Build Complete Webcam Security Camera | Python OpenCV & Pyqt
Step-by-step guide| Build your own webcam security camera alert system using Python Pyqt OpenCv QtDesigner from scratch
What you’ll learn
Build Complete Webcam Security Camera | Python OpenCV & Pyqt
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How to detect and recognize objects in webcam-captured images using OpenCV Python code.
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Learn to convert images to greyscale, the difference between two images, and gaussian blur in opencv python.
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Learn to get contours of detected objects in webcam-captured video frames and draw rectangles of detected objects.
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How to find the area of contours detected by the opencv in the camera-captured images and provide an alarm sound if any object
Requirements
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Basic Python programming
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A computer or laptop with an internet connection
Description
Hello Students
Welcome to the course “Build Complete Webcam Security Camera | Python OpenCv & Pyqt.”
You will learn how to create a beautiful user interface for the project using Pyqt Library and the Qt Designer.
1. Installation and configuration
First, we will
install the required software
to start our project from the internet.
Learn to install Python, pyqt5, pyqt5-tools and OpenCV library
. Then you will learn how to install the vs code and configure vs code to python programming through this course.
2. Design the user interface
Then we are going to
design a beautiful user interface using Qt Designer
. In this interface, we will use basic controls like
QPushButton, QLabel, and QSlider
and learn
how to use style sheets
to make the controls look good. Then you will learn how to provide the
hover effects
to the QPushButtons and change the images in the dynamic labels.
3. Camera Capture and display in the window
Then we will
implement the camera using the cv2 library
and
capture the images
in the camera. Then we
show the captured images
in the cv2 window.
4. Image processing
Then we will
convert the images to our required formats
to identify the contours in the images. We will first
convert the images to grayscale
images using OpenCV. Then we are going to
dilate images using OpenCV
. Then we will
collect all the contours in the images
using opencv python.
5. Object Detection
Then will find the
contour area greater than 5000
and
draw a rectangle using the cv2
library for the captured objects. This shows the captured objects in green colour to identify them easily.
6. Display captured objects
Then we are going to
save the captured objects
in an image file. The captured image file is then
labelled
in the pyqt window. This is
used to identify the object even if the object passes the cam area
.
This project will teach you many basic functions in the OpenCV library and how to use basic controls using qt designer and process the GUI controls using python code.
Thank you for your interest in this course…
I will see you on the course.
Who this course is for:
- Developers who want to learn OpenCV and develop a complete project using open cv
- Students who want to develop a complete project using opencv and pyqt for final-year submission
- Students or developers who want to build their security camera software using a webcam
- Python learners who want to increase their skills and enter into Artificial Intelligence programming
Build Complete Webcam Security Camera | Python OpenCV & Pyqt FreeCourseSites.com
Build your GUI Apps faster with PyQt5 & QT Designer | Python
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