我是深度学习和 TensorFlow/Keras 的新手，所以我无法理解为什么我在尝试拟合模型以将图像分类为“狗”或“猫”时抛出错误。第一个代码块涉及创建和保存模型（使用 pickle），第二个代码块是训练实际卷积网络的部分。下载图像数据库，保存到文件目录，编写模型训练分类器。代码如下：import numpy as npimport matplotlib.pyplot as pltimport osimport cv2DATADIR = "Pictures\\kagglecatsanddogs_3367a\\PetImages" #Workspace directory changed for postingCATEGORIES = ["Dog", "Cat"]#Iterate between all photos of dogs and catsfor category in CATEGORIES:    path = os.path.join(DATADIR, category) #path to cats or dogs dir    for img in os.listdir(path):        img_array = cv2.imread(os.path.join(path, img), cv2.IMREAD_GRAYSCALE) #Converts to grayscale, does not need color in this specific instance)        plt.imshow(img_array, cmap = "gray")        break    break#Print image dimensionsprint(img_array.shape)#All the images are different-shaped photos, so they must be normalized#Everything must be made the same shape#Decide on the image size you want to go withIMG_SIZE = 180new_array = cv2.resize(img_array, (IMG_SIZE, IMG_SIZE))training_data = []def create_training_data(): #With goal of iterating through everything and building the dataset    for category in CATEGORIES:        path = os.path.join(DATADIR, category) #path to cats or dogs dir        class_num = CATEGORIES.index(category)        for img in os.listdir(path):            try:                img_array = cv2.imread(os.path.join(path, img), cv2.IMREAD_GRAYSCALE) #Converts to grayscale, does not need color in this specific instance)                new_array = cv2.resize(img_array, (IMG_SIZE, IMG_SIZE))                training_data.append([new_array, class_num])            except Exception as e:                pass