Vision Programming Interface (VPI)
NVIDIA® Vision Programming Interface (VPI) is a software library that provides Computer Vision / Image Processing algorithms implemented on several computing engines available in NVIDIA embedded devices like Jetson and in discrete devices like dGPU.
VPI provides a uniform interface for seamless access to multiple compute engines like CPU, GPU Programmable Vision Accelerator (PVA), and Video Image Compositor (VIC). With VPI, a processing pipeline can fully utilize the installed computing capacity of the device with different parts of the pipeline running on different compute engines simultaneously.
VPI algorithms are highly optimized — check out the VPI performance benchmarks. Increase performance of your application by replacing parts of your pipeline containing any non performant OpenCV or Visionworks algorithms with VPI algorithms and by optimally distributing your workload on multiple compute engines with VPI.
VPI 1.0 is the first production release and is available with JetPack 4.5 to download on Jetson modules and developer kits and is also available for x86.
VPI 1.0 highlights include:
- Support for Pyramidal LK Optical Flow on CPU and GPU
- Supports YUV422 packed color format for VIC
- Enhanced interoperability with OpenCV
Refer to VPI Release Notes for details.
Harris Keypoint Detector
KLT Bounding Box Tracker
- Algorithms implemented on multiple compute engines (GPU, CPU, PVA, and VIC)
- Uniform interface to access all supported compute engines
- Seamless, zero-copy memory mapping to achieve high throughput
- Easy interoperability with OpenCV
- Sample applications to illustrate use of VPI algorithms
- Performance benchmarks for every supported algorithm
- Gaussian Pyramid Generator
- Separable Image Convolver
- Box Image Filter
- Gaussian Image Filter
- Bilateral Image Filter
- Image Rescaling
- Fast Fourier Transform
- Inverse Fast Fourier Transform
- Image Format Converter
- Perspective Warp
- Image Remapping
- Lens Distortion Correction
- Temporal Noise Reduction
- Pyramidal LK Optical Flow
- Stereo Disparity
Feature Detector and Tracking
- KLT Bounding Box Tracker
- Harris Corners Detector
- ColorNames Features Detector
- Histogram of Oriented Gradients
Webinars and Blogs
Learn how to build a complete and efficient stereo disparity-estimation pipeline using VPI that runs on Jetson-family devices. View webinar >