slideset | Slide Set : Batch Processing for ImageJ | Machine Learning library

by bnanes Java Version: Current License: BSD-2-Clause

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

kandi X-RAY | slideset Summary

slideset is a Java library typically used in Artificial Intelligence, Machine Learning, Deep Learning applications. slideset has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Slide Set is a framework for batch processing and analysis of image data using ImageJ. It simplifies image analysis by linking image files with important metadata like regions of interest, experimental conditions, and time point information, and automatically repeating analysis tasks across multiple regions in multiple images. Slide Set is a plugin for [ImageJ2] It works with [Fiji] but not with “plain” [ImageJ1] More information, including installation instructions and documentation: Comments, suggestions, and bug reports are greatly appreciated.

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Quality

Security

License

Reuse

Support

slideset has a low active ecosystem.

It has 6 star(s) with 1 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 1 have been closed. On average issues are closed in 518 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of slideset is current.

Quality

slideset has 0 bugs and 0 code smells.

Security

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

slideset code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

slideset is licensed under the BSD-2-Clause License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

slideset 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.

slideset saves you 7225 person hours of effort in developing the same functionality from scratch.

It has 14942 lines of code, 722 functions and 144 files.

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

Top functions reviewed by kandi - BETA

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

Run the main loop
Offset the top and bottom edges of a ROI
Get the 4 - connected neighbors of a vector
Get the next edge in the set
Runs the code
Checks to see if a polygon is near the border
Compute the Euclidean distance between two points
Get the length of the line in pixels
Runs the filter
Writes an element to the overlay
Set the action listeners
Add an input field to the plugin
Populate the properties from an XML stream
Run the sketch
Run the program
Reads the overlay
Builds the layout
Adds an output to this plugin matcher
Runs the analysis
Run the algorithm
The main method
Build the window layout
Runs the benchmark
Runs the run method
Runs the optimizer
Runs the algorithm

Get all kandi verified functions for this library.

slideset Key Features

No Key Features are available at this moment for slideset.

slideset Examples and Code Snippets

No Code Snippets are available at this moment for slideset.

Community Discussions

Vulnerabilities

No vulnerabilities reported

Install slideset

You can download it from GitHub.
You can use slideset like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the slideset component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

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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