Page 619 - MDP2020-1

················································································ 명장양성프로젝트 【MDP】 과제발표회 자료집 Ⅰ | 613

for idex, categorie in enumerate(categories):

label = [0 for i in range(num_classes)]
label[idex] = 1

image_dir = groups_folder_path + categorie + '/'

for top, dir, f in os.walk(image_dir):

for filename in f:

print(image_dir+filename)

img = cv2.imread(image_dir+filename)
img = cv2.resize(img, None, fx=image_w/img.shape[1], fy=image_h/img.shap
e[0])

X.append(img/256)

Y.append(label)

X = np.array(X)

Y = np.array(Y)

X_train, X_test, Y_train, Y_test = train_test_split(X,Y) #train,test 파일 나눔

xy = (X_train, X_test, Y_train, Y_test)

np.save("/tmp/TT/numpy_data/img_data.npy", xy) #npy 파일 만들기

나. CNN

from keras.models import Sequential
from keras.layers import Dropout, Activation, Dense

from keras.layers import Flatten, Convolution2D, MaxPooling2D

from keras.models import load_model
import cv2

X_train, X_test, Y_train, Y_test = np.load('/tmp/TT/numpy_data/img_data.npy',allow_pickle
=True) #npy 파일 로드

model = Sequential()