Page 620 - MDP2020-1

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model = Sequential()

model.add(Convolution2D(16, 3, 3, border_mode='same', activation='relu',
input_shape=X_train.shape[1:]))

model.add(MaxPooling2D(pool_size=(2, 2)))

model.add(Dropout(0.25))

model.add(Convolution2D(64, 3, 3, activation='relu'))

model.add(MaxPooling2D(pool_size=(2, 2)))

model.add(Dropout(0.25))

model.add(Convolution2D(64, 3, 3))

model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.25))

model.add(Flatten())
model.add(Dense(256, activation = 'relu'))

model.add(Dropout(0.5))

model.add(Dense(num_classes,activation = 'softmax'))

model.compile(loss='binary_crossentropy',optimizer='Adam',metrics=['accuracy'])

model.fit(X_train, Y_train, batch_size=32, nb_epoch=100)

model.save('/tmp/TT/numpy_data/Gersang.h5') # 학습된 모듈 저장하기

다. 학습된 모듈 테스트
import os, re, glob

import cv2

import numpy as np
import shutil

from numpy import argmax

from keras.models import load_model

categories = ["wildboar", "humans"] #카테고리 불러오기