OpenCV installation Raspberry Pi 3B model - python

I am trying to install OpenCV in raspberry pi 3B but every time I try to install it gives error during compilation. I have been trying this for a long time and I don't know how to do it. I have followed mainly all the instruction given in these articles :
Install opencv 4 on raspberry pi
Install guide raspberry pi 3 raspbian jessie opencv 3

I had the same error a few weeks ago and for me it works when I just use
make -j
instead of
make -j4
-j4 simply means that the raspberry pi uses all for cpu cores instead of just one with make -j
Hope I could help and please write if that works for you as well ;)

Related

Stuck on [131/416] test_faulthandler when installing Python 3.7 on Raspberry Pi 4

Python 3.7 Installation is always halted by test_faulthandler upon running
make -j 4
I've waiting many hours to no avail, I also tried to cancel and try again but didn't work either.

Installing Pandas_ta on Raspberry Pi

I have been trying for a day to install Pandas_ta on my raspberry py with little succes. I first made a Python script on my PC and then placed it on my Raspberry pi, after installing some packages, the last one I had to so was Pandas_ta. I searched op documentary, I tried out some youtube video's. But it feels harder then it should. Does someone had a guide for me ?

Installing openCV 3 in Raspian Jessie Pixel

I am trying to install OpenCV 3 in the raspian Jessie Pixel according to the method given on the following link : http://www.pyimagesearch.com/2015/10/26/how-to-install-opencv-3-on-raspbian-jessie/ but when i am trying "make -j4" command raspian OS got stuck and it made the processor speed so slow. The monitor screen went black and after certain time it comes back but still it will be stuck. Please help me in fixing this problem.
Is there any other way that i can try for installing openCV 3.

How to Copy Library between python installations

Here is the situation:
Raspberry pi 2 running raspbian running python 3.5.2 with Opencv,Numpy,pyusb
Orange pi pc running Armbian.
Both boards are quad-core arm.
So the question is can i somehow transfer the libraries from one distro to another without recompiling them? It would save me hours.
If not can i just transfer Opencv as this is the main culprit.
Thanks in advance.

TensorFlow Raspberry Pi Examples

I'm really not familiar with make. So I don't understand the meaning of those steps in 2 tutorials ("TensorFlow Makefile" and "TensorFlow Raspberry Pi Examples") to make my project on laptop work on raspberry pi 2
TensorFlow Makefile:
https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/makefile
TensorFlow Raspberry Pi Examples:
https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/pi_examples
As far as i know,"TensorFlow Makefile" will convert the tensorflow source,lib to executable file. "TensorFlow Raspberry Pi Examples" means convert your project to executable file then run the file in your_project/gen/bin/your_project
tensorflow/contrib/pi_examples/label_image/gen/bin/label_image
Hence,if I have a project on my laptop and want to load my project into Pi 2 ("TensorFlow Makefile" is already done). I just copy it to my pi 2 and do :
make -f tensorflow/my_project/Makefile
then run :
tensorflow/my_project/gen/bin/my_project
This is how to make your project work on raspberry pi 2, right ?
This will only work for Makefiles which have the option to cross-compile from a (presumably) x86(_64?)-architecture laptop to an ARM-architecture Raspberry Pi.
You're in luck, though: Google's included options in TensorFlow's Makefile to cross-compile between architectures!
If you look at line 123 of the Makefile, you'll see a comment about this.
Default to running on the same system we're compiling on.
You should override TARGET on the command line if you're cross-compiling, e.g.
make -f tensorflow/contrib/makefile/Makefile TARGET=ANDROID
So, simply make the project like so:
$ make -f tensorflow/contrib/makefile/Makefile TARGET=PI
This will compile TensorFlow for the RPi.
Incidentally, if you can, it may be easier to simply compile TensorFlow on the RPi by either pulling the sources from git or transferring it onto the RPi via USB, and building there.

Categories

Resources