A memo when face is detected with Python + OpenCV quickly

table of contents

[1. Preparing the virtual environment](# 1-Preparing the virtual environment) [2. Install openCV](# 2-Install openCV) [3. Face detection program preparation](# 3-Face detection program preparation) [4. Get the classifier file](# 4-Get the classifier file) [5. Execute](# 5-Execute) [6. Source Code](# 6-Source Code)

Preparing the virtual environment

Create opencvEnv environment with venv

$ python3 -m venv opencvEnv

#Activate
$ source opencvEnv/bin/activate

(opencvEnv)$  ...

install openCV

Install openCV with pip

(opencvEnv)$ pip install opencv-python

Collecting opencv-python
  Downloading https://files.pythonhosted.org/packages/e2/a9/cd3912ca0576ea6588095dce55e54c5f0efeb3d63fb88f16f4c06c0fac8d/opencv_python-4.1.2.30-cp36-cp36m-macosx_10_9_x86_64.whl (45.2MB)
    100% |████████████████████████████████| 45.2MB 721kB/s
Collecting numpy>=1.11.3 (from opencv-python)
  Using cached https://files.pythonhosted.org/packages/22/99/36e3408ae2cb8b72260de4e538196d17736d7fb82a1086cb2c21ee156ddc/numpy-1.17.4-cp36-cp36m-macosx_10_9_x86_64.whl
Installing collected packages: numpy, opencv-python
Successfully installed numpy-1.17.4 opencv-python-4.1.2.30
import cv2

Face detection program preparation

Create face_detect.py

face_detect.py

import cv2

if __name__ == '__main__':
    #Constant definition
    ESC_KEY = 27     #Esc key
    INTERVAL= 33     #Waiting time
    FRAME_RATE = 30  # fps

    ORG_WINDOW_NAME = "org"
    GAUSSIAN_WINDOW_NAME = "gaussian"

    DEVICE_ID = 0

    #Designation of classifier
    cascade_file = "../xml/haarcascade_frontalface_alt2.xml"
    cascade = cv2.CascadeClassifier(cascade_file)

    #Camera image acquisition
    cap = cv2.VideoCapture(DEVICE_ID)

    #Loading initial frame
    end_flag, c_frame = cap.read()
    height, width, channels = c_frame.shape

    #Window preparation
    cv2.namedWindow(ORG_WINDOW_NAME)
    cv2.namedWindow(GAUSSIAN_WINDOW_NAME)

    #Conversion processing loop
    while end_flag == True:

        #Image acquisition and face detection
        img = c_frame
        img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        face_list = cascade.detectMultiScale(img_gray, minSize=(100, 100))

        #Mark the detected face
        for (x, y, w, h) in face_list:
            color = (0, 0, 225)
            pen_w = 3
            cv2.rectangle(img_gray, (x, y), (x+w, y+h), color, thickness = pen_w)

        #Frame display
        cv2.imshow(ORG_WINDOW_NAME, c_frame)
        cv2.imshow(GAUSSIAN_WINDOW_NAME, img_gray)

        #Exit with Esc key
        key = cv2.waitKey(INTERVAL)
        if key == ESC_KEY:
            break

        #Read next frame
        end_flag, c_frame = cap.read()

    #End processing
    cv2.destroyAllWindows()
    cap.release()

Get the classifier file

Get the haarcascade_frontalface_alt2.xml used for face detection from the following site and download the file to any location </ b>.

(opencvEnv)$ python face_ detect.py