MRTech IFF SDK
for high-performance image processing
MRTech IFF SDK (Image Flow Framework SDK) is a powerful cross-platform toolkit that facilitates the development of high-performance machine vision and image processing applications. The core of IFF SDK was initially developed by MRTech in 2016 and has been continuously improved and used in many projects ever since.
The main feature of IFF SDK is delivering images to the customer’s application code in the most efficient way. The toolkit helps achieve maximum performance for any configuration of the customer’s image processing system.
IFF SDK v1.6 “Xerocomus”
Basic Functionality
- Textual descriptions of pipeline configurations to build image processing workflows
- Exporting and importing images from the SDK pipeline to the customer application
- Controlling acquisition and processing parameters at runtime
- Seamless integration with the target application using C or Python API as well as REST HTTP interface to control image processing
- Performing accelerated image processing on dedicated and embedded NVIDIA GPUs
- Providing input from multiple machine vision cameras with PCIe, USB3, Ethernet, and MIPI interfaces
Processing modules:
- FFC, white balance, histogram
- Auto-exposure, white balance
- Gamma correction, LUT
- High performance demosaicing
- Spatial denoiser
- Image cropping, resizing
- Color space transformation
- Color correction
Control interfaces:
- JSON configuration
- C/Python API
- HTTP REST API
Compression and decompression:
- H.264, H.265
- JPEG
- JPEG2000
Input capabilities:
- Machine vision cameras
- RTSP video source
- File data input
Output capabilities:
- TIFF/DNG image recording
- RTSP video stream, WebRTC
- Export to user applications
Competitive Advantage
- Production-ready, high-quality code, field-proven in multiple real-life projects
- High-performance image processing with low latency and low overhead
- SDK architecture that makes for easy development and customization of the target application
- Upon request, MRTech provides consulting services and technical support (including implementation assistance)
Supported Hardware
- Cameras:
- Machine vision cameras from XIMEA, Basler, and other vendors
- MIPI sensors
- Platforms and operating systems:
- 64-bit Intel x86, Linux and Windows
- 64-bit ARM, NVIDIA Jetson family, Linux
- Acceleration devices:
- CUDA processing on NVIDIA GPUs, including Jetson platform
- Hardware video encoding/decoding on NVIDIA GPUs and Jetsons
Use cases
High-speed image processing for digital cinema cameras
The developed system includes either one or two high-performance PCIe cameras with 65-megapixel resolution at up to 70 FPS and an embedded Intel Core i7 computer.
The MRTech software solution enables the recording of high-framerate, high-resolution clips with write speed of up to 10 GB/s and focus on reliability, previewing clips while recording, controlling the camera, and converting recorded images to CinemaDNG and TIFF formats.
A multi-camera system for medical applications
The system consists of an array of 32 high-resolution MIPI sensors placed on a specially designed sensor carrier board and connected to the NVIDIA AGX Xavier module.
The software provides image acquisition with 5 GB/s total bandwidth, custom image processing pipeline, and an API for remote control.
A large-scale video system for entertainment and 3D scanning
This scalable system is composed of several high-performance Intel/AMD capturing nodes with eight 12-megapixel machine vision cameras per computer.
The software used in the system ensures 64 GB/s bandwidth for each node.
The entire infrastructure is controlled by a dedicated computer.
Low-latency video solutions for embedded AI systems
We have a variety of solutions with low latency streaming applications that run on the NVIDIA Jetson platform.
The following results were achieved for NVIDIA Jetson AGX Orin module:
- 4K UHD (3840×2160) images at 100 FPS with G2G latency of less than 60 ms.
- Full HD (1920×1080) images at 250 FPS with G2G latency of less than 30 ms.
