python - 为什么当我尝试将 .jpg 文件转换为数组时，Google Colab 会使用这么多 RAM？

Question

我目前正在尝试加载和转换图像以进行训练，但 Colab 在我开始训练之前就在整个过程中使用了所有 RAM。代码块如下：

# 0=Angry, 1=Disgust, 2=Fear, 3=Happy, 4=Sad, 5=Surprise, 6=Neutral
classes = ["0", "1", "2", "3", "4", "5", "6"] # list of classes

IMG_SIZE = 224 # ImageNet => 224 x 224

# Read all images and convert them into an array
trainingData = []

def create_training_data():
    for category in classes:
        path = os.path.join(dataDirectory, category)
        class_num = classes.index(category)
        for img in os.listdir(path):
            try:
                img_array = cv2.imread(os.path.join(path, img))
                new_array = cv2.resize(img_array, (IMG_SIZE, IMG_SIZE))
                trainingData.append([new_array, class_num])
            except Exception as e:
                pass

create_training_data()

random.shuffle(trainingData)

features = []
labels = []

for feature, label in trainingData:
    features.append(feature)
    labels.append(label)

features = np.array(features).reshape(-1, IMG_SIZE, IMG_SIZE, 3) # Convert to 4 Dimension

features = features/255.0 # Normalization before training

labels = np.array(labels)

我正在使用 Colab Pro。任何可以解决此问题的帮助或建议将不胜感激！