Introduction

The Kunpeng Computer Vision Library (KPCV) contains optimizations of the OpenCV image operators and PyTorch image operators, and uses Kunpeng vector instructions to optimize the image processing operators. This document provides the installation guide and operator interface definitions of KPCV to help you quickly get started with this library.

Table 1 lists the operators in KPCV.

**Table 1** KPCV operator composition
No.	Operator	Description
1	CV image operator library	Kunpeng vector instructions are used to optimize image processing operators in this library, including merge, resize (it supports multiple interpolation modes, such as cv2.INTER_LINEAR, cv2.INTER_CUBIC, and cv2.INTER_NEAREST_EXACT), remap, dilate, GaussianBlur, and cvtColor.
2	PyTorch image operator library	Kunpeng vector instructions are used to optimize data preprocessing operators in this library, including normalize, permute, and resize (InterpolationMode.BILINEAR (default) and InterpolationMode.BICUBIC are optimized).

KPCV is available only on the Kunpeng platform. To achieve the optimal performance, the interfaces do not verify all input parameters and inherit the original parameter verification logic of the OpenCV and TorchVision functions. The validity of input parameters needs to be ensured by the service that calls the interfaces.

Parent topic: Kunpeng Computer Vision Library User Guide