CV-CUDA™ is an open-source, graphics processing unit (GPU)-accelerated library for cloud-scale image processing and computer vision developed jointly by NVIDIA and the ByteDance Applied Machine Learning teams. CV-CUDA helps developers build highly efficient pre- and post-processing pipelines that can improve throughput by more than 10x while lowering cloud computing costs.
CV-CUDA includes:
- A unified, specialized set of high-performance CV and image processing kernels
- C, C++, and Python APIs
- Batching support, with variable shape images
- Zero-copy interfaces to PyTorch
- Sample applications: object classification and image segmentation
| Pre/Post-Processing Operators | Definition |
|---|---|
| AverageBlur | Reduces image noise using an average filter |
| BilateralFilter | Reduces image noise while preserving strong edges |
| CenterCrop | Crops an image at its center |
| ChannelReorder | Shuffles the order of image channels |
| Composite | Composites two images together |
| Conv2D | Convolves an image with a provided kernel |
| CopyMakeBorder | Creates a border around an image |
| CustomCrop | Crops an image with a given region-of-interest |
| CvtColor | Converts an image from one color space to another |
| DataTypeConvert | Converts an image’s data type, with optional scaling |
| Erase | Erases image regions |
| Flip | Flips a 2D image around its axis |
| GammaContrast | Adjusts image contrast |
| Gaussian | Applies a gaussian blur filter to the image |
| Laplacian | Applies a Laplace transform to an image |
| MedianBlur | Reduces an image’s salt-and-pepper noise |
| Morphology | Performs morphological erode and dilate transformations |
| Normalize | Normalizes an image pixel’s range |
| PadStack | Stacks several images into a tensor, with border extension |
| PillowResize | Changes the size and scale of an image using python-pillow algorithm |
| Reformat | Converts a planar image into non-planar and vice versa |
| Resize | Changes the size and scale of an image |
| Rotate | Rotates a 2D array in multiples of 90 degrees |
| WarpAffine | Applies an affine transformation to an image |
| WarpPerspective | Applies a perspective transformation to an image |
An awesome product requires excellent support. CV-CUDA release notes can be found here
File requests for enhancements and bug reports here.
NVIDIA offers a number of computer vision products
In addition to cloud-scale computer vision and image processing, NVIDIA offers:
- DALI (Data Loading Library), a portable, holistic framework for accelerated data loading and augmentation in deep learning workflows involving images, videos, and audio data.
- VPI (Vision Programming Interface), an accelerated computer vision and image processing software library primarily for embedded/edge applications.
- cuCIM (Compute Unified Device Architecture Clara Image), an open source, accelerated computer vision and image processing library for multidimensional images in biomedical, geospatial, material life science, and remote sensing use cases.
- NPP (NVIDIA Performance Primitives), an image, signal, and video processing library that accelerates and performs domain-specific functions.
If you want to learn more about what computer vision solutions are available, review the computer vision solutions landing page.
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