Keras -> TensorFlow -> OpenCV/dnn

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I try to use a Tensorflow model (created with Keras) in OpenCV/dnn (3.3.0). But I get the following error message:

OpenCV Error: Unspecified error (Unknown layer type Shape in op flatten_1/Shape)

This is the python code to create and export the model.

import os
import sys
import shutil
import subprocess

import numpy as np

import tensorflow as tf

from keras.models import Model
from keras import backend as K

from keras.layers import Dense, Input, Conv2D, Flatten, MaxPooling2D, BatchNormalization


sess = tf.Session()
K.set_session(sess)

# create model
inputs = Input(shape=(64, 64, 3), name='input_layer')
x = Conv2D(8, (3, 3), padding='same', activation='relu')(inputs)
x = MaxPooling2D((2,2))(x)
x = Conv2D(16, (3, 3), padding='same', activation='relu')(x)
x = MaxPooling2D((2,2))(x)
x = Flatten()(x)
x = Dense(64, activation='sigmoid')(x)
x = BatchNormalization()(x)
x = Dense(32, activation='sigmoid')(x)
predictions = Dense(10, activation='softmax', name='output_layer')(x)
model = Model(inputs=inputs, outputs=predictions)
model.compile(optimizer='rmsprop',
              loss='categorical_crossentropy',
              metrics=['accuracy'])

# train model
data = np.random.random((100, 64, 64, 3))
labels = np.random.randint(2, size=(100, 10))
model.fit(data, labels, epochs=10, batch_size=32)

# create temp directory for export
temp_export_dir = './temp_export/'
if os.path.exists(temp_export_dir):
    shutil.rmtree(temp_export_dir)
os.makedirs(temp_export_dir)

# export model to temp directory
with sess.graph.as_default():
    saver = tf.train.Saver()
    saver.save(sess, temp_export_dir + 'model.ckpt')
    tf.train.write_graph(sess.graph.as_graph_def(), temp_export_dir, "graph.pbtxt")

# freeze graph and optimize for inference
_ = subprocess.call("python freeze_graph.py --input_graph=" + temp_export_dir + "graph.pbtxt --input_checkpoint=" + temp_export_dir + "model.ckpt --output_graph=" + temp_export_dir + "frozen_graph.pb --output_node_names=output_layer/Softmax")
_ = subprocess.call("python optimize_for_inference.py --input=" + temp_export_dir + "frozen_graph.pb --output=model.pb --frozen_graph=True --input_names=input_layer --output_names=output_layer/Softmax")

# remove temp directory
#shutil.rmtree(temp_export_dir)

The two external scripts freeze_graph.py and optimize_for_inference.py come from tensorflow/python/tools

And this is the C++ code to load the model:

#include <opencv2/dnn.hpp>
int main()
{
    cv::dnn::Net net = cv::dnn::readNetFromTensorflow( "model.pb" );
}

I uploaded the file model.pbhere: http://daiw.de/share/opencv_question_...

Am I doing something wrong or can OpenCV/dnn simply not import such a model?