因此，我尝试了这个教程（11:58分钟处），试图在我的CNN上实现，它包含数据集中10个物种。

我没有遇到加载数据时的错误

DATADIR = "dataset"CATEGORIES = ["Dendrobium_crumenatum","Grammatophyllum_speciosum", "Coelogyne_swaniana",               "Bulbophyllum_purpurascens", "Agrostophyllum_stipulatum",               "Spathoglottis_plicata", "Phalaenopsis_amabilis", "Nabaluia_angustifolia",               "Habenaria_rhodocheila_hance"] 这里是输出示例[![enter image description here][2]][2]

然后是下一部分

training_data = []def create_training_data():    for category in CATEGORIES:        path = os.path.join(DATADIR,category)        class_num = CATEGORIES.index(category)        for img in os.listdir(path):            try:                img_array = cv2.imread(os.path.join(path,img),cv2.IMREAD_GRAYSCALE)                new_array = cv2.resize(img_array, (IMG_SIZE,IMG_SIZE))                training_data.append([new,array, class_num])            except Exception as e:                passcreate_training_data()        

但是当我打印prin(len(training_data))

我得到了这样的输出

0

当我尝试

import randomrandom.shuffle(training_data)for sample in training_data[:10]:    print (sample[1])

它没有显示任何输出。这是否意味着我的训练数据为空？还是因为使用了类别的索引？因为我使用了10个类，而教程中使用了2个类。

回答：

使你的training_data成为全局变量

training_data =[]def create_training_data():    global training_data    for category in CATEGORIES:        path = os.path.join(DATADIR,category)        class_num = CATEGORIES.index(category)        for img in os.listdir(path):            try:                img_array = cv2.imread(os.path.join(path,img),cv2.IMREAD_GRAYSCALE)                new_array = cv2.resize(img_array,(IMG_SIZE, IMG_SIZE))                training_data.append([new_array,class_num])            except Exception as e:                passcreate_training_data()