我试过使用 (foo, foo1) = tf.keras.preprocessing.image_dataset_from_directory(dataDirectory,etc),但我得到 (trainData, trainLabels) = tf.keras.preprocessing.image_dataset_from_directory( ValueError:toomanyvaluestounpack(expected2 )如果我尝试将其作为一个变量返回,然后将其拆分为: train = tf.keras....
image_size = (180, 180) batch_size = 32 train_ds = tf.keras.preprocessing.image_dataset_from_directory( "PetImages", validation_split=0.2, subset="training", seed=1337, image_size=image_size, batch_size=batch_size, ) val_ds = tf.keras.preprocessing.image_dataset_from_directory( "PetIm...
dataset = image_dataset_from_directory( directory, # 图像数据集的根目录 labels='inferred', # 类别标签的获取方式,'inferred'表示从子目录名称中获取 label_mode='int', # 类别标签的数据类型,'int'表示整数类型 image_size=(224, 224), # 图像的尺寸 batch_size=32, # 批量大小 shuffle=True, #...
DatasetReference DataSource DataSourceReference DataSourceTarget DataSourceView DataTable DateTimeAxis DateTimePicker DebugCheckedTests DebugHistorySeekToFrame DebugInteractiveWindow DebugSelection DebugTemplate DebugXSLT DecisionNode DecisionTree 宣告 DeclarativeCatalogPart DecreaseDecimals DecreaseFontSize DecreaseHorizon...
image_dataset_from_directory(directory,labels ="inferred",label_mode ="int",class_names =NULL,color_mode ="rgb",batch_size =32,image_size =c(256,256),shuffle =TRUE,seed =NULL,validation_split =NULL,subset =NULL,interpolation ="bilinear",follow_links =FALSE,crop_to_aspect_ratio =FALSE,....
tf.keras.preprocessing.image_dataset_from_directory(...) 需要tf-nightly或者TF2.4的支持。输出: Found1182filesbelongingto6classes.['freshapples','freshbanana','freshoranges','rottenapples','rottenbanana','rottenoranges'] 让我们观察一下数据集里的样本: ...
记录如下。 原理简介 通过查看源代码，发现Keras调用了model.evaluate_generator验证数据，该函 ...
(directory=filepath,validation_split=0.2,subset="training",labels='inferred',seed=100,label_mode='categorical',batch_size=32,image_size=(75,35))validation_ds=tf.keras.preprocessing.image_dataset_from_directory(directory=filepath,validation_split=0.2,subset='validation',labels='inferred',seed=100,...
程序开发在我windows 本机是可以跑的, 为 conda 环境, tensorflow 2.10 , 运行程序为 linux debain 10 ,是 香橙派 orangepi 4 lts , tensorflow 2.4 , 需要修改 tensorflow 源码 nano ~/.local/lib/python3.7…