我正在尝试在 Keras 中微调和保存模型并加载它,但出现此错误:
值错误:您正在尝试将包含 16 层的权重文件加载到具有 0 层的模型中。
我尝试了另一种数字模型我让它保存和加载模式工作没有错误
当我尝试采用 vgg16 时,它给出了错误
我想要加载模型但由于此错误而无法加载。谁能帮忙?
import keras
from keras.models import Sequential,load_model,model_from_json
from keras import backend as K
from keras.layers import Activation,Conv2D,MaxPooling2D,Dropout
from keras.layers.core import Dense,Flatten
from keras.optimizers import Adam
from keras.metrics import categorical_crossentropy
from keras.layers.normalization import BatchNormalization
from keras.layers.convolutional import *
from keras.preprocessing.image import ImageDataGenerator
import matplotlib.pyplot as plt
import itertools
from sklearn.metrics import confusion_matrix
import numpy as np
train_path='dataset/train'
test_path='dataset/test'
valid_path='dataset/valid'
train_batches=ImageDataGenerator()
.flow_from_directory(train_path,batch_size=1,target_size=(224,224),classes=
['dog','cat'])
valid_batches=ImageDataGenerator()
.flow_from_directory(valid_path,batch_size=4,target_size=(224,224),classes=
['dog','cat'])
test_batches=ImageDataGenerator()
.flow_from_directory(test_path,target_size=(224,224),classes=['dog','cat'])
vgg16_model=keras.applications.vgg16.VGG16();
vgg16_model.summary()
type(vgg16_model)
model=Sequential()
for layer in vgg16_model.layers[:-1]:
model.add(layer)
for layer in model.layers:
layer.trainable=False
model.add(Dense(2,activation='softmax'))
model.compile(Adam(lr=.0001),loss='categorical_crossentropy',metrics=
['accuracy'])
model.fit_generator(train_batches,validation_data=valid_batches,epochs=1)
model.save('test.h5')
model.summary()
xx=load_model('test.h5')
最佳答案
我以不同的方式加载模型,四处寻找解决方案,我遇到了同样的问题。现在应用我训练过的模型。最后我使用 VGG16 作为模型并使用我自己训练的 h5 权重,太棒了!
weights_model='C:/Anaconda/weightsnew2.h5' # my already trained
weights .h5
vgg=applications.vgg16.VGG16()
cnn=Sequential()
for capa in vgg.layers:
cnn.add(capa)
cnn.layers.pop()
for layer in cnn.layers:
layer.trainable=False
cnn.add(Dense(2,activation='softmax'))
cnn.load_weights(weights_model)
def predict(file):
x = load_img(file, target_size=(longitud, altura))
x = img_to_array(x)
x = np.expand_dims(x, axis=0)
array = cnn.predict(x)
result = array[0]
respuesta = np.argmax(result)
if respuesta == 0:
print("Gato")
elif respuesta == 1:
print("Perro")
关于python - Keras try save and load model error You are trying to load a weight file containing 16 layers into a model with 0 层数,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/51544666/