Welcome to the Xtra Library for
Thermo Scientific Amira, Avizo and PerGeos Software
Below you will find a collection of add-ons (recipes, scripts, demos,…) that will help you improve your day-to-day use of Amira-Avizo and PerGeos Software and make you gain both time and efficiency.
Use the Search field to look for specific keywords related to your domain of interest. The different filters also help you target specific resources.
How to use PyQt5 in a pyscro module
Python (pyscro)
This example shows how to use PyQt5 in a pyscro module.
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Parameter optimization for auto-thresholding a data
Python (pyscro), Project (hx, pgo), Data
In this pyscro example we use opencv and matplotlib to automatically calculate an optimized parameter for thresholding the data based on various metrics.
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Automated sizing of large area nanoparticles
Recipe ISP (hxisp,a2d), Python (pyscro)
The recipe segments large area Pt-Rh nanoparticles at high resolution (TEM image).
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Python (pyscro)
This module extracts the displacement and strain components computed using the Digital Volume Correlation module.
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Load a Numpy array into PerGeos/Amira-Avizo using the Python API
Python (pyscro)
This script simply reads and loads numpy arrays in a user specified directory into PerGeos/Amira-Avizo as an image.
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Python (pyscro)
Perform incremental DVC analysis for a series of deformed image, using either small strain or large strain approaches (note: to run correctly the Green Lagrange strain script needs to be installed).
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Python (pyscro)
This module allows the user to compute the volume fraction per separated region depending on depth from the surface of a segmented object.
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Python (pyscro)
This module allows the user to measure the displacement and strain errors from two repeat scans.
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Python (pyscro)
This module allows the user to convert a scalar/vector/tensor field into a spreadsheet containing the X,Y,Z positions and the values of the field.
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Python (pyscro), Project (hx, pgo)
The purpose of this python script object is to average interleaved data.
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Particles identification in Nickel-Base Superalloy
Recipe ISP (hxisp,a2d), Python (pyscro), Data
FIB Serial Section of Particles in Nickel-Base Superalloy
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Random Forests for Multiclass Segmentation using Python API in PerGeos
Python (pyscro), Project (hx, pgo), Data
Simple demonstration of feature computation where the feature vector contains intensity and 2D eigenvalues (X & Y). This example uses random forests implementation from the sklearn package.
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