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@jordelver
jordelver / gist:3139365
Created July 18, 2012 22:29
How to write an image file to an SD card under Mac OS X (for Raspberry Pi)

Find the SD card device

In this case, the SD card is /dev/disk4. DO NOT get this wrong or you may destroy all the data on the wrong disk/card/drive.

diskutil list

/dev/disk0
   #:                       TYPE NAME                    SIZE       IDENTIFIER
   0:      GUID_partition_scheme                        *160.0 GB   disk0

1: EFI 209.7 MB disk0s1

@schwehr
schwehr / gdal_geotiff_metadata.ipynb
Created February 22, 2013 19:57
Using gdal to read/write the metadata fields for a geotiff and for specific bands within the geotiff.
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@iamtekeste
iamtekeste / Download Google Drive files with WGET
Created July 8, 2015 11:00
Download Google Drive files with WGET
Download Google Drive files with WGET
Example Google Drive download link:
https://docs.google.com/open?id=[ID]
To download the file with WGET you need to use this link:
https://googledrive.com/host/[ID]
Example WGET command:
@kylemcdonald
kylemcdonald / showarray.py
Created January 3, 2016 08:56
Minimal code for rendering a numpy array as an image in a Jupyter notebook in memory. Borrowed from the Deep Dream notebook.
import PIL.Image
from cStringIO import StringIO
import IPython.display
import numpy as np
def showarray(a, fmt='png'):
a = np.uint8(a)
f = StringIO()
PIL.Image.fromarray(a).save(f, fmt)
IPython.display.display(IPython.display.Image(data=f.getvalue()))
@awesomebytes
awesomebytes / inertia_matrix.py
Last active December 7, 2023 13:39
Compute inertia matrix for simple solids: cube, sphere and cylinder
#/usr/bin/env python
# Based on:
# http://mathworld.wolfram.com/MomentofInertia.html
def get_cube_inertia_matrix(mass, x, y, z):
"""Given mass and dimensions of a cube return intertia matrix.
:return: ixx, ixy, ixz, ixy, iyy, iyz, ixz, iyz, izz
From https://www.wolframalpha.com/input/?i=moment+of+inertia+cube"""
@stonehippo
stonehippo / docker_usb_guest_osx.md
Last active June 12, 2024 10:36
Getting a USB device to show up in a Docker container on OS X

Getting a USB device to show up in a Docker container on OS X

Some background

I was trying to get the Arduino IDE to work inside a Docker container on OS X. I was able to get the IDE working (see Getting X11 GUI applications to work on OS X with Docker), but I could not figure out how to make the USB port for the Arduino visible.

The solution

I first tried to directly map hardware serial port into the Docker container, doing something like this:

@hagerty
hagerty / CosmiQNet.Alternative.py
Last active February 27, 2017 14:12
Alternative architecture for CosmiQNet
with tf.device(gpu):
# Generator
x8 = tf.placeholder(tf.float32, shape=[None, FLAGS.ws, FLAGS.ws, 8])
x3 = tf.placeholder(tf.float32, shape=[None, scale * FLAGS.ws, scale * FLAGS.ws, 3])
label_distance = tf.placeholder(tf.float32, shape=[None, FLAGS.ws, FLAGS.ws, 1])
for i in range(layers):
alpha[i] = tf.Variable(0.9, name='alpha_' + str(i))
beta[i] = tf.maximum( 0.0 , tf.minimum ( 1.0 , alpha[i] ), name='beta_'+str(i))
bi[i] = tf.Variable(tf.constant(0.0,shape=[FLAGS.filters]), name='bi_'+str(i))
bo[i] = tf.Variable(tf.constant(0.0,shape=[FLAGS.filters]), name='bo_'+str(i))
@kolergy
kolergy / StupidLife_V0.5.4.py
Last active January 23, 2017 20:57
Stupid Life: it's stupid but it moves, NN & GA
#!/usr/freeware/bin/python
## #!/home/QtPalmtop/bin/python
#-------------------------------------------------------------------------------------------
#-------------------------------------------------------------------------------------------
# Ustructured NN
# Kolergy
# Written in Python. See http://www.python.org/
#-------------------------------------------------------------------------------------------
#-------------------------------------------------------------------------------------------
@ndronen
ndronen / model.py
Last active April 28, 2018 19:50
Semantic segmentation with ENet in PyTorch
#!/usr/bin/env python
"""
A quick, partial implementation of ENet (https://arxiv.org/abs/1606.02147) using PyTorch.
The original Torch ENet implementation can process a 480x360 image in ~12 ms (on a P2 AWS
instance). TensorFlow takes ~35 ms. The PyTorch implementation takes ~25 ms, an improvement
over TensorFlow, but worse than the original Torch.
"""
from __future__ import absolute_import
@lirnli
lirnli / Pytorch RNN.ipynb
Last active October 17, 2020 07:19
Pytorch RNN examples
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