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TengineKit

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OAID/TengineKit

TengineKit - Free, Fast, Easy, Real-Time Face Detection & Face Landmarks & Face Attributes & Hand Detection & Hand Landmarks & Body Detection & Body Landmarks & Iris Landmarks & Yolov5 SDK On Mobile.

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Last push
C++ OtherCreated Jun 29, 2020

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Maintenance
Dormant (1727d since push)
As of today · Source: github_public_v1
Provenance
Not a fork · Organization account
As of today · Source: github_public_v1
Security (OSV)
No lockfile
As of today · Source: none

Public GitHub metadata and optional OSV dependency scans. Signals, not a guarantee. Trust methodology.

Overview

TengineKit - Free, Fast, Easy, Real-Time Face Detection & Face Landmarks & Face Attributes & Hand Detection & Hand Landmarks & Body Detection & Body Landmarks & Iris Landmarks & Yolov5 SDK On Mobile.

Capability facts

Languages
c++

Source: github.language · Jul 11, 2026

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README

中文版本

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TengineKit, developed by OPEN AI LAB.
TengineKit is an easy-to-integrate AI algorithm SDK. At present, it can run on various mobile phones at very low latency.We will continue to update this project for better results and better performance!

Effect

Face Detection &
Face 2dLandmark
Face 3dLandmark &
Iris
Upper Body Detection &
Uppper Body Landmark
Hand Detection &
Hand Landmark
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Gif

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dance of host

Video( YouTube | BiliBili )

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Have a try

  • Apk can be directly downloaded and installed on the phone to see the effect.

or

  • scan code to download apk

Goals

  • Provide best performance in mobile client
  • Provide the simplest API in mobile client
  • Provide the smallest package in mobile client

Features

  • face detection
  • face landmarks
  • face 3dlandmarks
  • face attributes for example: age, gender, smile, glasses
  • eye iris & landmarks
  • body detect
  • hand detect(Real-time, not yet on Mobile)
  • hand landmarks(Real-time, not yet on Mobile)
  • body detect google(Real-time, not yet on Mobile)
  • body landamrks(Real-time, not yet on Mobile)
  • yolov5

Update (2021/03/25)

  • Fixed Linux sample code errer
  • Update Android sample code, up fps
  • update Linux so file
  • update Linux yolov5s
  • Fixed memory(Core v0.0.6)

Performance(Face Detect & Face Landmark)

CPUTime consumingFrame rate
Kirin 9804ms250fps
Qualcomm 8555ms200fps
Kirin 9707ms142fps
Qualcomm 8358ms125fps
Kirin 710F9ms111fps
Qualcomm 43916ms62fps
MediaTek Helio P6017ms59fps
Qualcomm 450B18ms56fps

Landmark Points Order

Landmark Points Order

Contact

About the use of TengineKit and face-related technical exchanges, you can join the following QQ groups(Group Answer:TengineKit):

  • TengineKit communication QQ group: 630836519
  • Scan to join group
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