Hi there! I just got a Jetson Nano, and flashed it by using the jetson-nano-jp451-sd-card-image file and Etcher. I need to install MxNet and GluonCV, so I did the following: ATTEMPT #1 I tried installing MXNet by using the compiled package, as described here Installed dependencies sudo apt-ge…

Hi, jetson-inference uses TensorRT as the inference engine which has optimized for the Jetson platform. For Jetson, we always recommend converting the model into TensorRT for saving resources and better performance. If you are using an MXNet model, you can first try to export the model into ONNX …

I tried following the procedure you linked, but I got the error CMakeFiles/Makefile2:889: recipe for target 'CMakeFiles/mxnet_static.dir/all' failed make[1]: *** [CMakeFiles/mxnet_static.dir/all] Error 2 Makefile:140: recipe for target 'all' failed make: *** [all] Error 2 + pushd . ~ ~ + PYTHON_DIR…

I noticed now there might be a typo at: -DCMAKE_CXX_FLAGS=-I/usr/local/cuda/targets/aarch64-linux/inlude \ I assume it should be ‘include’?

It seems the mxnet installation was successful after fixing the typo I mentioned above. However, I still have 2 issues: I tried importing mxnet and running a few simple tests, and the memory consumption when creating arrays using the gpu context seems too high. Specifically, I tried something ve…

Hi, Since Nano’s GPU is limited, the slowness may cause by the shortage of memory. Could you try it on a flash reboot environment to see if any difference? Thanks.

Hi! Are there any instructions on how to cross-compile it? I’d be happy to flash the card and try as many times as necessary, but on the Nano the compilation using the autobuild_mxnet.sh takes something between 6-8 hours :( EDIT: Even better, this is the script I’m using to run object detection w…

Hi, Have you tried to maximize the device performance first? $ sudo nvpmodel -m 0 $ sudo jetson_clocks We are going to test your script internally. Will share the data in our environment with you later. However, since OpenCV uses CPU for image IO. It’s expected to have a slower pipeline. Than…

I seem to understand I’m approaching this whole thing the wrong way. So far, I’ve been simply trying to install the deep learning libraries I generally use (MXNet, GluonCV, Tensorflow) on the Jetson Nano, and to run the code I have as it is (for example, like you pointed out, by using OpenCV for IO…

Problem trying to install MXNet and GluonCV on Jetson Nano

Robotics & Edge Computing Jetson Systems Jetson Nano

AastaLLL June 21, 2021, 2:55am 3

Hi,

The prebuilt package is for JetPack 4.3.
Since your environment is JetPack4.5.1, please build it from source.

To build MXNet, please refer to below comment:

And it’s recommended to the job on a clear environment.

Thanks.

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Problem trying to install MXNet and GluonCV on Jetson Nano

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