Svidro

Collections of scripts harvested mainly from Pete, but also picked up from the forums

TOC

Annotation subtraction example.groovy - An example of creating and subtracing ROIs through scripting

Create annotation of fixed size.groovy - see https://petebankhead.github.io/qupath/scripting/2018/03/09/script-create-fixed-size-region.html

Create object based on Viewer position.groovy - Creates an object at the Viewer position. In this case a rectangle. Useful if you want
to create the exact same size object multiple times and then move it to an area of interest for subsampling.

Svidro

Collections of scripts harvested mainly from Pete, but also picked up from the forums

TOC

Accessing dynamic measurements.groovy - Most annotation measurements are dynamically created when you click on the annotation, and 
are not accessible through the standard getMeasurement function. This is a way around that.

Affine transformation.groovy - access more accurate measurements for the affine transformation used in the image alignment (m5/m6+)

Alignment of local cells.groovy - check neighborhood for similarly aligned cells

Svidro

Collections of scripts harvested mainly from Pete, but also picked up from the forums
If you are starting with 0.2.0m4+ START HERE: https://petebankhead.github.io/qupath/2019/08/21/scripting-in-v020.html

TOC

Access objects in other project images.groovy - in later versions of 0.2.0M#, access the hierarchies of other images

Access other project images or data.groovy

Access project metadata.groovy - interact with user defined, per image metadata. Useful for sorting projects.

tiagocardosos

sudo apt-get install software-properties-common

sudo add-apt-repository ppa:jonathonf/python-3.6
sudo apt-get update
sudo apt-get install python3.6 libpython3.6

sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.5 2
sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.6 1

sudo rm /usr/bin/python3

dusenberrymw

Keras Tips & Tricks

fit_generator

• Can using either threading or multiprocessing for concurrent and parallel processing, respectively, of the data generator.
• In the threading approach (model.fit_generator(..., pickle_safe=False)), the generator can be run concurrently (but not parallel) in multiple threads, with each thread pulling the next available batch based on the shared state of the generator and placing it in a shared queue. However, the generator must be threadsafe (i.e. use locks at synchronization points).
• Due to the Python global interpreter lock (GIL), the threading option generally does not benefit from >1 worker (i.e. model.fit_generator(..., nb_worker=1) is best). One possible use case in which >1 threads could be beneficial is the presence of exceptionally long IO times, during which the GIL will be released to enable concurrency. Note also that TensorFlow's `session.run(

auxiliary

#!/usr/bin/python

import SimpleITK as sitk
import vtk
import numpy as np
import sys

from vtk.util.vtkConstants import *

filename = sys.argv[1]

lukas-h

Markdown License badges

Collection of License badges for your Project's README file.
This list includes the most common open source and open data licenses.
Easily copy and paste the code under the badges into your Markdown files.

Notes

• The badges do not fully replace the license informations for your projects, they are only emblems for the README, that the user can see the License at first glance.

Translations: (No guarantee that the translations are up-to-date)

• 🇫🇷 Cette liste en français

karenyyng

Table Of Content

Skip to the relevant sections if needed.

• 2-min tutorial to do it the quick-and-dirty-way
• Concepts for resolving Git conflicts
• Setting up different editors / tool for using git mergetool
  • Finding out what mergetool editors are supported
• mergetool simple code example for vimdiff
  • Resolving conflict from a Git pull
• Other great references and tutorials

somada141

#!/usr/bin/python

import SimpleITK as sitk
import vtk
import numpy as np

from vtk.util.vtkConstants import *

def numpy2VTK(img,spacing=[1.0,1.0,1.0]):
    # evolved from code from Stou S.,

kevin-keraudren

#!/usr/bin/python

import SimpleITK as sitk
import vtk
import numpy as np
import sys

from vtk.util.vtkConstants import *

filename = sys.argv[1]