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AI & Software Engineering

Beginner10 lessons10 lessons

DaisyKit: AI for Everyone

Learn to deploy real-time AI pipelines — face detection, human pose, background matting, hand pose, and object detection — with just a few lines of Python using DaisyKit.

DaisyKitComputer VisionAI DeploymentPythonEdge AI
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DaisyKit: AI for Everyone

Course Curriculum

10 Lessons
01

Lesson 01: What is DaisyKit?

Understand the motivation behind DaisyKit, its graph-based pipeline architecture, and how it compares to frameworks like MediaPipe and OpenCV.

March 12, 2026
02

Lesson 02: Installation & First Program

Install DaisyKit on Linux or Windows, understand the get_asset_file model registry, and run your first face detection flow on a static image.

March 12, 2026
03

Lesson 03: Face Detection & Landmarks

Run real-time face detection with YOLO Fastest and 68-point facial landmark regression with PFLD — including mask detection — using FaceDetectorFlow.

March 12, 2026
04

Lesson 04: Human Pose Estimation

Detect 17 body keypoints in real time using SSD-MobileNetV2 person detection and Google MoveNet Lightning — with HumanPoseMoveNetFlow.

March 12, 2026
05

Lesson 05: Background Matting

Replace video backgrounds in real time using AI portrait segmentation with BackgroundMattingFlow — no green screen required.

March 12, 2026
06

Lesson 06: Hand Pose Detection

Detect 21 3D hand keypoints per hand in real time using YOLOX hand detection and Google MediaPipe hand pose model — with HandPoseDetectorFlow.

March 12, 2026
07

Lesson 07: Object Detection with YOLOX

Detect 80 COCO object classes in real time using YOLOX via ObjectDetectorFlow — and learn how to filter classes and use custom-trained models.

March 12, 2026
08

Lesson 08: Barcode & QR Code Scanning

Scan QR codes, barcodes, and 2D codes in real time using BarcodeScannerFlow — powered by ZXing-CPP with no deep learning required.

March 12, 2026
09

Lesson 09: Mobile Deployment

Run all DaisyKit AI flows on Android and iOS devices using the prebuilt native SDKs — no server, no cloud, fully on-device inference.

March 12, 2026
10

Lesson 10: Custom Models & C++ SDK

Integrate custom NCNN models into DaisyKit flows, use the C++ graph API for concurrent pipelines, and build production-grade AI applications.

March 12, 2026

Course Details

Lessons10
Duration10 lessons
Difficultybeginner

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