Thursday, August 10, 2017

Python CAN bus

Install Python CAN library


~ uki$ sudo pip install python-can
Collecting python-can
Downloading python-can-1.5.2.tar.gz (77kB)
100% |████████████████████████████████| 81kB 3.3MB/s
Installing collected packages: python-can
Running setup.py install for python-can ... done
Successfully installed python-can-1.5.2

Follow the Directions


https://python-can.readthedocs.io/en/latest/installation.html

Monday, July 17, 2017

Android Adaptive Icons

Android allows us to create adaptive icons (various shapes for one icon for different devices) for:
  • launcher icons
  • shortcuts
  • Setting app
  • sharing dialogs
  • overview screen
You have to provide the following layers 108x108 dp:
  • top mask (circle, squircle, rounded square, square) provided by device OEM (e.g. Samsung)
  • foreground layer 72x72 dp should be visible in the mask viewport
  • background layer

The edge 18 dp are reserved for system's special effects.

Use Android Studio 3.0 Asset Studio to create these adaptive icons.



Reference:

https://developer.android.com/preview/features/adaptive-icons.html

Tuesday, April 25, 2017

Python UnicodeDecodeError



When you are reading CSV file (spreadsheet), make sure you set encoding="utf-8", or you might get:

UnicodeDecodeError: 'utf-8' codec can't decode byte
(result, consumed) = self._buffer_decode(data, self.errors, final)



def read_rows(CSV_file_path: str):
 
    import sys
    print("default encoding", sys.getdefaultencoding())
    import csv
    rows = []
    with open(CSV_file_path, 'rt', encoding="utf-8") as csvfile:
        cvs_reader = csv.reader(csvfile, delimiter=',', quotechar='"')
        for row in cvs_reader: # row is a list
            rows.append(row)
    return rows

Sunday, April 16, 2017

Using Docker containers on Mac

Install Docker on Mac


https://download.docker.com/mac/stable/Docker.dmg


$ docker --version
Docker version 17.03.1-ce, build c6d412e

$ docker-compose --version
docker-compose version 1.11.2, build dfed245

$docker-machine --version
docker-machine version 0.10.0, build 76ed2a6

Docker for Udacity Machine Learning

$ docker pull kyoungrok0517/tensorflow-udacity

Docker for Raspberry Pi

Having created a large Pi cluster, the next logical step is to deploy various microservices in Docker containers on Pi.

https://www.raspberrypi.org/blog/docker-comes-to-raspberry-pi/










Thursday, April 6, 2017

Python OCR for robotics.

I was thinking that it would be cool for my robots to have text reading capability, also known as OCR.

I was testing Python pytesseract library:


https://github.com/UkiDLucas/uki.guru/blob/master/OCR/ocr.ipynb


So far no success, but it will be worth trying.

Monday, March 27, 2017

Python: Passing *args and **kwargs into a function

# *args is the usual notation for optional, non-keyword arguments
# **kwargs is the usual notation for optional, keyword arguments
def test_var_args(regular_argument, *args, **kwargs):
    print ("- regular argument:", regular_argument)
    for arg in args:
        print ("- unnamed arguments arg:", arg)
    for key in kwargs:
        print ("- named arguments: %s: %s" % (key, kwargs[key]))
test_var_args(1, "two", 3, four=4, five="five")


- regular argument: 1
- unnamed arguments arg: two
- unnamed arguments arg: 3
- named arguments: four: 4
- named arguments: five: five

Wednesday, March 22, 2017

Python bubble sort

Since I had to learn python for my machine learning and self-driving classes and I had to review the basics. Not to waste my efforts, I am creating a new guide, you can see more in:

https://github.com/UkiDLucas/python_zen_interviews

def bubble_sort(the_list: list, verbose: int=0):
    """
    author: @UkiDLcuas
    This function changes the provided list.
    The list can contain integers, decimal numbers, strings, etc.
    The list is sorted in ascending order (first to last).
    The function does not return anything.
    """
    if verbose > 0:
        iteration = 0
   
    # count remining bubbles ( aka step backwards)
    start = len(the_list)-1 # end, zero-based list
    stop = 0 # beginning
    step = -1 # backwards
    for remaining_bubbles in range(start, stop, step):
        for i in range(remaining_bubbles):
            if verbose > 0:
                iteration = iteration + 1
                print("iteration", iteration, "remaining_bubbles", remaining_bubbles, "index", i)
                print("  ", the_list)
                print("    comparing if is", the_list[i], "bigger than", the_list[i+1])
            if the_list[i] > the_list[i+1]:
                # swap
                temp = the_list[i+1] # temp placehoder for the value to be moved
                the_list[i+1] = the_list[i] # bubble up
                the_list[i] = temp # bubble down
    if verbose > 0:
        print("*** finished", len(the_list), "element list in ", iteration, "iterations")

Thursday, March 16, 2017

AWS

Notes on how I use Amazon AWS EC2 instances for Convolutional Deep Neural Networks Machine Learning, using powerful GPU CUDA configurations.

I have moved this post to:

https://ukidlucas.github.io/posts/AWS.html

Sunday, March 5, 2017

Ubuntu: installing TensorFlow for NVidia (CUDA) GPU


I am setting TensorFlow on:
  • Ubuntu 16.04 LTS 64-bit
  • 16 GiB RAM
  • AMD Athlon(tm) II X4 640 Processor × 4 
  • GeForce GTX 1050 Ti/PCIe/SSE2

Check if you have NVidia CUDA GPU



uki@uki-p6710f:~$  lspci | grep -i nvidia
01:00.0 VGA compatible controller: NVIDIA Corporation Device 1c82 (rev a1)
01:00.1 Audio device: NVIDIA Corporation Device 0fb9 (rev a1)







Check the name of your OS




uki@uki-p6710f:~$ uname -m && cat /etc/*release
x86_64
DISTRIB_ID=Ubuntu
DISTRIB_RELEASE=16.04
DISTRIB_CODENAME=xenial
DISTRIB_DESCRIPTION="Ubuntu 16.04.1 LTS"
NAME="Ubuntu"
VERSION="16.04.1 LTS (Xenial Xerus)"
ID=ubuntu
ID_LIKE=debian
PRETTY_NAME="Ubuntu 16.04.1 LTS"
VERSION_ID="16.04"
HOME_URL="http://www.ubuntu.com/"
SUPPORT_URL="http://help.ubuntu.com/"
BUG_REPORT_URL="http://bugs.launchpad.net/ubuntu/"
VERSION_CODENAME=xenial
UBUNTU_CODENAME=xenial


Check C compiler



uki@uki-p6710f:~$ gcc --version
gcc (Ubuntu 5.4.0-6ubuntu1~16.04.4) 5.4.0 20160609
Copyright (C) 2015 Free Software Foundation, Inc.
This is free software; see the source for copying conditions.  There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

Ubuntu Headers 



uki@uki-p6710f:~$ sudo apt-get install linux-headers-$(uname -r)
[sudo] password for uki:
Reading package lists... Done
Building dependency tree
Reading state information... Done
linux-headers-4.4.0-62-generic is already the newest version (4.4.0-62.83).
linux-headers-4.4.0-62-generic set to manually installed.
The following packages were automatically installed and are no longer required:
  linux-headers-4.4.0-31 linux-headers-4.4.0-31-generic linux-image-4.4.0-31-generic linux-image-extra-4.4.0-31-generic
Use 'sudo apt autoremove' to remove them.
0 upgraded, 0 newly installed, 0 to remove and 89 not upgraded.

Download newest CUDA installer (1.4GB)


https://developer.nvidia.com/cuda-downloads

https://developer.nvidia.com/compute/cuda/8.0/Prod2/local_installers/cuda_8.0.61_375.26_linux-run

Execute CUDA installer

 cd ~/Downloads/
uki@uki-p6710f:~/Downloads$ ls -alt

Mar  5 14:54 cuda_8.0.61_375.26_linux.run
Feb  2 09:53 NVIDIA-Linux-x86_64-375.10.run

$ sudo sh cuda_8.0.61_375.26_linux.run

Set environment variables

uki@uki-p6710f:~$ nano ~/.bashrc

##### CUDA 
export PATH=/usr/local/cuda-8.0/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64



uki@uki-p6710f:~$ echo $LD_LIBRARY_PATH

/usr/local/cuda-8.0/lib64

Install TensorFlow via pip3 (Python 3.5)


uki@uki-p6710f:~$ python --version
Python 3.5.2 :: Anaconda 4.3.0 (64-bit)

$ sudo apt install python3-pip


$  conda info --envs
# conda environments:
#
tensorflow               /home/uki/anaconda3/envs/tensorflow
root                  *  /home/uki/anaconda3


$ conda env create -f /Users/ukilucas/dev/uki.guru/conda_enviroment_GPU.yml

$source activate tensorflow


Setting Jupyter kernel to match Python conda environment


http://ukitech.blogspot.com/2017/02/kernel.html

Saturday, February 18, 2017

Removing unused Jupyter notebook kernels on Mac

Since I am experimenting with various Python versions 2 vs 3.5 vs 3.6 and packages, e.g. TensorFlow I often end up with conda environments and corresponding Jupyter kernels that I do not use.

Removing Kernels



$ cd ~/Library/Jupyter/kernels 
$ rm -r tensorflow_gpu/

See my post on:

Installing Jupyter kernels to match Conda environments


http://ukitech.blogspot.com/2017/02/kernel.html