Python Keras - 如何输入自定义图像？

Question

    from keras import *
import os
import numpy as np
from keras.models import Sequential
from keras.layers import Activation, Dropout, Flatten, Dense
from keras.preprocessing.image import ImageDataGenerator
from keras.layers import Convolution2D, MaxPooling2D, ZeroPadding2D
from keras import optimizers

# Collecting data:
img_width, img_height = 150, 150
training_data_dir = "train"
testing_data_dir = "test"
batch_size = 16

# prepare data augmentation configuration
train_datagen = ImageDataGenerator(
    rescale=1. / 255,
    shear_range=0.2,
    zoom_range=0.2,
    horizontal_flip=True)

test_datagen = ImageDataGenerator(rescale=1. / 255)

train_generator = train_datagen.flow_from_directory(
    training_data_dir,
    target_size=(img_height, img_width),
    batch_size=batch_size,
    class_mode='binary')

validation_generator = test_datagen.flow_from_directory(
    testing_data_dir,
    target_size=(img_height, img_width),
    batch_size=batch_size,
    class_mode='binary')

# Building model:
model = Sequential()
model.add(Convolution2D(32, (3, 3), input_shape=(img_width, img_height,3)))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))

model.add(Convolution2D(32, (3, 3)))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))

model.add(Convolution2D(64, (3, 3)))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))

model.add(Flatten())
model.add(Dense(64))
model.add(Activation('relu'))
model.add(Dropout(0.5))
model.add(Dense(1))
model.add(Activation('sigmoid'))

model.compile(loss="binary_crossentropy",
              optimizer="rmsprop",
              metrics=["accuracy"])

#  Training model:
nb_epoch = 1
nb_train_samples = 2048
nb_validation_samples = 832

model.fit_generator(
        train_generator,
        samples_per_epoch=nb_train_samples,
        epochs=nb_epoch,
        validation_data=validation_generator,
        validation_steps=nb_validation_samples,
        steps_per_epoch=64)

我的代码在这里创建了一个神经网络，用于根据训练过的图片进行图像分类，我在整个互联网上进行了搜索，但我无法理解的一件事是如何输入我自己的图像文件来测试网络和让它打印输出。例如，如果网络用于对狗和猫进行分类，我不确定如何对我输入狗或猫的 jpg/png 文件的位以及输出它是哪个类的程序进行编码。请帮忙？

Answer 1

您调用模型的predict 方法。 https://keras.io/models/model/#predict