小编pur*_*ual的帖子

我有一个自定义文件，其中包含我所有图像的路径及其标签，这些文件的加载方式如下：

MyIndex=pd.read_table('./MySet.txt')

MyIndex具有两个感兴趣的列ImagePath和ClassName

接下来，我进行一些训练测试拆分并将输出标签编码为：

images=[]
for index, row in MyIndex.iterrows():
    img_path=basePath+row['ImageName']
    img = image.load_img(img_path, target_size=(299, 299))
    img_path=None
    img_data = image.img_to_array(img)
    img=None
    images.append(img_data)
    img_data=None


images[0].shape

Classes=Sample['ClassName']
OutputClasses=Classes.unique().tolist()

labels=Sample['ClassName']
images=np.array(images, dtype="float") / 255.0
(trainX, testX, trainY, testY) = train_test_split(images,labels, test_size=0.10, random_state=42)
trainX, valX, trainY, valY = train_test_split(trainX, trainY, test_size=0.10, random_state=41)

images=None
labels=None

encoder = LabelEncoder()
encoder=encoder.fit(OutputClasses)
encoded_Y = encoder.transform(trainY)
# convert integers to dummy variables (i.e. one hot encoded)
trainY = to_categorical(encoded_Y, num_classes=len(OutputClasses))

encoded_Y = encoder.transform(valY)
# convert integers …