AttributeError: 'function' object has no attribute 'predict' while using Alexnet in Keras
AttributeError: 'function' object has no attribute 'predict' while using Alexnet in Keras
我需要使用 Alexnet 模型进行图像分类任务。我从这个 source 中获取了架构实现。我想直接应用具有 imagenet 权重的模型(不需要微调)并获得 imageNet 数据集的一些预测。这是代码:
def alexnet_model(img_shape=(224, 224, 3), n_classes=1000, l2_reg=0.,
weights='/content/drive/My Drive/cbir/models_cnn/alexnet_weights.hdf'):
# Initialize model
alexnet = Sequential()
# Layer 1
alexnet.add(Conv2D(96, (11, 11), input_shape=img_shape,
padding='same', kernel_regularizer=l2(l2_reg)))
alexnet.add(BatchNormalization())
alexnet.add(Activation('relu'))
alexnet.add(MaxPooling2D(pool_size=(2, 2)))
# Layer 2
alexnet.add(Conv2D(256, (5, 5), padding='same'))
alexnet.add(BatchNormalization())
alexnet.add(Activation('relu'))
alexnet.add(MaxPooling2D(pool_size=(2, 2)))
# Layer 3
alexnet.add(ZeroPadding2D((1, 1)))
alexnet.add(Conv2D(512, (3, 3), padding='same'))
alexnet.add(BatchNormalization())
alexnet.add(Activation('relu'))
alexnet.add(MaxPooling2D(pool_size=(2, 2)))
# Layer 4
alexnet.add(ZeroPadding2D((1, 1)))
alexnet.add(Conv2D(1024, (3, 3), padding='same'))
alexnet.add(BatchNormalization())
alexnet.add(Activation('relu'))
# Layer 5
alexnet.add(ZeroPadding2D((1, 1)))
alexnet.add(Conv2D(1024, (3, 3), padding='same'))
alexnet.add(BatchNormalization())
alexnet.add(Activation('relu'))
alexnet.add(MaxPooling2D(pool_size=(2, 2)))
# Layer 6
alexnet.add(Flatten())
alexnet.add(Dense(3072))
alexnet.add(BatchNormalization())
alexnet.add(Activation('relu'))
alexnet.add(Dropout(0.5))
# Layer 7
alexnet.add(Dense(4096))
alexnet.add(BatchNormalization())
alexnet.add(Activation('relu'))
alexnet.add(Dropout(0.5))
# Layer 8
alexnet.add(Dense(n_classes))
alexnet.add(BatchNormalization())
alexnet.add(Activation('softmax'))
if weights is not None:
alexnet.load_weights(weights)
return alexnet.compile()
之后,我运行:
model = alexnet_model
target_size =(224,224)
img = load_img(imagePath, target_size=target_size)
img = img_to_array(img)
img = img.reshape((1, img.shape[0], img.shape[1], img.shape[2]))
img = preprocess_input(img)
y=model.predict(img)[0]
我收到这个错误:
AttributeError: 'function' object has no attribute 'predict'
您没有打电话给 alexnet_model
。
做
model = alexnet_model()
相反。
我需要使用 Alexnet 模型进行图像分类任务。我从这个 source 中获取了架构实现。我想直接应用具有 imagenet 权重的模型(不需要微调)并获得 imageNet 数据集的一些预测。这是代码:
def alexnet_model(img_shape=(224, 224, 3), n_classes=1000, l2_reg=0.,
weights='/content/drive/My Drive/cbir/models_cnn/alexnet_weights.hdf'):
# Initialize model
alexnet = Sequential()
# Layer 1
alexnet.add(Conv2D(96, (11, 11), input_shape=img_shape,
padding='same', kernel_regularizer=l2(l2_reg)))
alexnet.add(BatchNormalization())
alexnet.add(Activation('relu'))
alexnet.add(MaxPooling2D(pool_size=(2, 2)))
# Layer 2
alexnet.add(Conv2D(256, (5, 5), padding='same'))
alexnet.add(BatchNormalization())
alexnet.add(Activation('relu'))
alexnet.add(MaxPooling2D(pool_size=(2, 2)))
# Layer 3
alexnet.add(ZeroPadding2D((1, 1)))
alexnet.add(Conv2D(512, (3, 3), padding='same'))
alexnet.add(BatchNormalization())
alexnet.add(Activation('relu'))
alexnet.add(MaxPooling2D(pool_size=(2, 2)))
# Layer 4
alexnet.add(ZeroPadding2D((1, 1)))
alexnet.add(Conv2D(1024, (3, 3), padding='same'))
alexnet.add(BatchNormalization())
alexnet.add(Activation('relu'))
# Layer 5
alexnet.add(ZeroPadding2D((1, 1)))
alexnet.add(Conv2D(1024, (3, 3), padding='same'))
alexnet.add(BatchNormalization())
alexnet.add(Activation('relu'))
alexnet.add(MaxPooling2D(pool_size=(2, 2)))
# Layer 6
alexnet.add(Flatten())
alexnet.add(Dense(3072))
alexnet.add(BatchNormalization())
alexnet.add(Activation('relu'))
alexnet.add(Dropout(0.5))
# Layer 7
alexnet.add(Dense(4096))
alexnet.add(BatchNormalization())
alexnet.add(Activation('relu'))
alexnet.add(Dropout(0.5))
# Layer 8
alexnet.add(Dense(n_classes))
alexnet.add(BatchNormalization())
alexnet.add(Activation('softmax'))
if weights is not None:
alexnet.load_weights(weights)
return alexnet.compile()
之后,我运行:
model = alexnet_model
target_size =(224,224)
img = load_img(imagePath, target_size=target_size)
img = img_to_array(img)
img = img.reshape((1, img.shape[0], img.shape[1], img.shape[2]))
img = preprocess_input(img)
y=model.predict(img)[0]
我收到这个错误:
AttributeError: 'function' object has no attribute 'predict'
您没有打电话给 alexnet_model
。
做
model = alexnet_model()
相反。