How to use this package with Jetson-Nano-Ubuntu-20-image about tensorflow_lite_segmentation_jetson-nano HOT 3 CLOSED

@srevandro ,

I've checked one and another.

• Best you install the TensorFlow Lite framework according to our guide on your Ubuntu 20 Jetson Nano.
• Also the flatbuffers.
• Install Code::Blocks as the project hasn't a CMake.txt file (yet). sudo apt-get install codeblocks
• Download the example. git clone https://github.com/Qengineering/TensorFlow_Lite_Segmentation_Jetson-Nano.git
• Make sure you have the downloaded TensorFlow directory renamed tensorflow. Otherwise you get missing header errors.
• Remove the /home/jetson/tensorflow/bazel-bin/tensorflow/lite/delegates/gpu/libtensorflowlite_gpu_delegate.so from the linkage, as we don't use the delegates. It can be done with an text editor in the TestUnet.cbp file before opening the project.
  On my machine it compiles and played the video.

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• missing

@Qengineering

Thanks for your reply.

I have done everything you told me. But, the only problem that I have doing this for Ubuntu 18.04/20.04, is the following message in Code:Blocks build messages:

File: ld
Message: cannot find -ltensorflow-lite / error: ld returned 1 exit status.

I have installed the tensorflow in the following directory:
/home/jetson/evandro/app/tensorflow

Do you have any idea how to solve this problem? I have seen some issues on Google, but I am not pretty sure it should work on Jetson Nano.

Thanks again for all your help.

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@Qengineering

I found the problem. In the Properties->Project Build Options->linker settings->Link libraries, you have inserted the libs directly:

• libtensorflow-lite.a
• libflatbuffers.a

I just found these 2 libs in the tensorflow directory and inserted the full path to them:
/home/jetson/evandro/app/tensorflow/tensorflow/lite/tools/make/gen/linux_aarch64/lib/libtensorflow-lite.a
/home/jetson/evandro/app/tensorflow/tensorflow/lite/tools/make/downloads/flatbuffers/build/libflatbuffers.a

YOU ARE THE BEST, MAN! Really thank you for all the support.

After experimentation with this Segmentation algorithm, I will move forward with the others algorithms on your GitHub.

Thanks.

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