Welcome to the Ops documentation!

SciJava Ops is a library for extensible algorithm retrieval and execution. SciJava Ops Image is a collection of Ops for scientific image processing, built on SciJava Ops.

The combination of these libraries allows declarative image analysis workflows, allowing users to think more about the what than the how.

🚀 Getting Started

• Why Use SciJava Ops?
  • What are the driving values of SciJava Ops?
  • How do we integrate all of these different libraries and data structures?
  • Isn’t SciJava Ops just another algorithm library?
• Installation
  • Fiji

🪄 How-to guides

• Calling Ops with the OpBuilder
  • Specifying the name with .op()
  • Passing the inputs with .input()
  • Passing an output buffer with .output()
  • Computing with .compute()
  • Additions: Repeating execution
  • Additions: Matching with classes
  • Common Pitfalls: Wildcards
• Searching for Ops in the Environment
  • Searching for operations
  • Interrogating a Namespace
  • Signatures for Op Names
• SciJava Ops Benchmarks
  • Hardware and Software
  • Op Matching
  • Framework Comparison
  • Reproducing these Results
• Scripting in Fiji
  • Obtaining an OpEnvironment
  • Obtaining inputs
  • Calling Ops
  • Putting it all together

⚙️ Examples

• Richardson-Lucy Total Variation Deconvolution
  • RLTV parameter descriptions
• FLIM Analysis
  • Basic analysis
  • Adding Calibration and Scale Bars
  • Subsampling Within ROIs
• Gaussian blur subtraction
• Fast Non-Local Means Denoise with OpenCV
  • Denoise parameter descriptions
• Spatially Adaptive Colocalization Analysis
• SciJava Ops from Python

🛠️ Development

• Writing Your Own Op Package
  • Ops Through Javadoc
  • Ops using JPMS
  • Best Practices
• Migrating Ops Written for ImageJ Ops
  • Upgrading pom-scijava
  • Removing all the boilerplate
  • Implementing the right functional interface
  • The Example Op, configured for SciJava Ops

Indices and tables

• Search Page