对于猫和狗图像的二元分类,我的目录结构是train_dir/cats和train_dir/dogs。
train_datagen = ImageDataGenerator(rescale=1/255)
train_generator = train_datagen.flow_from_directory(
'/train_dir/', # This is the source directory for training images
target_size=(300, 300), # All images will be resized to 150x150
batch_size=128,
# Since we use binary_crossentropy loss, we need binary labels
class_mode='binary')
model.predict(images, batch_size=10)
如何知道model.predict((返回的概率属于哪一类?猫=1还是狗=1?我在某个地方读到,对于多类分类,返回的概率是按类名的字母顺序排列的。但我认为二元分类并非如此。
您需要访问与每个ImageDataGenerator
类关联的class_indices
变量。只需打印train_generator.class_indices
即可查看哪个类被赋予了哪个标签。