将 keras 模型导出到 tflite

Question

我正在尝试结合这两个示例并为我的 android 应用程序创建 tflite 文件。

https://medium.com/nybles/create-your-first-image-recognition-classifier-using-cnn-keras-and-tensorflow-backend-6eaab98d14dd

https://medium.com/@xianbao.qian/convert-keras-model-to-tflite-e2bdf28ee2d2

这是我的代码：

# Part 1 - Building the CNN

# Importing the Keras libraries and packages

from keras.models import Sequential

from keras.layers import Convolution2D

from keras.layers import MaxPooling2D

from keras.layers import Flatten

from keras.layers import Dense

import tensorflow as tf

from keras.models import load_model

# Initialising the CNN

classifier = Sequential()

# Step 1 - Convolution

classifier.add(Convolution2D(32, 3, 3, input_shape = (64, 64, 3), activation = 'relu'))

# Step 2 - Pooling

classifier.add(MaxPooling2D(pool_size = (2, 2)))

# Adding a second convolutional layer

classifier.add(Convolution2D(32, 3, 3, activation = 'relu'))

classifier.add(MaxPooling2D(pool_size = (2, 2)))

# Step 3 - Flattening

classifier.add(Flatten())

# Step 4 - Full connection

classifier.add(Dense(output_dim = 128, activation = 'relu'))

classifier.add(Dense(output_dim = 1, activation = 'sigmoid'))

# Compiling the CNN

classifier.compile(optimizer = 'adam', loss = 'binary_crossentropy', metrics = ['accuracy'])

# Part 2 - Fitting the CNN to the images

from keras.preprocessing.image import ImageDataGenerator

train_datagen = ImageDataGenerator(rescale = 1./255,

                                   shear_range = 0.2,

                                   zoom_range = 0.2,

                                   horizontal_flip = True)

在这一行：

frozen_def = tf.graph_util.convert_variables_to_constants(sess, sess.graph_def, output_names)

我有一个例外：

tensorflow.python.framework.errors_impl.FailedPreconditionError: Attempting to use uninitialized value conv2d_1/bias

[[Node: _retval_conv2d_1/bias_0_0 = _Retval[T=DT_FLOAT, index=0, _device="/job:localhost/replica:0/task:0/device:CPU:0"](conv2d_1/bias)]]

我是机器学习的初学者，完全不知道这个错误是什么:-(

有人可以向我解释什么是错的吗？我所需要的只是处理多个包含许多图片的文件夹，并可以预测新图片与特定文件夹的关系。谢谢你。