cascade.py

import cv2
import os
import numpy as np

CASE_PATH=os.path.join(os.getcwd(),"haarcascade_frontalface_default.xml")
face_size = 64

def crop_face( imgarray, section, margin=40, size=64):
        """
        :param imgarray: full image
        :param section: face detected area (x, y, w, h)
        :param margin: add some margin to the face detected area to include a full head
        :param size: the result image resolution with be (size x size)
        :return: resized image in numpy array with shape (size x size x 3)
        """
        img_h, img_w, _ = imgarray.shape
        if section is None:
            section = [0, 0, img_w, img_h]
        (x, y, w, h) = section
        margin = int(min(w,h) * margin / 100)
        x_a = x - margin
        y_a = y - margin
        x_b = x + w + margin
        y_b = y + h + margin
        if x_a < 0:
            x_b = min(x_b - x_a, img_w-1)
            x_a = 0
        if y_a < 0:
            y_b = min(y_b - y_a, img_h-1)
            y_a = 0
        if x_b > img_w:
            x_a = max(x_a - (x_b - img_w), 0)
            x_b = img_w
        if y_b > img_h:
            y_a = max(y_a - (y_b - img_h), 0)
            y_b = img_h
        cropped = imgarray[y_a: y_b, x_a: x_b]
        resized_img = cv2.resize(cropped, (size, size), interpolation=cv2.INTER_AREA)
        resized_img = np.array(resized_img)
        return resized_img, (x_a, y_a, x_b - x_a, y_b - y_a)





def detect_face(image):
    xmin = ymin = xmax = ymax = 0
    frame = np.asarray(image)
    face_cascade = cv2.CascadeClassifier(CASE_PATH)
    gray_image = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(gray_image, scaleFactor=1.1, minNeighbors=5,minSize=(face_size, face_size), flags=cv2.CASCADE_SCALE_IMAGE)
    face_imgs = np.empty((len(faces), face_size, face_size, 3))
    for i, face in enumerate(faces):
        face_img, cropped = crop_face(frame, face, margin=40, size=face_size)
        (x, y, w, h) = cropped
        if i == 0:
            xmin = x
            ymin = y
            xmax = x+w
            ymax = y+h
    
    return xmin , ymin , xmax , ymax