Script for detecting faces with argparse options

detect_faces.py

#!python3
import sys
import os
import numpy as np
import cv2
import argparse

METHOD = "haarcascade_frontalface_default.xml"
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + METHOD)

if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Script for detecting and counting faces in the picture.")
    parser.add_argument("file", help="Image file location.")
    parser.add_argument("-s", "--scale", help="Scale up the image. Helps finding smaller faces.", type=int, default=1)
    args = parser.parse_args()

    image_location = args.file
    assert(os.path.isfile(image_location))

    image = cv2.imread(image_location)
    scale = args.scale
    dim = (image.shape[1] * scale, image.shape[0] * scale)
    image_procured = cv2.resize(image, dim, interpolation=cv2.INTER_AREA)

    # grayImage = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

    faces = face_cascade.detectMultiScale(image_procured)

    if len(faces) == 0:
        print("No faces found")
        exit(1)

    else:
        print(f"Number of faces detected: {faces.shape[0]}")

        for (x_, y_, w_, h_) in faces:
            (x, y, w, h) = (x_ // scale, y_ // scale, w_ // scale, h_ // scale)
            cv2.rectangle(image, (x, y), (x+w, y+h), (0, 255, 0), 1)

        cv2.imshow("Image with faces", image)
        cv2.waitKey(0)
        cv2.destroyAllWindows()