小编Ali*_*ini的帖子

因此，我根据人类的存在为我的图像提供了“0”和“1”的标签。当我传递所有图像并尝试训练我的模型时。我收到内存错误。

    import warnings
    warnings.filterwarnings('ignore')
    import tensorflow as to
    import tensorflow.keras
    from tensorflow.keras.preprocessing.image import ImageDataGenerator
    from tensorflow.keras.callbacks import ReduceLROnPlateau, CSVLogger, EarlyStopping
    from tensorflow.keras.models import Model
    from tensorflow.keras.layers import GlobalAveragePooling2D, Dense
    from tensorflow.keras.applications.resnet50 import ResNet50


    from PIL import Image
    import os
    import numpy as np
    train_x=[]
    train_y=[]
    for path in os.listdir('C:\\Users\\maini_\\Desktop\\TestAndTrain\\in\\train'):
        img = Image.open('C:\\Users\\maini_\\Desktop\\TestAndTrain\\in\\train\\'+path)
        train_x.append(np.array(img))
        train_y.append(1)
        img.close()
    for path in os.listdir('C:\\Users\\maini_\\Desktop\\TestAndTrain\\notin\\train'):
        img = Image.open('C:\\Users\\maini_\\Desktop\\TestAndTrain\\notin\\train\\'+path)
        train_x.append(np.array(img))
        train_y.append(0)
        img.close()
    print("done" )

   train_x = np.array(train_x)
   train_x = train_x.astype(np.float32)
   train_x /= 255.0

   train_y = np.array(train_y)

我正在与 …