MIPAR APIs

Introducing our API tools for MIPAR: Designed to seamlessly integrate with the MIPAR desktop application, our APIs enable you to execute MIPAR recipes in external workflows, expanding your image analysis capabilities. Build, optimize, and test image analysis recipes within the desktop application before deploying them as part of a larger system or analysis pipeline.

Our MIPAR REST API is tailored for network deployment in low-maintenance environments, utilizing Docker containers for streamlined implementation. Meanwhile, the MIPAR Python API is specifically designed for Python workflows and applications, making it an ideal choice for large-scale batch analysis projects or database plugin integrations.

With MIPAR API tools, enhance the power and flexibility of your image analysis solutions, unlocking new possibilities for your projects and applications.

API Comparison

 
REST API
Python API
Operating System
Windows​
Windows
Deployment​
Windows Docker container
Python library
Licensed
  • Per parallel instance
  • Subscription or perpetual
  • Network
  • Per parallel instance
  • Subscription or perpetual
  • Network or machine locked
Hosting Hardware
Customer responsibility
Customer responsibility
Security
Docker managed
No authentication control
Communication Protocol
HTTP requests
Library methods
Recommended Use Cases
  • Web hosted applications
  • Enterprise Docker applications
  • Minimal maintenance applications
  • Closed loop systems
  • Desktop applications
  • Python batch workflows
 
REST API Overview
Python API Overview

MIPAR REST API

Product Overview:
The MIPAR REST API enables users to execute Recipes through HTTP calls to a MIPAR REST API server. Designed to complement the MIPAR Image Analysis Software, it allows users to prototype, refine, and deploy scalable image analysis solutions seamlessly. The server can be deployed on a single machine or a local network server, while the REST API itself is implemented using a Windows Docker Container, ensuring a self-contained, low-maintenance solution.

Local Deployment:
With the MIPAR REST API, you can deploy it locally on a machine, regardless of network connectivity. This flexibility enables users to build, package, and deploy MIPAR Recipes on standalone workstations. Additionally, automated feature detection can be integrated with capture devices or programmable logic controllers, creating closed-loop systems.

Network Deployment:
For broader applications, the MIPAR REST API can be deployed on a server network, integrating with other network-based applications. Utilize the REST server in image processing pipelines for artificial intelligence or database processing, enhancing your overall analysis capabilities.

Documentation:
Stay up-to-date with the comprehensive REST API library documentation, which remains current with your existing MIPAR version. Access Documentation ›› 

MIPAR Python API

Product Overview:
The MIPAR Python API empowers users to execute Recipes within Python scripts and applications. Available at no additional cost to all perpetual MIPAR Software license holders, the API works hand-in-hand with the MIPAR Image Analysis Software to prototype, refine, and deploy scalable image analysis solutions.

Integrations:
The MIPAR API enables seamless integration of MIPAR Recipes into broader computer vision pipelines. By combining MIPAR's robust detection capabilities with Python's versatile libraries, users can create powerful, flexible image analysis systems. Check out the MDMI Simplify MIPAR plugin for Ansys Granta.
Application Page ›› 

Documentation:
Stay informed with the comprehensive API library documentation, which remains up-to-date with your existing MIPAR version. 
​Access Documentation ›› 

Check Out Our Other Products

MIPAR Base: our core product to analyze images from almost any source. Extensions enable Deep Learning models, Word reports and 3D data analysis.  MIPAR Base Page >>

​Microscope Software: capture, analyze and report all in a single workflow with MIPAR Live. Check to see if your camera is supported. MIPAR Live Page >> ​​
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