How IFF SDK works
Follow these steps to tap into all the benefits IFF SDK has to offer:
1. Select cameras and system hardware
This step is one of the most important in creating a machine vision system. The right choice of equipment is crucial for project success.
Please contact us if you have any questions. The MRTech team happily shares its extensive hands-on experience, know-hows, and best practices to help our customers successfully implement even the most complex machine vision projects.
2. Order and get IFF SDK software package with:
- Binary libraries for your system configuration
- C/C++ header files, Python interface module
- Sample applications with the source code
- Technical manual in PDF and HTML formats
The technical manual or a trial version of IFF SDK can be provided upon request.
3. Read the technical manual to explore how to use IFF SDK
The technical manual contains a detailed description of the library components and explains how to use the SDK efficiently.
4. Try out sample applications included in the SDK software package and available on GitHub:
- farsight is the first and most general sample application of the SDK.
It supports various functionalities, including acquisition from a machine vision camera, color pre-processing, auto-exposure and white balance, writing to disk, H.265 encoding, and RTSP streaming.
- imagebroker is another sample application that shows how to export images to the user code across IFF SDK library boundaries. Additionally, it provides an example code to render an image on the screen using OpenCV.
5. Design the required image processing pipeline using IFF SDK components and describe the pipeline in the JSON format.
The figure on the right represents an example pipeline.
6. Build your own application
Below is an example of a basic C application that illustrates the user-friendly, low-code approach implemented in IFF SDK interface:
void* handle = iff_create_chain(chain_cfg, error_handler);