Real-Time Human Body Detection OpenCV Python – Human detection is the process of detecting all occurrences of human beings in an image by examining all locations in the image at all feasible scales and comparing a small area at each site with known templates or patterns of people.

Importance of Real-Time Human Body Detection OpenCV Python

We can use the detection program to identify and find things. It’s critical in areas of research where the detected object can be counted and determined precisely.

The OpenCV library functions in Python are primarily designed for real-time computer vision.

Beneficiaries of Real-Time Human Body Detection OpenCV Python

A combination of cameras, radar, and lidar sensors is used to detect pedestrians.

These systems keep an eye on the environment around a vehicle and should allow the driver and vehicle to react properly.

Some cameras search for items in the car’s path, while others look for individuals who may cross in front of it.

Real-Time Human Body Detection In Python: Project Details and Technology

Project Name:	Real-Time Human Body Detection Project In Python With Source Code
Abstract	Human Body Detection Python OpenCV The task of detecting all occurrences of humans in an image is known as human detection.
Language/s Used:	Python Deep Learning
Python version (Recommended):	3.8/3.9
Database:	None
Type:	Desktop Application
Developer:	Source Code Hero
Updates:	0

Real-Time Human Body Detection Project In Python – Project Information

Real-Time Human Body Detection OpenCV Python: About the project

This Real-Time Human Body Detection OpenCV Python was created with the Python programming language, and it will show you how to make your own “smart” video camera.

It will demonstrate how to capture an image from a web camera’s frame, recognize if there is a human in the frame, and count how many persons or individuals are detected on the video camera.

A Human Body Detection Python OpenCV project is an intermediate-level deep learning project on computer vision that will help you master the principles and become a Data Science specialist.

Let’s work together to create an intriguing project.

We will develop a Human Detection and Counting System using a Webcam or your own video or photos in this Full Body Detection OpenCV Python.

Pedestrian crossing, criminal identification, healthcare, and other computer applications that identify the human body in digital photographs are just a few examples.

We can use the detection program to identify and find things.

It’s critical in areas of research where the detected object can be counted and determined precisely.

The functions of the Detection OpenCV Python package are primarily intended for real-time computer vision.

We will create a Pedestrian Detection program in this post. The OpenCV library includes algorithms for detecting people’s faces.

Real-Time Human Body Detection OpenCV Python: Project Prerequisites

The project in Python requires you to have basic knowledge of Python programming and the OpenCV library. We will be needing the following libraries:

OpenCV – A strong library used for machine learning
Imutils – To Image Processing
Numpy – Used for Scientific Computing. Image is stored in a numpy array.
Argparse – Used to give input in command line.

To install the required library, run the following code in your terminal.

pip install opencv-python
pip install imutils
pip install numpy

Histogram of Oriented Gradient Descriptor

HOG is a feature descriptor used in computer vision and image processing for the purpose of object detection. This is one of the most popular techniques for object detection, to our fortune, OpenCV has already been implemented in an efficient way to combine the HOG Descriptor algorithm with Support Vector Machine or SVM.

This Real-Time Human Body Detection In Python also includes a downloadable Python Project With Source Code for free, just find the downloadable source code below and click to start downloading.

By the way, if you are new to Python programming and you don’t have any idea what Python IDE is, I have here a list of the Best Python IDE for Windows, Linux, Mac OS for you.

Additionally, I also have here How to Download and Install the Latest Version of Python on Windows.

To start executing a Real-Time Human Body Detection OpenCV Python With Source Code, make sure that you have installed Python on your computer.

Real-Time Human Body Detection OpenCV Python With Source Code: Steps on how to run the project

Time needed: 5 minutes

These are the steps on how to run Real-Time Human Body Detection OpenCV Python With Source Code

Step 1: Download Source Code
First, download the provided source code below.
Step 2: Extract File
Next, after the download finished extract the zip file.
Step 3: Import the project to your PyCharm IDE.
Next, import the source code you’ve download to your PyCharm IDE.
Step 4: Install all Libraries.
Next, install all libraries given below.
Step 5: Open cmd.
Next, click the folder directory of the project and type cmd.
Step 6: Run Project.
last, run the project with the command “py main.py”

Download the Source Code below

DOWNLOAD

Summary

In this deep learning project, we have learned how to create a people counter using HOG and OpenCV to generate an efficient people counter.

We developed the project where you can supply the input as: video, image, or even live camera. This is an intermediate-level project, which will surely help you in mastering Python and deep learning libraries.

Inquiries

If you have any questions or suggestions about Real-Time Human Body Detection OpenCV Python With Source Code, please feel free to leave a comment below.

Real-Time Human Body Detection OpenCV Python