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@Juventi, thanks for the code! I have no problems.

There are my graph postprocessing:

python ~/tensorflow/tensorflow/python/tools/freeze_graph.py \
  --input_graph=graph.pb \
  --input_checkpoint=tmp.ckpt \
  --output_graph=frozen_graph.pb \
  --output_node_names=y_pre

python ~/tensorflow/tensorflow/python/tools/optimize_for_inference.py \
  --input frozen_graph.pb \
  --output opt_graph.pb \
  --frozen_graph True \
  --input_names inputs_placeholder \
  --output_names y_pre

And the invocation:

#include <opencv2/opencv.hpp>
#include <opencv2/dnn.hpp>

int main(int argc, char** argv) {
  cv::dnn::Net net = cv::dnn::readNetFromTensorflow("../opt_graph.pb");

  cv::Mat input(32, 32, CV_32FC3);
  net.setInput(cv::dnn::blobFromImage(input));
  net.forward();
  return 0;
}

@Juventi, thanks for the code! I have no problems.

There are my graph postprocessing:

python ~/tensorflow/tensorflow/python/tools/freeze_graph.py \
  --input_graph=graph.pb \
  --input_checkpoint=tmp.ckpt \
  --output_graph=frozen_graph.pb \
  --output_node_names=y_pre

python ~/tensorflow/tensorflow/python/tools/optimize_for_inference.py \
  --input frozen_graph.pb \
  --output opt_graph.pb \
  --frozen_graph True \
  --input_names inputs_placeholder \
  --output_names y_pre

And the invocation:

#include <opencv2/opencv.hpp>
#include <opencv2/dnn.hpp>

int main(int argc, char** argv) {
  cv::dnn::Net net = cv::dnn::readNetFromTensorflow("../opt_graph.pb");

  cv::Mat input(32, 32, CV_32FC3);
  net.setInput(cv::dnn::blobFromImage(input));
  net.forward();
  return 0;
}