Overview

Cvitek provides TDL integration algorithms to reduce the time required for application development.

This architecture realizes the algorithm required by TDL, including its pre and post processing, and provides a unified and convenient programming interface.

At present, TDL SDK includes motion detection, face detection, face recognition, face tracking, pedestrian detection, semantic segmentation, license plate recognition, license plate detection, live recognition, IR live recognition, infant detection, cry detection, attitude detection, gesture detection, Gesture Recognition and other algorithms.

Cvitek 所提供的 TDL（Turnkey Deep Learning）集成算法，用以缩短应用程序开发所需的时间。

此架构实现了 TDL 所需算法包含其前后处理 提供统一且便捷的编程接口。

目前 TDL SDK 包含 移动侦测，人脸检测，人脸识别，人脸追踪，行人检测，语义分割，车牌辨识，车牌检测，活体识别，IR活体识别，婴儿检测，哭声检测，姿态检测，手势侦测，手势识别 等算法。

Documents

Chinese Version(中文版)	格式		English Version	Format
深度学习SDK软件开发指南	html	pdf	TDL SDK Software Development Guide	html	pdf
YOLO系列开发指南	html	pdf	YOLO Development Guide	html	pdf

Compilation

1. Download toolchain

wget https://sophon-file.sophon.cn/sophon-prod-s3/drive/23/03/07/16/host-tools.tar.gz
tar xvf host-tools.tar.gz
cd host-tools
export PATH=$PATH:$(pwd)/gcc/riscv64-linux-musl-x86_64/bin

2. Compile cvitek-tdl-sdk

git clone https://github.com/milkv-duo/cvitek-tdl-sdk-cv180x.git
cd cvitek-tdl-sdk-cv180x
cd sample
./compile_sample.sh

The generated program is in the corresponding subdirectory in the sample directory.

For clean:

./compile_sample.sh clean

Reference link

https://developer.sophgo.com/thread/556.html