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from pathlib import PurePath, Path | |
def stringify_file(filename: str) -> str: | |
single_file = "" | |
with open(filename) as file: | |
for line in file: | |
if len(line.strip()) > 0: | |
line = line.split('#') | |
if len(line) == 1: # the line has comments, then ignore them |
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#include <iostream.h> //example of operator overloading | |
template<class T> | |
class Stack { | |
public: | |
Stack(int n); | |
Stack(Stack<T>& s); //copy constructor | |
~Stack() {delete [] stackPtr;} // destructor | |
Stack<T> operator + (const Stack<T>& s2) const; //overloading + | |
Stack<T>& operator = (const Stack<T>& s); //overloading assignment |
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# Numpy is needed because OpenCV images in python are actually numpy arrays. | |
import numpy | |
import cv2 | |
class iris_detection(): | |
def __init__(self, image_path): | |
''' | |
initialize the class and set the class attributes | |
''' | |
self._img = None |
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#include <windows.h> | |
#include <GLFW/glfw3.h> | |
#include <iostream> | |
// change this to int main() to allow the console | |
int WINAPI WinMain(HINSTANCE hInstance, HINSTANCE hPrevInstance, char*, int nShowCmd) | |
{ | |
GLFWwindow* window; | |
int windowSizeW = 640, windowSizeH = 480; | |
// initialize the library |
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import scipy.io as scio | |
from typing import Any, Dict | |
import numpy as np | |
def load_matfile(filename: str) -> Dict: | |
def parse_mat(element: Any): | |
# lists (1D cell arrays usually) or numpy arrays as well | |
if element.__class__ == np.ndarray and element.dtype == np.object_ and len(element.shape) > 0: | |
return [parse_mat(entry) for entry in element] |
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@echo off | |
REM Remove files generated by compiler in this directory and all subdirectories. | |
REM Essential release files are kept. | |
echo Removing "*.csproj.user" files... | |
for /f "delims==" %%i in ('dir /b /on /s "%~p0*.csproj.user"') do del "%%i" /f /q | |
echo. | |
echo Removing "*.exe.config" files... |
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import sys | |
import pandas as pd | |
filename = sys.argv[1] | |
filename = filename[:-4] | |
read_file = pd.read_csv (filename + ".csv") | |
read_file.to_excel (filename + ".xlsx", index = None, header=True) | |
# run as | |
# python csv_to_xlsx.py %1 |
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from tensorflow.keras import Model | |
from tensorflow.keras.layers import Convolution2D | |
from tensorflow.keras.layers import MaxPool2D | |
from tensorflow.keras.layers import BatchNormalization | |
from tensorflow.keras.layers import Input | |
from tensorflow.keras.layers import Flatten | |
from tensorflow.keras.layers import Dropout | |
from tensorflow.keras.layers import Dense | |
from tensorflow.keras.layers import concatenate | |
from tensorflow.keras.optimizers import Adam |
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vtkNew<vtkCallbackCommand> keypressCallback; | |
auto KeypressCallbackFunction = [](vtkObject* caller, long unsigned int vtkNotUsed(eventId), void* clientData, void* vtkNotUsed(callData)) { | |
vtkRenderWindowInteractor* iren = static_cast<vtkRenderWindowInteractor*>(caller); | |
std::cout << "Pressed: " << iren->GetKeySym() << std::endl; | |
}; | |
keypressCallback->SetCallback(KeypressCallbackFunction); | |
renderWindowInteractor->AddObserver(vtkCommand::KeyPressEvent, keypressCallback); |
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#include <iostream> | |
#include <string> | |
#include <sstream> | |
template <typename T> | |
std::string to_string_with_precision(const T a_value, const int n = 4) | |
{ | |
std::ostringstream out; | |
out.precision(n); | |
out << std::fixed << a_value; |
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