Application Face Detection and Digital Imaging with Python on PYChram [part1] [NumPY]

in #utopian-io7 years ago (edited)

What Will I Learn?

Write here briefly the details of what the user is going to learn in a bullet list.

  • You will learn Python
  • You will learn Numpy
  • You will learn Pychram

Requirements

  • Package Numpy
  • Pychram

Difficulty

  • Basic

Tutorial Contents

Hello All of member Utopian, now I wanna make tutorial how to make "Application Face Detection and Digital Imaging with Python" but first you must know, what is numpy?

Explanation Numpy

Numpy is the module needed for OpenCV to work properly. Numpy itself is an abbreviation of Numerical python, is a library package that provides various routines to process multidimensional arrays.

Add Numpy Package on PYChram

1 . Open Your PYChram.

2 . Add New Project With Name facedetector.

3 . Add Numpy Library. Follow me to get install numpy library on your Pychram.

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Project First Numpy.

1 . Add new python file. click right on project name > new > Python file.
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2 . Set with name tes-numpy.

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3 . Write this source code.

import numpy as num
number = num.array([1,2,3])
print (number)

4 . Run that program. right click > Run 'tes-numpy,
and you got that program result.
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Explain Source Code.

This code to call numpy package to program.

import numpy as num

This code to make variable number with Array value ([1,2,3]).

number = num.array([1,2,3])

This code to print value on variable number.

print (number)

Okay this tutorial to be continue to part 2 how to install OpenCV on PYChram and run it.



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Your contribution cannot be approved because it does not follow the Utopian Rules.

Hi, this is the reason your contribution was rejected

  • The tutorial is too trivial to be accepted and has nothing to do with the title of your tutorial. You only install numpy, create an array and print it - this is much too little information and simply too trivial to be a valuable contribution.

I recommend you focus on the non-trivial aspects of face detection using numpy, of which there are more than enough.

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