Python Learning

  Python  Syntax As we learned in the previous page, Python syntax can be executed by writing directly in the Command Line: >>> print("Hello, World!") Hello, World! Or by creating a python file on the server, using the .py file extension, and running it in the Command Line: C:\Users\ Your Name >python myfile.py Python Indentation Indentation refers to the spaces at the beginning of a code line. Where in other programming languages the indentation in code is for readability only, the indentation in Python is very important. Python uses indentation to indicate a block of code. Python has no command for declaring a variable. You will learn more about variables in the  Python Variables  chapter. Comments Python has commenting capability for the purpose of in-code documentation. Comments start with a #, and Python will render the rest of the line as a comment:

  Python  Tutorial print ( "Hello, World!" ) What is Python? Python is a popular programming language. It was created by Guido van Rossum, and released in 1991. It is used for: web development (server-side), software development, mathematics, system scripting. What can Python do? Python can be used on a server to create web applications. Python can be used alongside software to create workflows. Python can connect to database systems. It can also read and modify files. Python can be used to handle big data and perform complex mathematics. Python can be used for rapid prototyping, or for production-ready software development. Why Python? Python works on different platforms (Windows, Mac, Linux, Raspberry Pi, etc). Python has a simple syntax similar to the English language. Python has syntax that allows developers to write programs with fewer lines than some other programming languages. Python runs on an interpreter system, meaning that code can be executed as soon as it is wri...

  How to Detect Shapes in Images in Python using OpenCV import numpy as np import matplotlib.pyplot as plt import cv2 import sys # read the image from arguments image = cv2.imread( r'G:\PARAS\anuradha.png' ) # convert to grayscale grayscale = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) # perform edge detection edges = cv2.Canny(grayscale, 30 , 100 ) # detect lines in the image using hough lines technique lines = cv2.HoughLinesP(edges, 1 , np.pi/ 180 , 60 , np.array([]), 50 , 5 ) # iterate over the output lines and draw them for line in lines: for x1, y1, x2, y2 in line: cv2.line(image, (x1, y1), (x2, y2), color =( 20 , 220 , 20 ), thickness = 3 ) # show the image plt.imshow(image) plt.show()