mode 100644 logs_relu/events.out.tfevents.1690795272.DESKTOP-NPRDBA4.12024.0
 create mode 100644 read_data.py
 create mode 100644 src/nn_conv.py
 create mode 100644 src/nn_conv2d.py
 create mode 100644 src/nn_liner.py
 create mode 100644 src/nn_maxpool.py
 create mode 100644 src/nn_module.py
 create mode 100644 src/nn_relu.py
 create mode 100644 test/call_test.py
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diff --git a/.idea/.gitignore b/.idea/.gitignore
new file mode 100644
index 0000000..e69de29
diff --git a/.idea/.name b/.idea/.name
new file mode 100644
index 0000000..e69de29
diff --git a/.idea/inspectionProfiles/Project_Default.xml b/.idea/inspectionProfiles/Project_Default.xml
new file mode 100644
index 0000000..03d9549
--- /dev/null
+++ b/.idea/inspectionProfiles/Project_Default.xml
@@ -0,0 +1,6 @@
+<component name="InspectionProjectProfileManager">
+  <profile version="1.0">
+    <option name="myName" value="Project Default" />
+    <inspection_tool class="Eslint" enabled="true" level="WARNING" enabled_by_default="true" />
+  </profile>
+</component>
\ No newline at end of file
diff --git a/.idea/inspectionProfiles/profiles_settings.xml b/.idea/inspectionProfiles/profiles_settings.xml
new file mode 100644
index 0000000..e69de29
diff --git a/.idea/learn_torch.iml b/.idea/learn_torch.iml
new file mode 100644
index 0000000..9bd3226
--- /dev/null
+++ b/.idea/learn_torch.iml
@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$" />
+    <orderEntry type="jdk" jdkName="paddleocr" jdkType="Python SDK" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>
\ No newline at end of file
diff --git a/.idea/misc.xml b/.idea/misc.xml
new file mode 100644
index 0000000..6268301
--- /dev/null
+++ b/.idea/misc.xml
@@ -0,0 +1,4 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectRootManager" version="2" project-jdk-name="paddleocr" project-jdk-type="Python SDK" />
+</project>
\ No newline at end of file
diff --git a/.idea/modules.xml b/.idea/modules.xml
new file mode 100644
index 0000000..e69de29
diff --git a/.idea/vcs.xml b/.idea/vcs.xml
new file mode 100644
index 0000000..9034421
--- /dev/null
+++ b/.idea/vcs.xml
@@ -0,0 +1,7 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$" vcs="Git" />
+    <mapping directory="$PROJECT_DIR$/torch_test" vcs="Git" />
+  </component>
+</project>
\ No newline at end of file
diff --git a/.idea/workspace.xml b/.idea/workspace.xml
new file mode 100644
index 0000000..d0d55ae
--- /dev/null
+++ b/.idea/workspace.xml
@@ -0,0 +1,228 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="AutoImportSettings">
+    <option name="autoReloadType" value="SELECTIVE" />
+  </component>
+  <component name="ChangeListManager">
+    <list default="true" id="9b08595a-de5f-423b-829d-72901fefefcb" name="变更" comment="" />
+    <option name="SHOW_DIALOG" value="false" />
+    <option name="HIGHLIGHT_CONFLICTS" value="true" />
+    <option name="HIGHLIGHT_NON_ACTIVE_CHANGELIST" value="false" />
+    <option name="LAST_RESOLUTION" value="IGNORE" />
+  </component>
+  <component name="FileTemplateManagerImpl">
+    <option name="RECENT_TEMPLATES">
+      <list>
+        <option value="Python Script" />
+      </list>
+    </option>
+  </component>
+  <component name="FlaskConsoleOptions" custom-start-script="import sys&#10;sys.path.extend([WORKING_DIR_AND_PYTHON_PATHS])&#10;from flask.cli import ScriptInfo&#10;locals().update(ScriptInfo(create_app=None).load_app().make_shell_context())&#10;print(&quot;Python %s on %s\nApp: %s [%s]\nInstance: %s&quot; % (sys.version, sys.platform, app.import_name, app.env, app.instance_path))">
+    <envs>
+      <env key="FLASK_APP" value="app" />
+    </envs>
+    <option name="myCustomStartScript" value="import sys&#10;sys.path.extend([WORKING_DIR_AND_PYTHON_PATHS])&#10;from flask.cli import ScriptInfo&#10;locals().update(ScriptInfo(create_app=None).load_app().make_shell_context())&#10;print(&quot;Python %s on %s\nApp: %s [%s]\nInstance: %s&quot; % (sys.version, sys.platform, app.import_name, app.env, app.instance_path))" />
+    <option name="myEnvs">
+      <map>
+        <entry key="FLASK_APP" value="app" />
+      </map>
+    </option>
+  </component>
+  <component name="Git.Settings">
+    <option name="UPDATE_TYPE" value="REBASE" />
+  </component>
+  <component name="MarkdownSettingsMigration">
+    <option name="stateVersion" value="1" />
+  </component>
+  <component name="ProjectColorInfo">{
+  &quot;customColor&quot;: &quot;&quot;,
+  &quot;associatedIndex&quot;: -1
+}</component>
+  <component name="ProjectId" id="2TA5xGAWaNWm4rZlvJvesyExVNe" />
+  <component name="ProjectLevelVcsManager" settingsEditedManually="true">
+    <ConfirmationsSetting value="2" id="Add" />
+  </component>
+  <component name="ProjectViewState">
+    <option name="hideEmptyMiddlePackages" value="true" />
+    <option name="showLibraryContents" value="true" />
+  </component>
+  <component name="PropertiesComponent"><![CDATA[{
+  "keyToString": {
+    "ASKED_ADD_EXTERNAL_FILES": "true",
+    "RunOnceActivity.OpenProjectViewOnStart": "true",
+    "RunOnceActivity.ShowReadmeOnStart": "true",
+    "WebServerToolWindowFactoryState": "false",
+    "last_opened_file_path": "C:/Users/Ruilisi/Desktop/Projects/Picture",
+    "node.js.detected.package.eslint": "true",
+    "node.js.detected.package.stylelint": "true",
+    "node.js.detected.package.tslint": "true",
+    "node.js.selected.package.eslint": "(autodetect)",
+    "node.js.selected.package.stylelint": "",
+    "node.js.selected.package.tslint": "(autodetect)",
+    "settings.editor.selected.configurable": "preferences.pluginManager",
+    "vue.rearranger.settings.migration": "true"
+  }
+}]]></component>
+  <component name="RecentsManager">
+    <key name="CopyFile.RECENT_KEYS">
+      <recent name="C:\Users\12642\Desktop\Picture\images" />
+    </key>
+  </component>
+  <component name="RunManager" selected="Python.nn_liner">
+    <configuration name="nn_conv2d" type="PythonConfigurationType" factoryName="Python" temporary="true" nameIsGenerated="true">
+      <module name="learn_torch" />
+      <option name="INTERPRETER_OPTIONS" value="" />
+      <option name="PARENT_ENVS" value="true" />
+      <envs>
+        <env name="PYTHONUNBUFFERED" value="1" />
+      </envs>
+      <option name="SDK_HOME" value="" />
+      <option name="WORKING_DIRECTORY" value="$PROJECT_DIR$/src" />
+      <option name="IS_MODULE_SDK" value="true" />
+      <option name="ADD_CONTENT_ROOTS" value="true" />
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diff --git a/dataloader.py b/dataloader.py
new file mode 100644
index 0000000..c1b314e
--- /dev/null
+++ b/dataloader.py
@@ -0,0 +1,26 @@
+import torchvision
+from torch.utils.data import DataLoader
+from torch.utils.tensorboard import SummaryWriter
+
+# 准备的测试数据集
+test_data = torchvision.datasets.CIFAR10("./dataset", train=False, transform=torchvision.transforms.ToTensor())
+
+test_loader = DataLoader(dataset=test_data, batch_size=64, shuffle=True, num_workers=0, drop_last=True)
+
+# 测试数据集中第一张图片以及target
+img, target = test_data[0]
+print(test_data.classes)
+print(img.shape)
+print(target)
+
+writer = SummaryWriter("dataloader")
+for epoch in range(2):
+    step = 0
+    for data in test_loader:
+        imgs, targets = data
+        # print(imgs.shape)
+        # print(targets)
+        writer.add_images("Epoch: {}".format(epoch), imgs, step)
+        step = step + 1
+
+writer.close()
\ No newline at end of file
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diff --git a/dataset_transform.py b/dataset_transform.py
new file mode 100644
index 0000000..e0ef2ed
--- /dev/null
+++ b/dataset_transform.py
@@ -0,0 +1,25 @@
+import torchvision
+from torch.utils.tensorboard import SummaryWriter
+
+dataset_transform = torchvision.transforms.Compose([
+    torchvision.transforms.ToTensor(),
+
+])
+train_set = torchvision.datasets.CIFAR10(root='./dataset', train=True, transform=dataset_transform ,download=True)
+test_set = torchvision.datasets.CIFAR10(root='./dataset', train=False, transform=dataset_transform ,download=True)
+
+# print(test_set[0])
+# print(test_set.classes)
+# img, target = test_set[0]
+# print(img)
+# print(target)
+# print(test_set.classes[target])
+# img.show()
+# print(test_set[0])
+
+writer = SummaryWriter("p10")
+for i in range(10):
+    img, target = test_set[i]
+    writer.add_image("test_set", img, i)
+
+writer.close()
\ No newline at end of file
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diff --git a/logs/events.out.tfevents.1690790854.DESKTOP-NPRDBA4.11540.0 b/logs/events.out.tfevents.1690790854.DESKTOP-NPRDBA4.11540.0
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diff --git a/logs_maxpool/events.out.tfevents.1690793100.DESKTOP-NPRDBA4.20196.0 b/logs_maxpool/events.out.tfevents.1690793100.DESKTOP-NPRDBA4.20196.0
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diff --git a/logs_relu/events.out.tfevents.1690795272.DESKTOP-NPRDBA4.12024.0 b/logs_relu/events.out.tfevents.1690795272.DESKTOP-NPRDBA4.12024.0
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diff --git a/read_data.py b/read_data.py
new file mode 100644
index 0000000..f3dc554
--- /dev/null
+++ b/read_data.py
@@ -0,0 +1,33 @@
+from torch.utils.data import Dataset
+import cv2
+from PIL import Image
+import os
+
+
+class MyDataset(Dataset):
+
+    def __init__(self, root_dir, label_dir):
+        self.root_dir = root_dir
+        self.label_dir = label_dir
+        self.path = os.path.join(self.root_dir, self.label_dir)
+        self.img_path = os.listdir(self.path)
+
+    # __getitem__ 是一个魔法方法，当使用dataset[i]获取第i个样本时，就会调用该方法。
+    def __getitem__(self, idx):
+        img_name = self.img_path[idx]
+        img_item_path = os.path.join(self.root_dir, self.label_dir, img_name)
+        img = Image.open(img_item_path)
+        label = self.label_dir
+
+        return img, label
+
+    def __len__(self):
+        return len(self.img_path)
+
+
+root_dir = 'dataset/train'
+ants_label_dir = 'ants'
+bees_label_dir = 'bees'
+ants_dataset = MyDataset(root_dir, ants_label_dir)
+bees_dataset = MyDataset(root_dir, bees_label_dir)
+print(ants_dataset[0])
\ No newline at end of file
diff --git a/src/nn_conv.py b/src/nn_conv.py
new file mode 100644
index 0000000..46238f9
--- /dev/null
+++ b/src/nn_conv.py
@@ -0,0 +1,31 @@
+import torch
+import torch.nn.functional as F
+
+input = torch.tensor([[1, 2, 0, 3, 1],
+                      [0, 1, 2, 3, 2],
+                      [1, 2, 1, 0, 0],
+                      [5, 2, 3, 1, 1],
+                      [2, 1, 0, 1, 1]])
+
+kernel = torch.tensor([[1, 2, 1],
+                       [0, 1, 0],
+                       [2, 1, 0]])
+
+input = torch.reshape(input, (1, 1, 5, 5))
+kernel = torch.reshape(kernel, (1, 1, 3, 3))
+
+print(input.shape)
+print(kernel.shape)
+
+output = F.conv2d(input, kernel, stride=1)
+print(output)
+
+output2 = F.conv2d(input, kernel, stride=2)
+print(output2)
+
+# stride步进 kernel我们的卷积核 padding是填充四周
+output3 = F.conv2d(input, kernel, stride=1, padding=1)
+print(output3)
+
+
+
diff --git a/src/nn_conv2d.py b/src/nn_conv2d.py
new file mode 100644
index 0000000..f3617d5
--- /dev/null
+++ b/src/nn_conv2d.py
@@ -0,0 +1,38 @@
+import torch
+import torchvision
+import torch.nn as nn
+from torch.utils.data import DataLoader
+from torch.utils.tensorboard import SummaryWriter
+
+dataset = torchvision.datasets.CIFAR10(root='../dataset', train=False, transform=torchvision.transforms.ToTensor(),
+                                       download=True)
+dataloader = DataLoader(dataset, batch_size=64)
+
+class Tudui(nn.Module):
+    def __init__(self):
+        super(Tudui, self).__init__()
+        self.conv1 = nn.Conv2d(in_channels=3, out_channels=6, kernel_size=3, stride=1, padding=0)
+
+    def forward(self, x):
+        x = self.conv1(x)
+        return x
+
+tudui = Tudui()
+# print(tudui)
+
+writer = SummaryWriter('../logs')
+step = 0
+for data in dataloader:
+    imgs, targets = data
+    output = tudui(imgs)
+    print(imgs.shape)
+    print(output.shape)
+    # torch.Size([64, 3, 32, 32])
+    writer.add_images('input', imgs, step)
+    # torch.Size([64, 6, 30, 30]) => torch.Size([64, 3, 30, 30])
+    output = torch.reshape(output, (-1, 3, 30, 30))
+    writer.add_images('output', output, step)
+    step += 1
+
+writer.close()
+
diff --git a/src/nn_liner.py b/src/nn_liner.py
new file mode 100644
index 0000000..c6a6d62
--- /dev/null
+++ b/src/nn_liner.py
@@ -0,0 +1,30 @@
+import torch
+import torchvision
+from torch import nn
+from torch.nn import Linear
+from torch.utils.data import DataLoader
+
+datasset = torchvision.datasets.CIFAR10(root='../dataset', train=False, download=True,
+                                        transform=torchvision.transforms.ToTensor())
+dataloader = DataLoader(datasset, batch_size=64)
+
+
+class Tudui(nn.Module):
+    def __init__(self):
+        super(Tudui, self).__init__()
+        self.Linera1 = Linear(196608, 10)
+
+    def forward(self, input):
+        output = self.Linera1(input)
+        return output
+
+
+tudui = Tudui()
+
+for data in dataloader:
+    imgs, targets = data
+    output = torch.reshape(imgs, (1, 1, 1, -1))
+    output = torch.flatten(imgs)
+    print(output.shape)
+    output = tudui(output)
+    print(output.shape)
diff --git a/src/nn_maxpool.py b/src/nn_maxpool.py
new file mode 100644
index 0000000..c71f71d
--- /dev/null
+++ b/src/nn_maxpool.py
@@ -0,0 +1,50 @@
+import torch
+import torchvision
+from torch import nn
+from torch.utils.data import DataLoader
+from torch.utils.tensorboard import SummaryWriter
+
+dataset = torchvision.datasets.CIFAR10(root='../dataset', train=False,
+                                       transform=torchvision.transforms.ToTensor(),)
+
+dataloader = DataLoader(dataset, batch_size=64)
+
+# input = torch.tensor([[1, 2, 0, 3, 1],
+#                       [0, 1, 2, 3, 1],
+#                       [1, 2, 1, 0, 0],
+#                       [5, 2, 3, 1, 1],
+#                       [2, 1, 0, 1, 1]], dtype=torch.float32)
+#
+# # 转换为(C,H ,W)格式 unsqueeze是增加维度 0是在第0维增加
+# # input = input.unsqueeze(0).unsqueeze(0)
+# input = torch.reshape(input, (-1, 1, 5, 5))
+# print(input.shape)
+
+class Tudui(nn.Module):
+    def __init__(self):
+        super(Tudui, self).__init__()
+        # ceil_mode=True表示向上取整
+        # self.maxpool1 = nn.MaxPool2d(kernel_size=3, ceil_mode=True)
+        self.maxpool1 = nn.MaxPool2d(kernel_size=3, ceil_mode=False)
+
+
+    def forward(self, input):
+        output = self.maxpool1(input)
+        return output
+
+# 最大池化的感觉就是把一个区域内的最大值取出来
+# 文件尺寸会变小
+tudui = Tudui()
+step = 0
+writer = SummaryWriter("../logs_maxpool")
+for data in dataloader:
+    imgs, targets = data
+    output = tudui(imgs)
+    writer.add_images("input", imgs, step)
+    writer.add_images("output", output, step)
+    step += 1
+
+writer.close()
+
+
+
diff --git a/src/nn_module.py b/src/nn_module.py
new file mode 100644
index 0000000..304d96b
--- /dev/null
+++ b/src/nn_module.py
@@ -0,0 +1,17 @@
+import torch
+from torch import nn
+
+
+class Tudui(nn.Module):
+    def __init__(self):
+        super().__init__()
+
+    def forward(self, input):
+        output = input + 1
+        return output
+
+
+tudui = Tudui()
+x = torch.tensor(1.0)
+output = tudui(x)
+print(output)
diff --git a/src/nn_relu.py b/src/nn_relu.py
new file mode 100644
index 0000000..83aa8bf
--- /dev/null
+++ b/src/nn_relu.py
@@ -0,0 +1,40 @@
+import torch
+import torchvision
+from torch.nn import ReLU, Sigmoid
+from torch.utils.data import DataLoader
+from torch.utils.tensorboard import SummaryWriter
+
+# 检查GPU是否可用，若可用，则使用GPU，否则使用CPU
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+dataset = torchvision.datasets.CIFAR10(root='../dataset', train=False, download=True,
+                                       transform=torchvision.transforms.ToTensor())
+dataloader = DataLoader(dataset, batch_size=64)
+
+
+class Tudui(torch.nn.Module):
+    def __init__(self):
+        super(Tudui, self).__init__()
+        self.relu1 = ReLU(inplace=True)
+        self.sigmoid1 = Sigmoid()
+
+    def forward(self, input):
+        output = self.sigmoid1(input)
+        return output
+
+
+tudui = Tudui().to(device)
+
+writer = SummaryWriter('../logs_relu')
+step = 0
+for data in dataloader:
+    imgs, targets = data
+    # 将数据移动到GPU上
+    imgs = imgs.to(device)
+    targets = targets.to(device)
+
+    writer.add_images('input', imgs, step)
+    output = tudui(imgs)
+    writer.add_images('output', output, step)
+    step += 1
+writer.close()
diff --git a/test/call_test.py b/test/call_test.py
new file mode 100644
index 0000000..4bc3ed8
--- /dev/null
+++ b/test/call_test.py
@@ -0,0 +1,11 @@
+class Person:
+    def __call__(self, name):
+        print("__call__"+"hello", name)
+
+    def hello(self, name):
+        print("hello", name)
+
+
+person = Person()
+person("world")
+person.hello("world")
\ No newline at end of file
diff --git a/test_tb.py b/test_tb.py
new file mode 100644
index 0000000..068db2c
--- /dev/null
+++ b/test_tb.py
@@ -0,0 +1,18 @@
+from torch.utils.tensorboard import SummaryWriter
+import numpy as np
+from PIL import Image
+
+writer = SummaryWriter('logs')
+# image_path = r"C:\Users\12642\Desktop\Picture\dataset\train\ants\0013035.jpg"
+image_path = r"C:\Users\12642\Desktop\Picture\dataset\train\ants\6240338_93729615ec.jpg"
+img_PIL = Image.open(image_path)
+img_array = np.array(img_PIL)
+print(type(img_array))
+print(img_array.shape)
+
+
+writer.add_image("train", img_array, 1, dataformats='HWC')
+for i in range(100):
+    writer.add_scalar("y=2x", 2*i, i)
+
+writer.close()
diff --git a/transforms_test.py b/transforms_test.py
new file mode 100644
index 0000000..d4d9713
--- /dev/null
+++ b/transforms_test.py
@@ -0,0 +1,15 @@
+from PIL import Image
+from torch.utils.tensorboard import SummaryWriter
+from torchvision import transforms
+
+img_path = r"C:\Users\12642\Desktop\Picture\dataset\train\ants\6240338_93729615ec.jpg"
+img = Image.open(img_path)
+
+writer = SummaryWriter("logs")
+
+# transforms.ToTensor() 将 PIL.Image 或者 numpy.ndarray 转化为 tensor
+tensor_trans = transforms.ToTensor()
+tensor_img = transforms.ToTensor()(img)
+
+writer.add_image("tensor_img", tensor_img) # 这里的tensor_img是一个三维的tensor，所以可以直接显示
+writer.close()
\ No newline at end of file
diff --git a/userful_transforms.py b/userful_transforms.py
new file mode 100644
index 0000000..0cab2b7
--- /dev/null
+++ b/userful_transforms.py
@@ -0,0 +1,44 @@
+from PIL import Image
+from torch.utils.tensorboard import SummaryWriter
+from torchvision import transforms
+
+writer = SummaryWriter("logs")
+img = Image.open(r"images/7759525_1363d24e88.jpg")
+
+# TeTensor的使用
+trans_totensor = transforms.ToTensor()
+img_tensor = trans_totensor(img)
+writer.add_image("ToTensor", img_tensor)
+
+# Normalize的使用
+print(img_tensor[0][0][0])
+trans_norm = transforms.Normalize([1, 3, 5], [3, 2, 1])
+img_norm = trans_norm(img_tensor)
+print(img_norm[0][0][0])
+writer.add_image("Normalize", img_norm,2)
+
+# Resize的使用
+print(img.size)
+trans_resize = transforms.Resize((512, 512))
+# img PIL -> resize -> img_resize PIL
+img_resize = trans_resize(img) # 返回的是PIL
+# img_resize PIL -> ToTensor -> img_resize Tensor
+img_resize = trans_totensor(img_resize) # PIL转换为Tensor
+writer.add_image("Resize", img_resize, 0)
+
+# Compose的使用 compose = ToTensor + Normalize
+trans_resize_2 = transforms.Resize(512)
+# transforms.Compose([trans_resize_2, trans_totensor])是一个类，可以直接调用
+# 用于将多个transforms组合起来使用 达到 ToTensor + Normalize 的效果
+trans_compose = transforms.Compose([trans_resize_2, trans_totensor])
+img_resize_2 = trans_compose(img)
+writer.add_image("Raszie", img_resize_2, 1)
+
+# RandomCrop的使用
+trans_random = transforms.RandomCrop(256, 128)
+trans_compose2 = transforms.Compose([trans_random, trans_totensor])
+for i in range(10):
+    img_crop = trans_compose2(img)
+    writer.add_image("RandomCrop", img_crop, i)
+
+writer.close()
\ No newline at end of file