Hello I am trying to do a human-tracking drone and I am using Nvidia Jetson nano and pixhawk 4 . lately i learned that arm platforms do not support mavsdk-python. Is there any way to use Jetson nano and mavsdk together ?
And I tried to install mavsdk-python to Jetson nano but I couldn't.
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I want to install gcc-9 to run (E)XLA accelerated Linear Algebra on the CPU.
XLA requires GLIBCXX_3.4.26 which is only available for gcc > 8.
Debians testing package source does not seem to work, since it cannot find gcc-9 either.
I'm using Windows with a GTX 1050.
Currently I'm working with OpenCV in object detecting using yolo model. I found it's quite slow at ~7fps. I tried to install OpenCV with GPU support but it's only run when I execute the Python script in cmd, i mean not in Anaconda.
Is there any possible way to install OpenCV with GPU support?
If I want to use my computer's GPU with OpenCV, is it necessary that I build OpenCV from source with CUDA enabled? Or can I install OpenCV with CUDA support via apt-get? I noticed the following 2 packages in apt-get:
libopencv-gpu-dev - development files for libopencv-gpu2.4v5
libopencv-gpu2.4v5 - computer vision GPU library
But I am not sure if these will work with OpenCV3 or if they are only compatible with OpenCV2. I know that the gpu module in Opencv2 was split up into multiple CUDA modules in OpenCV3.
Yes it is necessary that you build opencv from the source with CUDA option enabled. The apt-get packages won't work with OpenCV3 and above versions. I suggest you install the CUDA Toolkit first and then attempt installation of OpenCV or the GPU functions won't work.
I want to install OpenCV on arm board installed ubuntu 16.04 arm OS.
Most of the docs. install OpenCV using a cross-compiler.
I've never used cross-compiler, I have a few question about it
Why do I need use cross-compiler to install OpenCV?
If I install using a cross-compiler, then always host-computer need when any of source code using OpenCV running?
I am installing openCV 3.1 following this guide. However after running CMake I see the following output
NVIDIA CUDA
Use CUFFT: YES
Use CUBLAS: NO
USE NVCUVID: NO
NVIDIA GPU arch: 20 21 30 35
NVIDIA PTX archs: 30
Use fast math: NO
I see that CUBLAS, NVCUVID and fastmath is set to NO. But I have installed cuda toolkit 7.5, so I don't understand why is it still NO, and how can I make so to install with full gpu support?
I am using Ubuntu 16.04, OpenCV 3.1
The guide that you mentioned using does not appear to have a flag related to or set to turn on the fast math feature. As far as I am aware you need to specify this during the cuda toolkit build or it will not be included in the build.
For example if you are using NVCC you must use the --use_fast_math flag; as is indicated here. So it is likely that the CMAKE scripting doesn't have that flag set anywhere either.