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kin4stat's questions

Martin Hope
kin4stat
Asked: 2020-05-23 00:37:25 +0000 UTC
  • 0

当我从 IDE 运行应用程序时，它运行良好，但是当我运行 PyInstaller 构建的应用程序时，pyscreenshot.grab 的工作方式类似于 MainWindow.show()。我尝试了 3 种不同的后端（PyQt5；PIL；默认），但它们都不起作用。不明白的可以看视频

如果我关闭主窗口，则会出现错误：

Exception in thread Thread-1:
Traceback (most recent call last):
  File "threading.py", line 926, in _bootstrap_inner
  File "threading.py", line 870, in run
  File "main1.py", line 96, in main
  File "lib\site-packages\pyscreenshot\__init__.py", line 31, in grab
  File "lib\site-packages\pyscreenshot\loader.py", line 145, in backend_grab
  File "lib\site-packages\pyscreenshot\loader.py", line 136, in force
  File "lib\site-packages\pyscreenshot\childproc.py", line 39, in childprocess_grab
FileNotFoundError: [Errno 2] No such file or directory: 'C:\\Users\\User\\AppData\\Local\\Temp\\pyscreenshotmrgm1pkk\\screenshot.png'

PS 我使用的是开发版的 PyInstaller，因为 我需要 TensorFlow 支持

python
Martin Hope
kin4stat
Asked: 2020-05-21 19:24:01 +0000 UTC
  • 1

如何在您的目录中打开 Python 文件？当我使用

os.openfile("Additional.exe")

或者

subprocess.Popen("Additional.exe")

该文件已启动，当您尝试从 Additional.exe 所在的目录打开该文件时，会出现错误FileNotExists，因为。它在 main.exe 所在的目录中查找

看不懂文字的可以试试看图，我这里描述的比较简单 问题描述

PS 我使用了 PyInstaller

python
Martin Hope
kin4stat
Asked: 2020-05-20 03:20:08 +0000 UTC
  • 0

缺少数据错误。大约 4-5 天前，同一代码上不存在此错误。模型创建代码：

model = Sequential()
model.add(Conv2D(32, (3, 3), input_shape=(27, 48, 1)))
model.add(Activation("relu"))
model.add(MaxPooling2D(pool_size=(2, 2)))

model.add(Conv2D(32, (3, 3)))
model.add(Activation("relu"))
model.add(MaxPooling2D(pool_size=(2, 2)))

model.add(Conv2D(64, (3, 3)))
model.add(Activation("relu"))
model.add(MaxPooling2D(pool_size=(2, 2)))

model.add(Flatten())
model.add(Dense(64))
model.add(Activation("relu"))
model.add(Dropout(0.5))
model.add(Dense(10))
model.add(Activation('sigmoid'))
model.compile(loss="categorical_crossentropy", optimizer="adam",
              metrics=["accuracy"])

学习代码

datagen = ImageDataGenerator()
dirTrain = "/content/GeneratedI/train"
train_data = datagen.flow_from_directory(dirTrain, target_size=(27, 48), batch_size=100,
                                         class_mode="categorical", color_mode="grayscale")
dirVal = "/content/GeneratedI/val"
validation_data = datagen.flow_from_directory(dirVal, target_size=(27, 48), batch_size=100,
                                              class_mode="categorical", color_mode="grayscale")
print("Training the network...")
t_start = time.time()
history = model.fit_generator(train_data,
                              steps_per_epoch=60000 // 10,
                              epochs=1,
                              validation_data=validation_data,
                              validation_steps=10000 // 10)
print(time.time() - t_start)

肯定有图像，60k 用于训练，10k 用于验证。甚至输出也证实了这一点：

Found 60000 images belonging to 10 classes.
Found 10000 images belonging to 10 classes.

我使用谷歌协作

python
Martin Hope
kin4stat
Asked: 2020-05-11 21:59:36 +0000 UTC
  • 2

我正在尝试在我的数据集上训练神经网络。图片示例（所有图像都是位图）。

模型创建代码：

model = Sequential()
model.add(Dense(1296, activation='relu', input_shape=(27, 48)))
model.add(Dense(10, activation='softmax'))
model.compile(loss='categorical_crossentropy', optimizer=RMSprop(), metrics=['accuracy'])

学习和创建生成器的代码：

datagen = ImageDataGenerator()
dirTrain = "D:\\GeneratedI\\train"
train_data = datagen.flow_from_directory(dirTrain, target_size=(27, 48), batch_size=20,
                                         class_mode="categorical", color_mode="grayscale")

dirVal = "D:\\GeneratedI\\val"
validation_data = datagen.flow_from_directory(dirVal, target_size=(27, 48), batch_size=20,
                                              class_mode="categorical", color_mode="grayscale")

print("Training the network...")
t_start = time.time()
history = model.fit_generator(train_data,
                              steps_per_epoch=60000 / 20,
                              epochs=10,
                              validation_data=validation_data,
                              validation_steps=6000 / 20)
print(time.time() - t_start)

PS 由于我的处理器上没有 AVX，我使用 tensorflow 1.5 和 keras 2.1.6。

python