以下Pyhthon架构库: EfficientNet & DenseNet 169 EfficientNet导入问题
以下Pyhthon架构库: EfficientNet & DenseNet 169 EfficientNet导入问题
提问于 2020-01-17 19:49:30
我试图使用以下深度学习CNN架构: DenseNet169 & EfficientNet与传输学习。我通过PyCharm安装了以下库，并调用了以下导入库：
from keras.models import Model
from keras.layers import Dense, GlobalAveragePooling2D
from keras.preprocessing.image import ImageDataGenerator
from keras.optimizers import SGD, RMSprop
from keras.callbacks import ModelCheckpoint
from keras.callbacks import History
from keras import applications
import keras_applications
#Transfer Learning Networks Models
# 5 - DensNet family
import densenet
from keras.applications.densenet.DenseNet121 import DenseNet121
from keras.applications.densenet.DenseNet169 import DenseNet169
from keras.applications.densenet.DenseNet201 import DenseNet201
from keras_applications.densenet.DenseNet121 import DenseNet121
from keras_applications.densenet.DenseNet169 import DenseNet169
from keras_applications.densenet.DenseNet201 import DenseNet201
# 6 - EfficientNet Alone
import efficientnet.keras as efn
# 6 - EfficientNet family
from efficientnet import EfficientNetB0
from efficientnet import EfficientNetB1
from efficientnet import EfficientNetB2
from efficientnet import EfficientNetB3
from efficientnet import EfficientNetB4
from efficientnet import EfficientNetB5
from efficientnet import EfficientNetB6
from efficientnet import EfficientNetB7我称之为以下架构：
下载预训练的模型和权重
elif model_tl_name == 'DenseNet169':
print("base_model = DenseNet169")
base_model = densenet.DenseNetImageNet169(include_top=True, input_shape=(224, 224, 3), input_tensor=None, pooling=None, classes=1000)
#base_model = DenseNet169(include_top=True, weights='imagenet', input_tensor=None, input_shape=None, pooling=None, classes=1000)
elif model_tl_name == 'EfficientNetB5':
print("base_model = EfficientNetB5")
#base_model = EfficientNetB5(include_top=False, weights='imagenet')
base_model = efn.EfficientNetB5(include_top=False, weights='imagenet')
# model = EfficientNetB3(weights='imagenet', include_top=False, input_shape=(img_size, img_size, 3))
# Changing last layer to adapt to two classes
model = add_new_last_layer(base_model, nb_classes)但是，我总是收到以下错误消息：
对于DenseNet169 :掩码= node.output_maskstensor_index AttributeError：‘节点’对象没有属性'output_masks‘
对于从"C:\Users\QTR7701\AppData\Local\Programs\Python\Python37\lib\site-packages\efficientnet\initializers.py"，keras.applications导入EfficientNetB5文件的第44行，在call返回tf.random_normal( AttributeError:模块'tensorflow‘)中没有属性'random_normal’
如果有人能帮我的话。
回答 1
Stack Overflow用户
发布于 2021-01-07 09:46:45
在PyPharm中，转到设置->项目解释器，并尝试加载tensorflow库。之后再试->
from tensorflow.keras.applications.efficientnet import EfficientNetB0, EfficientNetB5
mm = EfficientNetB0(include_top=True, weights=None, input_tensor=None, input_shape=None, pooling=None, classes=2, classifier_activation="softmax")
mm.summary()页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/59793997
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