Real-Time Face Blur OpenCV Python With Source Code
The Real-Time Face Blur OpenCV Python was developed using Python OpenCV, This Python OpenCV Project With Source Code you will learn how to blur and anonymize faces using OpenCV and Python.
A OpenCV Python Face Blur we are going to learn to Realtime videos using OpenCV and try to learn with existing tools like Haar cascades and build Realtime Face Detection and Face blur.
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 Face Blur OpenCV Python With Source Code, make sure that you have installed Python 3.9 and PyCharm in your computer.
Real-Time Face Blur 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 Face Blur 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
# import the necessary packages import cv2 cap = cv2.VideoCapture(0) faceCascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml') while True: success,img = cap.read() faces = faceCascade.detectMultiScale(img,1.2,4) for (x, y, w, h) in faces: # To make a face blurred ROI = img[y:y+h, x:x+w] blur = cv2.GaussianBlur(ROI, (91,91),0) # Insert ROI back into image img[y:y+h, x:x+w] = blur # To make a bounding box #*(Not Necessary) # cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),4) if faces==(): cv2.putText(img,'No Face Found!',(20,50),cv2.FONT_HERSHEY_COMPLEX,1,(0,0,255)) cv2.imshow('Face Blur',img) if cv2.waitKey(1) & 0xff==ord('q'): break # Turn camera off cap.release() # Close camera window cv2.destroyAllWindows()
Real-Time Face Blur OpenCV Python : Project Information
|Project Name:||Real-Time Face Blur OpenCV Python|
|Language/s Used:||Python OpenCV|
|Python version (Recommended):||3.8|
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 Python OpenCV Project With Source Code, you learned how to blur and anonymize faces in both images and real-time video streams using OpenCV and Python. It also includes a downloadable source code for free.
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