Face detection with OpenCV in Python

For Face Detection with OpenCV in Python for Windows, Debian and Raspberry you can follow these simple steps:

ยป More Python Examples

Create a virtual environment in Python

In Linux Debian we use the following command to install virtualenv, which will allow us to create virtual environments and isolate the libraries that we will install so that they do not cause problems:

sudo apt -y install virtualenv

To create a virtual environment we execute the following command:

python3 -m venv /path/to/virtual/environment
# Or you can also use this other one if you want to create it in the same folder:
python3 -m venv venv

More to how to create an environment or virtual environment in Python: https://decodigo.com/create-a-virtual-environment-in-python

Activate the virtual environment

To activate the virtual environment:

source venv/bin/activate

Install OpenCV

Install OpenCV using pip3:

pip3 install opencv-python

Python code for Windows and Linux

This example was tested on Windows 10 and Debian 11

import cv2

#geekole.com

# https://github.com/opencv/opencv/tree/master/data/haarcascades
# read the file cascade
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

# Capture the video
cap = cv2.VideoCapture(0)

while True:
    # Read the frame
    _, img = cap.read()
    # Converts to grayscale
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    # Detecting faces
    faces = face_cascade.detectMultiScale(gray, 1.1, 4)
    # Drawing a rectangle for each detected face
    for (x, y, w, h) in faces:
        cv2.rectangle(img, (x, y), (x+w, y+h), (255, 0, 0), 2)
    # Shown in the window
    cv2.imshow('img', img)
    # For if the 'Esc' key is pressed
    k = cv2.waitKey(30) & 0xff
    if k==27:
        break
# The capture object is released
cap.release()

Code for Raspberry with Raspbian

Code for Raspberry with Raspbian modifying the resolution of the capture video, you should also know that other Web cameras can be used. You can use the Camera Pi, however from the latest version of Raspbian (bullseye) the camera will no longer be supported. But for this example you can use any other connected by the USB port.

Face detection with OpenCV in Python

import cv2

#geekole.com

# https://github.com/opencv/opencv/tree/master/data/haarcascades
# read the file cascade
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

# Capture the video
cap = cv2.VideoCapture(0)
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 320)  # set new dimensionns to cam object (not cap)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 240)

while True:
    # Lee el frame
    _, img = cap.read()
    # Converts to grayscale
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    # Detecting faces
    faces = face_cascade.detectMultiScale(gray, 1.1, 4)
    # Drawing a rectangle for each detected face
    for (x, y, w, h) in faces:
        cv2.rectangle(img, (x, y), (x+w, y+h), (255, 0, 0), 2)
    # Shown in the window
    cv2.imshow('img', img)
    # For if the 'Esc' key is pressed
    k = cv2.waitKey(30) & 0xff
    if k==27:
        break
# The capture object is released
cap.release()

Additional

It could happen that you need the following libraries, but if you have no problems it is not necessary to install them

sudo apt-get libatlas-base-dev

sudo apt-get install libcblas-dev
sudo apt-get install libhdf5-dev
sudo apt-get install libhdf5-serial-dev
sudo apt-get install libatlas-base-dev
sudo apt-get install libjasper-dev 
sudo apt-get install libqtgui4 
sudo apt-get install libqt4-test

As you can see face detection with OpenCV in Python is easy but you can do much more with OpenCV.

More about OpenCV: https://opencv.org/