Real-Time Profile Face Detection OpenCV Python With Source Code
The Real-Time Profile Face Detection OpenCV Python was developed using Python OpenCV, In computer vision, one essential problem we are trying to figure out is to automatically detect objects in an image without human intervention. Face detection can be thought of as such a problem where we detect human faces in an image.
A Profile Face Detection OpenCV Python is usually the first step towards many face-related technologies, such as face recognition or verification. However, face detection can have very useful applications. The most successful application of face detection would probably be photo taking. When you take a photo of your friends, the face detection algorithm built into your digital camera detects where the faces are and adjusts the focus accordingly.
The very first task we perform is detecting faces in the image or video stream. Now that we know the exact location/coordinates of face, we extract this face for further processing ahead.
In this Face Detection OpenCV Python also includes a downloadable Python Project With Source Code for free, just find the downloadable source code below and click to start downloading.
Watch the video here to see the full running source code of the Real-Time Profile Face Detection OpenCV Python with Source Code
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 Real-Time Profile Face Detection OpenCV Python With Source Code, make sure that you have installed Python 3.9 and PyCharm in your computer.
Real-Time Profile Face 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 Profile Face Detection 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
# Load the cascade
face_cascade = cv2.CascadeClassifier('haarcascade_profileface.xml')
# To capture video from webcam.
cap = cv2.VideoCapture(0)
# To use a video file as input
# cap = cv2.VideoCapture('filename.mp4')
# Read the frame
_, img = cap.read()
# Convert to grayscale
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Detect the faces
faces = face_cascade.detectMultiScale(gray, 1.1, 4)
# Draw the rectangle around each face
for (x, y, w, h) in faces:
cv2.rectangle(img, (x, y), (x+w, y+h), (255, 0, 0), 2)
# Stop if escape key is pressed
k = cv2.waitKey(30) & 0xff
# Release the VideoCapture object
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Download Source Code below
In this article, we will know what is face recognition and how is different from face detection. We will go briefly over the theory of face recognition and then jump on to the coding section. At the end of this article, you will be able to make a face recognition program for recognizing faces in images as well as on live webcam feed.
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