我完成模型训练处理。在训练期间,我使用ModelCheckpint通过以下方法节省了最佳模型的权重:
checkpoint = ModelCheckpoint(filepath, monitor='val_acc', verbose=1,
save_best_only=True, mode='max')
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训练后,我将模型权重加载到模型中进行评估,但是我发现模型不能提供训练中观察到的最佳准确性。我按如下方式重新加载模型:
model.load_weights(filepath) #load saved weights
model = Sequential()
model.add(Convolution2D(32, 7, 7, input_shape=(3, 128, 128)))
....
....
model.compile(loss='categorical_crossentropy',
optimizer=sgd,
metrics=['accuracy'])
#evaluate the model
scores = model.evaluate_generator(test_generator,val_samples)
print("Accuracy = ", scores[1])
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Modelcheckpoint所保存的最高准确度约为85%,但是重新编译的模型仅提供16%的准确度?
我在做错什么吗?
为了安全起见,有什么方法可以直接保存最佳模型而不是模型权重?
我已经在 my 中声明了三个插槽,mainwindow.h并在实现文件中给出了它们的定义。这是 MainWindow 类:
class MainWindow : public QMainWindow
{
Q_OBJECT
public:
explicit MainWindow(QWidget *parent = 0);
~MainWindow();
signals:
void nextImage(int direction);
private slots:
void updateImage(void);
void cameraControl(void);
void cameraStart(void);
private:
Ui::MainWindow *ui;
CMUCamera *camera;
ImageProcessing *process;
RenderImage *renderImage;
bool saveImgFlg;
QString path;
};
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转到 mainwindow.ui,我为用户界面设计了一个菜单栏。QAction一共有三个,如下图所示:

然后,我进行信号和插槽编辑。但是头文件中定义的槽(udpateImage,cameraStart和cameraControl)并没有出现在槽列表中,如下图所示:
我在这里错过了其他任何步骤还是我做错了什么?还需要注意QMainWindow的是,这些插槽应该出现在哪些框架中,我猜也没有显示在列表中。
我想检查是否已清除某些轴,根据这些轴执行某些进一步的任务.我cla用来清除一些轴,而不是delete.例如:
figure
hs1 = subplot(121); plot(rand(100,2), 'x');
hs2 = subplot(122); plot(rand(100,2), 'o');
cla(hs1)
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然后,问题是如何确定是否hs1被清除.
按照http://docs.opencv.org/trunk/d4/d73/tutorial_py_contours_begin.html提供的示例 ,我在 Spyder 环境中使用 python 在二进制图像中绘制检测到的组件的轮廓。我的代码在这里:
im = cv2.imread('test.jpg') #raw RGB image
im2 = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY) #gray scale image
plt.imshow(im2,cmap = 'gray')
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图像如下:
然后,
thresh, im_bw = cv2.threshold(im2, 127, 255, cv2.THRESH_BINARY) #im_bw: binary image
im3, contours, hierarchy = cv2.findContours(im_bw,cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
cv2.drawContours(im2, contours, -1, (0,255,0), 3)
plt.imshow(im2,cmap='gray') #without the code, only an array displayed in the console
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由于某种原因,这些代码没有给出具有轮廓的图形。但是如果我将最后两行代码更改如下:
cv2.drawContours(im, contours, -1, (0,255,0), 3)
plt.imshow(im,cmap='gray')
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它产生一个具有轮廓的图形:
我对这些代码如何工作感到困惑?cv2.drawCoutours 只适用于 GRB 图像吗?希望不是。此外,值得注意的是,contours[0] 给出了一个 3D 数组:
idx = contours[0]
print idx.shape
(392L, 1L, 2L)
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idx …
我正在使用python代码network3.py(http://neuralnetworksanddeeplearning.com/chap6.html)开发卷积神经网络。现在,我想通过添加动量学习规则来对代码进行一些修改,如下所示:
velocity = momentum_constant * velocity - learning_rate * gradient
params = params + velocity
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有谁知道该怎么做吗?特别是如何设置或初始化速度?我在下面发布了SGD的代码:
def __init__(self, layers, mini_batch_size):
"""Takes a list of `layers`, describing the network architecture, and
a value for the `mini_batch_size` to be used during training
by stochastic gradient descent.
"""
self.layers = layers
self.mini_batch_size = mini_batch_size
self.params = [param for layer in self.layers for param in layer.params]
self.x = T.matrix("x")
self.y = T.ivector("y")
init_layer = self.layers[0]
init_layer.set_inpt(self.x, self.x, self.mini_batch_size)
for j in xrange(1, …Run Code Online (Sandbox Code Playgroud) 我正在开发一个用 C++ 编写的 Qt5 项目。构建项目报错:
C2440:“=”:无法从“const char [9]”转换为“char*”
这指向下面的代码行:
port_name= "\\\\.\\COM4";//COM4-macine, COM4-11 Office
SerialPort arduino(port_name);
if (arduino.isConnected())
qDebug()<< "ardunio connection established" << endl;
else
qDebug()<< "ERROR in ardunio connection, check port name";
//the following codes are omitted ....
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这里有什么问题,我该如何纠正?
我想通过一个简单的例子来看看按位不工作是如何工作的:
int x = 4;
int y;
int z;
y = ~(x<<1);
z =~(0x01<<1);
cout<<"y = "<<y<<endl;
cout<<"z = "<<z<<endl;
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这导致y = -9和z = -3。我不明白这是怎么发生的。任何人都可以教育我一点吗?
我对char数组的内存地址感到困惑.这是演示代码:
char input[100] = "12230 201 50";
const char *s = input;
//what is the difference between s and input?
cout<<"s = "<<s<<endl; //output:12230 201 50
cout<<"*s = "<<*s<<endl; //output: 1
//here I intended to obtain the address for the first element
cout<<"&input[0] = "<<&(input[0])<<endl; //output:12230 201 50
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char数组本身是指针吗?为什么&运算符不给出char元素的内存地址?如何获取个别条目的地址?谢谢!
Following is my code for creating a map<int, vector<int>> and printing:
//map<int, vector>
map<int, vector<int>> int_vector;
vector<int> vec;
vec.push_back(2);
vec.push_back(5);
vec.push_back(7);
int_vector.insert(make_pair(1, vec));
vec.clear();
if (!vec.empty())
{
cout << "error:";
return -1;
}
vec.push_back(1);
vec.push_back(3);
vec.push_back(6);
int_vector.insert(make_pair(2, vec));
//print the map
map<int, vector<int>>::iterator itr;
cout << "\n The map int_vector is: \n";
for (itr2 = int_vector.begin(); itr != int_vector.end(); ++itr)
{
cout << "\t " << itr->first << "\t" << itr->second << "\n";
}
cout << endl;
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The printing part …
我正在使用 anaconda python 3.7 和tensorflow 2.1以及cuda 10.1和cudnn 7.6.5,并尝试运行retinaset(https://github.com/fizyr/keras-retinanet):
python keras_retinanet/bin/train.py --freeze-backbone --random-transform --batch-size 8 --steps 500 --epochs 10 csv annotations.csv classes.csv
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下面是由此产生的错误:
Epoch 1/10
2020-02-10 20:34:37.807590: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2020-02-10 20:34:38.835777: E tensorflow/stream_executor/cuda/cuda_dnn.cc:329] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
2020-02-10 20:34:39.753051: E tensorflow/stream_executor/cuda/cuda_dnn.cc:329] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
2020-02-10 20:34:39.776706: W tensorflow/core/common_runtime/base_collective_executor.cc:217] BaseCollectiveExecutor::StartAbort Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if …Run Code Online (Sandbox Code Playgroud) 给定一个仅包含 0 和 1 个元素的索引数组idx,1 代表感兴趣的样本索引,以及一个样本数组A( A.shape[0] = idx.shape[0])。这里的目标是根据索引向量提取样本子集。
在 matlab 中,执行以下操作很简单:
B = A(idx,:) %assuming A is 2D matrix and idx is a logical vector
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如何在Python中以简单的方式实现这一点?
我想将一些字符串和数值打印到 txt 文件中。输出类似于:
Accuracy: 0.98
Loss: 0.10
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我的代码如下:
output_file = open('filepath','w')
output_file.write('Accuracy:\n',0.98)
output_file.write('Loss:\n',0.10)
output_file.close()
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但由于写入函数“TypeError:函数恰好需要 1 个参数(给定 2 个)”,它们将无法工作
我看到代码:Mat imgOrg = imread( fileName, -1 );。该参数指的是哪种标志imreadmodes ?-1