IPSDK Explorer  

All the image analysis and processing functions of IPSDK Toolkit are available through its user-friendly, ergonomic interface. IPSDK Explorer requires no programming skills.

Available from its interface or in the form of Python or C++ scripts, IPSDK‘s functions will significantly accelerate the speed of your applications.

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IPSDK Explorer displays the results of algorithms directly in its Viewer. This means you can directly define the most appropriate functionality to use, and precisely define the most suitable parameters.

This software solution lets you design scripts using only the mouse. Once the desired result has been obtained, it automatically generates the equivalent Python code. If you have created a Machine Learning model during your process, it will be automatically integrated into the equivalent Python script (to find out more about Machine Learning, click here).

Discover the new 3D visualization features of IPSDK Explorer 4.

Open Source Graphical User Interface

Being Open-source, its graphic interface can be modified and adapted, either by contacting Reactiv’IP or directly by each user. For example, it can be modified from the Python console by adding buttons, parameters or creating interface macros…

Furthermore, as IPSDK Explorer is implemented in Python, it is an open and scalable tool. It can be easily connected to third-party software simply by using the generated scripts or via the graphical user interface.

Finally, you can manually retouch detected elements. You can also define the elements or region of interest to be analyzed directly on the images, and correct automatic element detection if necessary (add, delete, combine, separate elements).

SMART Segmentation in IPSDK Explorer.

Machine Learning Automatic pixel segmentation

(Activate Subtitles for more explanations)

Presentation SMART Segmentation module of IPSDK.:

• how to create a model
• how to add new classes
• how to improve the model
• how to use the model

Mesh extraction, simplification and visualization

In this tutorial, you’ll discover how to :

• Generate a mesh from a label image (Mesh generation)
• Create a hybrid 3D mesh / raw dataset visualization
• Simplify the mesh and display the mesh triangles

Hover mode for 3D image travel

In this tutorial, we’ll show you how:

• Use normal view mode (fixed camera and moving dataset)
• Fly mode (fixed object and moving camera)
• Navigate within a dataset in Fly mode
• View Fly navigation mode shortcuts

4D image management and display (3D image sequence)

In this tutorial, you’ll discover how to:

• View a dataset in 4 views (Volume Rendering and 3 orthoslices)
• Adjust the display context synchronously on all 4 views
• Move an orthoslice and see its position on the other 2 orthoslices