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Does the wrapper support the feature fractal markers #33
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I updated the Python wrapper to aruco 3.1.2 which supports fractal markers. Can you try the branch 3.1.2? It's not uploaded to pip yet. |
Setting it up!
Thank you for pointing out!
…On Fri, May 24, 2019 at 1:35 PM fehlfarbe ***@***.***> wrote:
I updated the Python wrapper to aruco 3.1.2 which supports fractal
markers. Can you try the branch 3.1.2
<https://github.com/fehlfarbe/python-aruco/tree/aruco-3.1.2>? It's not
uploaded to pip yet.
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I am trying to install it but getting errors
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Did you run |
got through with: |
python3 ./fractal.py |
did you run |
python
does swigbuild need swig or swig3.0 in case of python 3? |
it seems that it installed aruco to system wide python instead of the one that I am using in the virtualenv |
after I installed it system wide it fails with: |
with python2 it fails with: |
probably the opencv-contrib doesn't have the fractal detector? |
You don't have to import |
trying again:
~/opencv-4.1.0/python-aruco/example$ python3 fractal.py During handling of the above exception, another exception occurred: Traceback (most recent call last): |
python
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python3
During handling of the above exception, another exception occurred: Traceback (most recent call last): |
did you try it with python 3.6? |
Yes, I tried with python 3.6 (created this
I'm working on a x86 system so maybe it's just not working on ARM. Maybe I can test it on Monday with my Jetson TX1. |
it seems that your docker file utilizes opencv 3.1. |
I did up a cloud instance with 18.04, downloaded the python-aruco, and added Dockerfile and started with docker build . it fails, unfortunately both at local x86_64 and in cloud instances with 18.04 and clean OS WARNING: apt does not have a stable CLI interface. Use with caution in scripts. Reading package lists... |
I installed fresh Ubuntu OS 18.04 locally and trying again. ` |
Hm seems there was an encoding error in setup.py. I updated the branch. This Dockerfile should work:
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It worked with the docker file. |
However, I am trying to reproduce the success in virtual environment with the sequence below Outputs seems non success: writing manifest file 'aruco.egg-info/SOURCES.txt' During handling of the above exception, another exception occurred: Traceback (most recent call last): |
any chance to patch venv installation process somehow? Thanks writing manifest file 'aruco.egg-info/SOURCES.txt' Installed /home/nvidia/venv/lib/python3.6/site-packages/aruco-3.1.2.0-py3.6-linux-x86_64.egg Using /home/nvidia/venv/lib/python3.6/site-packages Using /home/nvidia/venv/lib/python3.6/site-packages During handling of the above exception, another exception occurred: Traceback (most recent call last): |
The missing symbol is part of OpenCV. Do you have multiple OpenCV versions on your system? |
no, I have just reinstalled OS Ubuntu, then installed opencv 4.1.0 [ with aruco module from contrib], then installed aruco, then installed python aruco. |
with opencv 3.4 I can successfully reproduce steps at Fresh OS Ubuntu environment at cloud instance. |
at a new cloud instance, I am repeating the steps, but with substitution of 3.4.6 to 4.1.0 Could you check if Docker file with 4.1.0 will work at your side? |
can get through with: |
You don't need to compile aruco for python-aruco. A modified version of aruco (there are some function declarations in the header files without a definition in the cpp files) is already included in python-aruco :) |
thank you for the update |
Done! Replace 1000 with your user / group idRUN apt-get update && apt-get install -y sudo apt-utils install tools and libsRUN apt-get update install opencv and arucoRUN mkdir -p /home/nvidia/Templates/src #RUN mkdir -p /home/user/src/python-aruco |
May be you have insights how to split the work to multiple processors? |
Is only one CPU busy? OpenCV already uses multiple threads for some functions maybe you can speed up the detection if you use (multiprocessing)[https://docs.python.org/3/library/multiprocessing.html] Pool. Don't uses threads for better performance in Python because they all run on the same core (due Python's GIL). |
it just runs terribly slow in our case like 1-5 fps and therefore a need to accelerate arises.
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for aarch there are sudo apt-get install -y python-opencv python3-opencv |
we were previously using the code to process a stream with cv2.aruco cap = cv2.VideoCapture(gst, cv2.CAP_GSTREAMER) while True: cap.release() |
it is rather a question or feature request than an issue.
Thank you for understanding.
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