from tensorflow.keras.applications.inception_v3 import InceptionV3

input = Input(shape=(224, 224, 3))
base_model = InceptionV3(weights='imagenet', include_top=False, input_tensor=input, pooling='max')

x = base_model.output
x = Dropout(rate=0.25)(x)
x = Dense(64, activation='relu')(x)
x = Dense(256, activation='relu')(x)
x = Dense(64, activation='relu')(x)
x = Dense(32, activation='relu')(x)
x = Dense(8, activation='relu')(x)
output = Dense(4, activation='softmax')(x)

model = Model(inputs=base_model.input, outputs=output)
model.compile(loss='categorical_crossentropy', optimizer=Adam(lr=0.001), metrics=['acc'])

import cv2
import glob

# haarcascade 불러오기
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')

images = glob.glob('images\*')
for image in images:
    # 이미지 불러오기
    img = cv2.imread(image)
    img = cv2.resize(img, dsize=(0, 0), fx=0.3, fy=0.3, interpolation=cv2.INTER_AREA)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    # 얼굴 찾기
    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
    for (x, y, w, h) in faces:
        img_x1 = x
        img_x2 = x + w
        img_y1 = y
        img_y2 = y + h

    img = img[img_y1:img_y2, img_x1:img_x2]

    try:
        print(f'face/{image}')
        cv2.imwrite(f'face/{image}', img)
    except:
        pass

import cv2
import glob

# haarcascade 불러오기
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')

images = glob.glob('images/*')
print("images =", end=""), print(images)

result_list = []

for i in images:
    temp = i.replace("\\", "/")
    result_list.append(temp)

print("result_list = ", end=""), print(result_list)

# 이미지 불러오기
for image in result_list:

    if "jpg" in image:
        print("image = ", end=""), print(image)

        ori_img = cv2.imread(image)
        ori_img = cv2.resize(ori_img, dsize=(0, 0), fx=0.4, fy=0.4, interpolation=cv2.INTER_AREA)
        gray = cv2.cvtColor(ori_img, cv2.COLOR_BGR2GRAY)

        # 얼굴 찾기
        faces = face_cascade.detectMultiScale(gray, 1.2, minSize=(75,75))
        print("faces =", end=""), print(faces)

        cnt = 0
        for (x, y, w, h) in faces:
            img_x1 = x
            img_x2 = x + w
            img_y1 = y
            img_y2 = y + h

            img = ori_img[img_y1:img_y2, img_x1:img_x2]

            image_file_name = image.split('.')
            print("image_file_name =", end=""), print(image_file_name)
            file_name = image_file_name[0]
            extension = image_file_name[1]

            file_name += str(cnt)

            filename = 'face/images/' + file_name + '.' + extension
            print("filename =", end=""), print(filename)
            cv2.imwrite(filename, img)

            cnt += 1