dancebean

Pushing to Multiple Git Repos

If a project has to have multiple git repos (e.g. Bitbucket and Github) then it's better that they remain in sync.

Usually this would involve pushing each branch to each repo in turn, but actually Git allows pushing to multiple repos in one go.

If in doubt about what git is doing when you run these commands, just

Imports:

import vtk
from vtk.util import numpy_support
import numpy

Create a vtkDICOMImageReader object, set its directory to the one containing all DICOM files, and Update to read in all data:

	#!/usr/bin/env python
	# -- coding: utf-8 --
	"""
	tif_to_nii

	command line executable to convert a directory of tif images
	(from one image) to a nifti image stacked along a user-specified axis

	call as: python tif_to_nii.py /path/to/tif/ /path/to/nifti
	(append optional arguments to the call as desired)

	#CODE

	#Generate root password
	import random, string
	password = ''.join(random.choice(string.ascii_letters + string.digits) for i in range(20))

	#Download ngrok
	! wget -q -c -nc https://bin.equinox.io/c/4VmDzA7iaHb/ngrok-stable-linux-amd64.zip
	! unzip -qq -n ngrok-stable-linux-amd64.zip
	#Setup sshd

	#!/usr/bin/env python
	# -- coding: utf-8 --
	"""
	nii_to_tif

	command line executable to convert 3d nifti images to
	individual tiff images along a user-specified axis

	call as: python nii_to_tif.py /path/to/nifti /path/to/tif
	(append optional arguments to the call as desired)

	!pip install fastai
	!apt-get -qq install -y libsm6 libxext6 && pip install -q -U opencv-python
	import cv2
	from os import path
	from wheel.pep425tags import get_abbr_impl, get_impl_ver, get_abi_tag
	platform = '{}{}-{}'.format(get_abbr_impl(), get_impl_ver(), get_abi_tag())

	accelerator = 'cu80' if path.exists('/opt/bin/nvidia-smi') else 'cpu'

	!pip install -q http://download.pytorch.org/whl/{accelerator}/torch-0.3.0.post4-{platform}-linux_x86_64.whl torchvision

	import nrrd # pip install pynrrd
	import nibabel as nib # pip install nibabel
	import numpy as np

	# load nrrd
	_nrrd = nrrd.read('/path/to/nrrd.nrrd')
	data = _nrrd[0]
	header = _nrrd[1]
	print data.shape, header