Kerasで花画像の名前を当てる~検出編~[Keras][CNN][深層学習][Python]

9月 24, 20187月 27, 2020

vastee.hatenablog.com

の続き

今回は学習したモデルを使って花の名前を当てるプログラムを作成する．

import numpy as np
from keras.preprocessing.image import load_img, img_to_array
from keras.applications.vgg16 import VGG16, preprocess_input
from keras.models import Sequential, Model
from keras.layers import Input, Dense, Dropout, Activation, Flatten
from keras.optimizers import SGD
classes = ['daisy', 'dandelion', 'roses', 'sunflowers', 'tulips']
nb_classes = len(classes)
img_rows, img_cols = 224, 224
def
build_model() :
input_tensor = Input(shape=(img_rows, img_cols, 3))
vgg16 = VGG16(include_top=False, weights='imagenet', input_tensor=input_tensor)
_model = Sequential()
_model.add(Flatten(input_shape=vgg16.output_shape[1:]))
_model.add(Dense(256, activation='relu'))
_model.add(Dropout(0.5))
_model.add(Dense(nb_classes, activation='softmax'))
model = Model(inputs=vgg16.input, outputs=_model(vgg16.output))
for layer in model.layers[:15]:
layer.trainable = False
model.compile(loss='categorical_crossentropy',
optimizer=SGD(lr=1e-4, momentum=0.9), metrics=['accuracy'])
return model
if __name__ == "__main__":
model = build_model()
# 学習時に使ったモデルを使用
model.load_weights("./flower-model.hdf5")
filename = "./daisy.jpg"
# kerasに画像を読み込む関数がある
img = load_img(filename, target_size=(img_rows, img_cols))
x = img_to_array(img)
x = np.expand_dims(x, axis=0)
predict = model.predict(preprocess_input(x))
for pre in predict:
y = pre.argmax()
print("Name: ", classes[y])