Hi,
I get :
CMake Error at CMakeLists.txt:118 (add_subdirectory):
The source directory
/home/m/jetson-inference/examples
does not contain a CMakeLists.txt file.
also:
qt4 dependency - takes forever, lots of diskspace and unneeded for headless
doxygen is missing from the sudo apt install
instead of making a UI for selecting the models we want to downloads a simple text list would do really… we can edit it and remove the models we don’t need/want
I have removed the add directory from the CMakeLists.txt and its progressing well. I guess its because the python examples do not need any build.
To join the testing, I flashed a new image, updated via apt, cloned the repo, and started following this guide here to build. Some paths look to be unset. Here is the end portion of cmake’s output.
[Pre-build] Finished CMakePreBuild script
-- Finished installing dependencies
CUDA_TOOLKIT_ROOT_DIR not found or specified
-- Could NOT find CUDA (missing: CUDA_TOOLKIT_ROOT_DIR CUDA_NVCC_EXECUTABLE CUDA_INCLUDE_DIRS CUDA_CUDART_LIBRARY)
-- CUDA version:
-- system arch: aarch64
-- output path: /home/someuser/Dev/jetson-inference/build/aarch64
-- Copying /home/someuser/Dev/jetson-inference/detectNet.h
-- Copying /home/someuser/Dev/jetson-inference/homographyNet.h
-- Copying /home/someuser/Dev/jetson-inference/imageNet.h
-- Copying /home/someuser/Dev/jetson-inference/segNet.h
-- Copying /home/someuser/Dev/jetson-inference/superResNet.h
-- Copying /home/someuser/Dev/jetson-inference/tensorNet.h
-- Copying /home/someuser/Dev/jetson-inference/calibration/randInt8Calibrator.h
-- Copying /home/someuser/Dev/jetson-inference/data/images/airplane_0.jpg
-- Copying /home/someuser/Dev/jetson-inference/data/images/banana_0.jpg
-- Copying /home/someuser/Dev/jetson-inference/data/images/bird_0.jpg
-- Copying /home/someuser/Dev/jetson-inference/data/images/black_bear.jpg
-- Copying /home/someuser/Dev/jetson-inference/data/images/bottle_0.jpg
-- Copying /home/someuser/Dev/jetson-inference/data/images/brown_bear.jpg
-- Copying /home/someuser/Dev/jetson-inference/data/images/cat_0.jpg
-- Copying /home/someuser/Dev/jetson-inference/data/images/dog_0.jpg
-- Copying /home/someuser/Dev/jetson-inference/data/images/dog_1.jpg
-- Copying /home/someuser/Dev/jetson-inference/data/images/dog_2.jpg
-- Copying /home/someuser/Dev/jetson-inference/data/images/drone_0255.png
-- Copying /home/someuser/Dev/jetson-inference/data/images/drone_0427.png
-- Copying /home/someuser/Dev/jetson-inference/data/images/drone_0428.png
-- Copying /home/someuser/Dev/jetson-inference/data/images/drone_0435.png
-- Copying /home/someuser/Dev/jetson-inference/data/images/drone_0436.png
-- Copying /home/someuser/Dev/jetson-inference/data/images/fontmapA.png
-- Copying /home/someuser/Dev/jetson-inference/data/images/fontmapB.png
-- Copying /home/someuser/Dev/jetson-inference/data/images/granny_smith_0.jpg
-- Copying /home/someuser/Dev/jetson-inference/data/images/granny_smith_1.jpg
-- Copying /home/someuser/Dev/jetson-inference/data/images/orange_0.jpg
-- Copying /home/someuser/Dev/jetson-inference/data/images/orange_1.jpg
-- Copying /home/someuser/Dev/jetson-inference/data/images/peds-001.jpg
-- Copying /home/someuser/Dev/jetson-inference/data/images/peds-002.jpg
-- Copying /home/someuser/Dev/jetson-inference/data/images/peds-003.jpg
-- Copying /home/someuser/Dev/jetson-inference/data/images/peds-004.jpg
-- Copying /home/someuser/Dev/jetson-inference/data/images/polar_bear.jpg
-- Copying /home/someuser/Dev/jetson-inference/data/images/red_apple_0.jpg
-- Could NOT find Doxygen (missing: DOXYGEN_EXECUTABLE)
CMake Error at CMakeLists.txt:118 (add_subdirectory):
The source directory
/home/someuser/Dev/jetson-inference/examples
does not contain a CMakeLists.txt file.
-- Found OpenCV: /usr (found suitable version "3.2.0", minimum required is "3.0.0") found components: core calib3d
-- jetson-utils: building as submodule, /home/someuser/Dev/jetson-inference
-- Looking for Q_WS_X11
-- Looking for Q_WS_X11 - found
-- Looking for Q_WS_WIN
-- Looking for Q_WS_WIN - not found
-- Looking for Q_WS_QWS
-- Looking for Q_WS_QWS - not found
-- Looking for Q_WS_MAC
-- Looking for Q_WS_MAC - not found
-- Found Qt4: /usr/bin/qmake (found version "4.8.7")
-- Copying /home/someuser/Dev/jetson-inference/utils/XML.h
-- Copying /home/someuser/Dev/jetson-inference/utils/commandLine.h
-- Copying /home/someuser/Dev/jetson-inference/utils/filesystem.h
-- Copying /home/someuser/Dev/jetson-inference/utils/loadImage.h
-- Copying /home/someuser/Dev/jetson-inference/utils/mat33.h
-- Copying /home/someuser/Dev/jetson-inference/utils/pi.h
-- Copying /home/someuser/Dev/jetson-inference/utils/rand.h
-- Copying /home/someuser/Dev/jetson-inference/utils/timespec.h
-- Copying /home/someuser/Dev/jetson-inference/utils/camera/gstCamera.h
-- Copying /home/someuser/Dev/jetson-inference/utils/camera/v4l2Camera.h
-- Copying /home/someuser/Dev/jetson-inference/utils/codec/gstDecoder.h
-- Copying /home/someuser/Dev/jetson-inference/utils/codec/gstEncoder.h
-- Copying /home/someuser/Dev/jetson-inference/utils/codec/gstUtility.h
-- Copying /home/someuser/Dev/jetson-inference/utils/cuda/cudaFont.h
-- Copying /home/someuser/Dev/jetson-inference/utils/cuda/cudaMappedMemory.h
-- Copying /home/someuser/Dev/jetson-inference/utils/cuda/cudaNormalize.h
-- Copying /home/someuser/Dev/jetson-inference/utils/cuda/cudaOverlay.h
-- Copying /home/someuser/Dev/jetson-inference/utils/cuda/cudaRGB.h
-- Copying /home/someuser/Dev/jetson-inference/utils/cuda/cudaResize.h
-- Copying /home/someuser/Dev/jetson-inference/utils/cuda/cudaUtility.h
-- Copying /home/someuser/Dev/jetson-inference/utils/cuda/cudaWarp.h
-- Copying /home/someuser/Dev/jetson-inference/utils/cuda/cudaYUV.h
-- Copying /home/someuser/Dev/jetson-inference/utils/display/glDisplay.h
-- Copying /home/someuser/Dev/jetson-inference/utils/display/glTexture.h
-- Copying /home/someuser/Dev/jetson-inference/utils/display/glUtility.h
-- Copying /home/someuser/Dev/jetson-inference/utils/input/devInput.h
-- Copying /home/someuser/Dev/jetson-inference/utils/input/devJoystick.h
-- Copying /home/someuser/Dev/jetson-inference/utils/input/devKeyboard.h
-- Copying /home/someuser/Dev/jetson-inference/utils/network/Endian.h
-- Copying /home/someuser/Dev/jetson-inference/utils/network/IPv4.h
-- Copying /home/someuser/Dev/jetson-inference/utils/network/NetworkAdapter.h
-- Copying /home/someuser/Dev/jetson-inference/utils/network/Socket.h
-- Copying /home/someuser/Dev/jetson-inference/utils/threads/Event.h
-- Copying /home/someuser/Dev/jetson-inference/utils/threads/Mutex.h
-- Copying /home/someuser/Dev/jetson-inference/utils/threads/Process.h
-- Copying /home/someuser/Dev/jetson-inference/utils/threads/Thread.h
-- Copying /home/someuser/Dev/jetson-inference/utils/data/fontmapA.png
-- Copying /home/someuser/Dev/jetson-inference/utils/data/fontmapB.png
-- trying to build Python bindings for Python versions: 2.7;3.6;3.7
-- detecting Python 2.7...
-- Python 2.7 wasn't found
-- detecting Python 3.6...
-- Python 3.6 wasn't found
-- detecting Python 3.7...
-- Python 3.7 wasn't found
-- Copying /home/someuser/Dev/jetson-inference/utils/python/examples/camera-viewer.py
-- Copying /home/someuser/Dev/jetson-inference/utils/python/examples/gl-display-test.py
-- trying to build Python bindings for Python versions: 2.7;3.6;3.7
-- detecting Python 2.7...
-- Python 2.7 wasn't found
-- detecting Python 3.6...
-- Python 3.6 wasn't found
-- detecting Python 3.7...
-- Python 3.7 wasn't found
-- Copying /home/someuser/Dev/jetson-inference/python/examples/detectnet-camera.py
-- Copying /home/someuser/Dev/jetson-inference/python/examples/detectnet-console.py
-- Copying /home/someuser/Dev/jetson-inference/python/examples/imagenet-camera.py
-- Copying /home/someuser/Dev/jetson-inference/python/examples/imagenet-console.py
-- Copying /home/someuser/Dev/jetson-inference/python/examples/my-recognition.py
CMake Error: The following variables are used in this project, but they are set to NOTFOUND.
Please set them or make sure they are set and tested correctly in the CMake files:
CUDA_CUDART_LIBRARY (ADVANCED)
linked by target "jetson-inference" in directory /home/someuser/Dev/jetson-inference
linked by target "trt-bench" in directory /home/someuser/Dev/jetson-inference/tools/trt-bench
linked by target "trt-console" in directory /home/someuser/Dev/jetson-inference/tools/trt-console
linked by target "jetson-utils" in directory /home/someuser/Dev/jetson-inference/utils
CUDA_TOOLKIT_INCLUDE (ADVANCED)
used as include directory in directory /home/someuser/Dev/jetson-inference
used as include directory in directory /home/someuser/Dev/jetson-inference
used as include directory in directory /home/someuser/Dev/jetson-inference
used as include directory in directory /home/someuser/Dev/jetson-inference
used as include directory in directory /home/someuser/Dev/jetson-inference
used as include directory in directory /home/someuser/Dev/jetson-inference
used as include directory in directory /home/someuser/Dev/jetson-inference
used as include directory in directory /home/someuser/Dev/jetson-inference/docs
used as include directory in directory /home/someuser/Dev/jetson-inference/docs
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used as include directory in directory /home/someuser/Dev/jetson-inference/tools/trt-console
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used as include directory in directory /home/someuser/Dev/jetson-inference/tools/trt-console
used as include directory in directory /home/someuser/Dev/jetson-inference/tools/trt-console
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-- Configuring incomplete, errors occurred!
See also "/home/someuser/Dev/jetson-inference/build/CMakeFiles/CMakeOutput.log".
See also "/home/someuser/Dev/jetson-inference/build/CMakeFiles/CMakeError.log".
someuser@somenano:~/Dev/jetson-inference/build$
How is ‘CUDA_TOOLKIT_ROOT_DIR’ ordinarily set? Have I missed a step somewhere?
Edit: I suspect I have to install dependencies via my host machine onto the Nano using the JetPack installer. It would be nice if the configure script could do this. It installs all the other dependencies.
sudo ldconfig is missing here as well in the make install
ok, it worked but it is pretty slow compared to the mobilnet. The peds runs in 165ms/frame on 10w nano.
So, I’m actually stuck here:
Is there a way to install the dependencies without this? Can’t cmake do it? I tried the usb method and my workstation’s keyboard an bluetooth failed at the moment i plugged the nano in.
I am trying via ssh right now. No offense but the whole process seems kind of silly.
you don’t have to install jetpack on the nano for this. the pre-installed version is good.
You didn’t do anything and CUDA_TOOLKIT_ROOT_DIR got defined? Mind sharing what as? I’m wondering what’s the difference between our systems then.
This is kind of funny since I built the repo before sucessfully. This is my second time around building this repo and it’s not working. I would use the old image where it built but I wrote over it.
I don’t recall if I installed the dependencies on nano via the JetPack installer. I think I skipped it. In any case, I will debug some more when I have time. Something else has me occupied until Monday.
Thank you for the python bindings, Dusty!
I had forgotten to check-in this file, it should be there now, sorry about that.
It turns out what I use Qt4 for is for loading/saving images from disk and some directory listing stuff I think, so it is still relevant for headless - but yes, looking into switching to a small image loader library and removing Qt4 dependency when I have time.
That is strange, this command is included in CMakeLists.txt as a step during sudo ldconfig. I will need to debug if/when that is actually getting run, or if I need to just include it in the docs as a step that users manually run.
That is automatically defined by find_package(CUDA) in CMakeLists.txt, so what it means is your CUDA toolkit isn’t properly installed. If you are having problems with JetPack, recommend using the pre-populated SD card image (it already has CUDA toolkit, cuDNN, TensorRT installed)
My next task is integrating the SSD-Mobilenet-v1/v2 Coco models from Aasta’s sample, which I think run north of 20 FPS on Nano. They use TensorFlow UFF format and a couple plugins which I’ll need to add support for, but should be fine.
BTW the numpy bindings are working, see these example scripts of the usage:
https://github.com/dusty-nv/jetson-utils/blob/master/python/examples/cuda-to-numpy.py
https://github.com/dusty-nv/jetson-utils/blob/master/python/examples/cuda-from-numpy.py
From these we can also show how to work with PIL and OpenCV through these Numpy<->CUDA bindings.
TBH, I would probably prefer using the lower footprint Aasta code for my use case but it would be interesting to see how it works with the whole framework.
Out of curiosity, why aren’t you doing a uff model zoo? I understand its per platform, but suppose for nano?
I do plan to make an app store / model zoo page on the eLinux wiki, listing in one place all the sw install procedures from around the forums along with the different models that are known to work with TensorRT. The community will also be able to edit/contribute to it since it’s on eLinux. Hopefully will get to creating that this week or next.
OK, the SSD object detection models are now in the repo. After re-cloning and re-building, you can run them like so:
$ cd jetson-inference/build/aarch64/bin
$ ./detectnet-console.py --network=ssd-mobilenet-v2 peds-004.jpg test-004.jpg
$ ./detectnet-camera.py --network=ssd-mobilenet-v2
New options for --network flag are: ssd-inception-v2, ssd-mobilenet-v1, and ssd-mobilenet-v2
Next I am going to attempt to remove Qt4 dependency, and add a text UI for selection of the models that the user wishes to download.
Hey, I just reclone and rebuilding
Thanks a lot,
10 fps with mobilnet-ssd-v2…
14 fps with mobilenet-ssd-v1
8 fps with ssd-inception-v2 and very good accuracy…
so… for the moment, I can’t have more than 16 fps.
Thanks for checking it out - I plan to profile the camera applications and see how I can squeeze out more FPS from the pre-processing/post-processing/display and minimize any overhead.
I forgot about this thread. Reporting back, the repo built after installing cuda with the JetPack installer. I haven’t gotten a chance to write any code yet.
Is there something like an apt repository for arm64 cuda so I can avoid the JetPack installer in the future?
You don’t need to use the JetPack installer on Nano - the downloadable SD card image comes with all the JetPack components already installed.
Yes, but the default image has a broken firewall and I spent a fair amount of time building a new image using the documentation. Is there a documented procedure to install the dependencies on a new rootfs? I can’t find it here:
https://docs.nvidia.com/jetson/l4t/index.html
Barring any suggestions otherwise, Tomorrow I’m going to try overwriting my root_fs folder with the JetPack rootfs (except for my new modules) and make a new image the same way I did before using create-jetson-nano-sd-card-image.sh.
The L4T components + drivers get overlayed during this procedure: https://docs.nvidia.com/jetson/l4t/index.html#page/Tegra%2520Linux%2520Driver%2520Package%2520Development%2520Guide%2Fquick_start.html%23
(in particular the apply_binaries.sh step)
CUDA toolkit, cuDNN, TensorRT, VisionWorks, and OpenCV get installed by JetPack installer over the network / SSH. However you can quit the installer after it downloads the deb packages for these and install them yourself if you wish.