Extract Faces From Image OpenCV Python With Source Code
The Extract Faces From Image OpenCV Python was developed using Python OpenCV, This Python OpenCV Project With Source Code, Images make up a large amount of the data that gets generated each day, which makes the ability to process these images important. One method of processing images is via face detection. Face detection is a branch of image processing that uses machine learning to detect faces in images.
A OpenCV Extract Faces Python you will use a pre-trained Haar Cascade model from OpenCV and Python to detect and extract faces from an image. OpenCV is an open-source programming library that is used to process images.
A Haar Cascade is an object detection method used to locate an object of interest in images. The algorithm is trained on a large number of positive and negative samples, where positive samples are images that contain the object of interest. Negative samples are images that may contain anything but the desired object. Once trained, the classifier can then locate the object of interest in any new images.
What is OpenCV?
OpenCV is short for Open Source Computer Vision. Intuitively by the name, it is an open-source Computer Vision and Machine Learning library. This library is capable of processing real-time image and video while also boasting analytical capabilities. It supports the Deep Learning frameworks.
In this Python OpenCV Project 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 know what would be the the Python IDE to use, I have here a list of Best Python IDE for Windows, Linux, Mac OS that will suit for you. I also have here How to Download and Install Latest Version of Python on Windows.
To start executing Extract Faces From Image OpenCV Python With Source Code, make sure that you have installed Python 3.9 and PyCharm in your computer.
Extract Faces From Image OpenCV Python With Source Code : Steps on how to run the project
Time needed: 5 minutes.
These are the steps on how to run Extract Faces From Image OpenCV Python With Source Code
- Step 1: Download the given source code below.
First, download the given source code below and unzip the source code.
- Step 2: Import the project to your PyCharm IDE.
Next, import the source code you’ve download to your PyCharm IDE.
- Step 3: Run the project.
last, run the project with the command “py main.py”
Complete Source Code
img = cv2.imread('profile .jpg') #Path of an image
faceCascade = cv2.CascadeClassifier('haarcascades/haarcascade_frontalface_default.xml')
faces = faceCascade.detectMultiScale(img,1.1,4)
directory = os.getcwd()+r''
except FileExistsError as fee:
for (x, y, w, h) in faces:
FaceImg = img[y:y+h,x:x+w]
# To save an image on disk
filename = 'Face'+str(i)+'.jpg'
Extract Faces From Image OpenCV Python : Project Information
|Project Name:||Extract Faces From Image OpenCV Python|
|Language/s Used:||Python OpenCV|
|Python version (Recommended):||3.8|
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Download Source Code below
Anyway, if you want to level up your programming knowledge, especially Python OpenCV, try this new article I’ve made for you Best OpenCV Projects With Source Code For Beginners 2021.
In this article, you know on how to wrote a script that uses OpenCV and Python to detect, count, and extract faces from an input image. You can update this script to detect different objects by using a different pre-trained Haar Cascade from the OpenCV library, or you can learn how to train your own Haar Cascade.
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