nireg | Brain image registration package | Data Labeling library

by nipy Python Version: Current License: Non-SPDX

X-Ray Key Features Code Snippets Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | nireg Summary

nireg is a Python library typically used in Artificial Intelligence, Data Labeling applications. nireg has no bugs, it has no vulnerabilities, it has build file available and it has low support. However nireg has a Non-SPDX License. You can download it from GitHub.

Brain image registration package

Support

Quality

Security

License

Reuse

Support

nireg has a low active ecosystem.

It has 27 star(s) with 13 fork(s). There are 12 watchers for this library.

It had no major release in the last 6 months.

There are 4 open issues and 1 have been closed. On average issues are closed in 1 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of nireg is current.

Quality

nireg has 0 bugs and 0 code smells.

Security

nireg has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

nireg code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

nireg has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

nireg releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

nireg saves you 4023 person hours of effort in developing the same functionality from scratch.

It has 8556 lines of code, 683 functions and 82 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed nireg and discovered the below as its top functions. This is intended to give you an instant insight into nireg implemented functionality, and help decide if they suit your requirements.

Resample a 3D image
Convert rotation matrix to matrices
Convert to affine matrix
Convert a rotation matrix to a 4x3 matrix
Write the comment to a file
Decode an element
Convert a string to unicode
Handle comments
Add subparsers
Write the section to a file
Check whether x is a numpy array
Checks if the given check is valid
Check if value is a tuple
Convert from euler to axis angle
Renames a key
Clamp an image
Compose this transform from another
Add an argument to the parser
Convert a rotation angle to an euler matrix
Class decorator
Calculate a time - realignment of a time series
Optimizes the chain
Add all the actions to the container
Convert a matrix to a quaternion
Optimized version of fminest
Format the list of actions
Convert euler to matrix

Get all kandi verified functions for this library.

nireg Key Features

No Key Features are available at this moment for nireg.

nireg Examples and Code Snippets

No Code Snippets are available at this moment for nireg.

Community Discussions

Trending Discussions on Data Labeling

How can I do this split process in Python?

Replacing a character with a space and dividing the string into two words in R

Azure ML FileDataset registers, but cannot be accessed for Data Labeling project

QUESTION

How can I do this split process in Python?

Asked 2021-Dec-30 at 14:06

I'm trying to make a data labeling in a table, and I need to do it in such a way that, in each row, the index is repeated, however, that in each column there is another Enum class.

What I've done so far is make this representation with the same enumerator class.

A solution using the column separately as a list would also be possible. But what would be the best way to resolve this?

...

ANSWER

Answered 2021-Dec-30 at 13:57

Instead of using Enum you can use a dict mapping. You can avoid loops if you flatten your dataframe:

Source https://stackoverflow.com/questions/70532286

QUESTION

Replacing a character with a space and dividing the string into two words in R

Asked 2020-Nov-18 at 07:32

I have a dataframe that contains a column that includes strings separeted with semi-colons and it is followed by a space. But unfortunately in some of the strings there is a semi-colon that is not followed by a space.

In this case, This is what i'd like to do: If there is a space after the semi-colon we do not need a change. However if there are letters before and after the semi-colon, we should change semi-colon with space

i have this:

...

ANSWER

Answered 2020-Nov-16 at 07:24

Try something like:

Source https://stackoverflow.com/questions/64853962

QUESTION

Azure ML FileDataset registers, but cannot be accessed for Data Labeling project

Asked 2020-Oct-28 at 20:31

Objective: Generate a down-sampled FileDataset using random sampling from a larger FileDataset to be used in a Data Labeling project.

Details: I have a large FileDataset containing millions of images. Each filename contains details about the 'section' it was taken from. A section may contain thousands of images. I want to randomly select a specific number of sections and all the images associated with those sections. Then register the sample as a new dataset.

Please note that the code below is not a direct copy and paste as there are elements such as filepaths and variables that have been renamed for confidentiality reasons.

...

ANSWER

Answered 2020-Oct-27 at 22:39

Is the data behind virtual network by any chance?

Source https://stackoverflow.com/questions/64546521

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install nireg

You can download it from GitHub.
You can use nireg like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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