Construisez une caméra de sécurité avec Python et OpenCV

Dans ce tutoriel, nous allons construire un système de sécurité de base en utilisant uniquement Python, le module OpenCV et une webcam.

Le but sera de détecter un visage ou un corps (donc la webcam). Une fois qu'un visage ou un corps est détecté, le système les extraira automatiquement et les enregistrera dans un dossier.

Cela dit, ce tutoriel supposera que Python est installé et que vous connaissez les bases du module OpenCV.
Écrivons du code.

Configuration d'OpenCV

Si vous avez déjà installé OpenCV, vous pouvez ignorer cette étape.
Sinon, accédez à votre terminal dans votre dossier de projet et tapez :

pip3 install opencv-python

Si pip3 ne fonctionne pas, essayez avec seulement pip.

Maintenant que le module est installé, ouvrons un fichier main.py et commençons à écrire la logique.

Bibliothèques et configuration

Commençons par importer quelques bibliothèques utiles et commençons à écrire ce que nous utiliserons.

import cv2
from datetime import datetime
import os

cap = cv2.VideoCapture(0) 

face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml")
body_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_fullbody.xml")

if not os.path.exists('detections'):
    os.mkdir('detections') # make sure you have a detections folder

Nous utilisons l'algorithme haarcascade pour détecter les visages et les corps, pré-construit par OpenCV.
La bonne chose est qu'ils sont très rapides et assez précis. Cependant, ils sont notoirement sujets aux faux positifs et ils fonctionnent mieux avec des faces frontales, mais compte tenu de leur vitesse, c'est assez bon pour nos besoins.

Boucle principale

C'est ici que les grandes choses vont se passer. Nous accéderons à chaque cadre de caméra, nous le transmettrons à nos deux modèles et nous extrairons les visages et les corps.

while True:    
    _, frame = cap.read()    
    
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)    
    
    faces = face_cascade.detectMultiScale(gray, 1.3, 5)    
    bodies = face_cascade.detectMultiScale(gray, 1.3, 5)

Nous convertissons d'abord notre cadre en une image en niveaux de gris, car c'est ce dont les cascades ont besoin.

• 1.3 est simplement un facteur d'échelle et il détermine la vitesse et la précision de l'algorithme (plus il est bas, plus il sera précis et lent, mais il doit être > 1)
• 5 est le nombre de voisins pour le classement (vous pouvez jouer avec eux).

Une fois les visages ou les corps détectés, nous pouvons accéder à leurs coordonnées. Nous allons dessiner des rectangles autour de chaque face et les extraire du cadre. (Vous pouvez faire exactement la même chose avec les corps).

  for (x, y, width, height) in faces:    
        cv2.rectangle(frame, (x, y), (x + width, y + height), (255, 0, 0), 3)
        face_roi = frame[y:y+height, x:x+width]

ROI signifie région d'intérêt, ce qui correspond aux visages dans notre cas.

Maintenant que nous avons les visages, il ne nous reste plus qu'à les sauvegarder, mais attention : puisque nous sommes dans une boucle, nous risquons d'avoir des centaines et des centaines d'images identiques, si nous ne mettons pas certaines conditions en place.

 if not os.path.exists('detections/' + datetime.now().strftime('%Y-%m-%d')):
            os.mkdir('detections/' + datetime.now().strftime("%Y-%m-%d"))

        cv2.imwrite('detections/' + datetime.now().strftime("%Y-%m-%d") + '/' + datetime.now().strftime("%H-%M") + '.jpg', face_roi)

    cv2.imshow('frame', frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

Ça y est ...! Cependant, outre quelques correctifs qui pourraient rendre le code plus efficace (un peu de refactorisation, de modularisation, une meilleure implémentation), c'est un bon point de départ pour construire une belle caméra de sécurité.

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Lambda, Map, Filter functions in python

Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.

Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is

Syntax: x = lambda arguments : expression

Now i will show you some python lambda function examples:

#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map

Why use Python for Software Development

No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas. 

By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities. 

Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly. 

5 Reasons to Utilize Python for Programming Web Apps 

Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.

Robust frameworks 

Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions. 

Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events. 

Simple to read and compose 

Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building. 

The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties. 

Utilized by the best 

Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player. 

Massive community support 

Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions. 

Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking. 

Progressive applications 

Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.

The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.

Summary

Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential. 

The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.

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Create a Virtual Pen and Eraser with Python OpenCV - Genial Code

Learn Free how to create a virtual pen and eraser with python and OpenCV with source code and complete guide. This entire application is built fundamentally on contour detection. It can be thought of as something like closed color curves on compromises that have the same color or intensity, it’s like a blob. In this project we use color masking to get the binary mask of our target color pen, then we use the counter detection to find the location of this pen and the contour to find it.

#python #create virtual pen and eraser with opencv #create virtual pen and eraser with python opencv #programming #opencv #python opencv

Python Tricks Every Developer Should Know

Python is awesome, it’s one of the easiest languages with simple and intuitive syntax but wait, have you ever thought that there might ways to write your python code simpler?

In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.

Let’s get started

Swapping value in Python

Instead of creating a temporary variable to hold the value of the one while swapping, you can do this instead

>>> FirstName = "kalebu"
>>> LastName = "Jordan"
>>> FirstName, LastName = LastName, FirstName 
>>> print(FirstName, LastName)
('Jordan', 'kalebu')

#python #python-programming #python3 #python-tutorials #learn-python #python-tips #python-skills #python-development

How to Remove all Duplicate Files on your Drive via Python

Today you’re going to learn how to use Python programming in a way that can ultimately save a lot of space on your drive by removing all the duplicates.

Intro

In many situations you may find yourself having duplicates files on your disk and but when it comes to tracking and checking them manually it can tedious.

Heres a solution

Instead of tracking throughout your disk to see if there is a duplicate, you can automate the process using coding, by writing a program to recursively track through the disk and remove all the found duplicates and that’s what this article is about.

But How do we do it?

If we were to read the whole file and then compare it to the rest of the files recursively through the given directory it will take a very long time, then how do we do it?

The answer is hashing, with hashing can generate a given string of letters and numbers which act as the identity of a given file and if we find any other file with the same identity we gonna delete it.

There’s a variety of hashing algorithms out there such as

• md5
• sha1
• sha224, sha256, sha384 and sha512

#python-programming #python-tutorials #learn-python #python-project #python3 #python #python-skills #python-tips