
Learn how pose detection, a computer vision model that identifies up to 33 body landmarks to form a digital skeleton, enables real-time exercise tracking and virtual coaching in mobile apps.
Learn to set up and launch an Android emulator, selecting a Pixel 7 device with Android 14, downloading the system image, and installing your Flutter app inside the emulator.
Create and launch an Android virtual device in Android Studio using Virtual Device Manager to test apps on Android 14, selecting devices like Pixel 7 Pro and configuring orientation.
Create a flutter image picker app by building a graphical user interface with an elevated button to choose or capture images from gallery or camera, then display the selected image.
Learn to capture images in a Flutter app by long-pressing a button to launch the camera via image_picker, display the captured image, and test on an Android emulator.
Learn to build a Flutter image picker app that lets users choose images from the gallery or capture with the camera. Review library setup, permissions, and displaying the selected image.
Add Google ML Kit pose detection library via pub.dev, then configure Android sdk requirements (min 21, target 33, compile 34) in build.gradle to enable pose detection.
Improve pose detector accuracy in Flutter by switching to the accurate model and single-image mode, test with various images, and draw lines joining these points.
Learn how flutter detects the downward dog pose using body landmarks, angle checks, and visibility validation, guiding users to straighten arms or lift the hip to form inverted v.
Create a real-time flutter app by starting a project and adding the camera library to display live footage and pass frames to ML models with iOS and Android permissions.
Pass live camera frames to a Flutter app's pose detector using Google ML Kit in stream mode, with a guard to draw body joints in real time for exercise counting.
Add a bottom-centered, rounded black container with a text widget in white to display the exercise rep count, overlaid on the Flutter UI using a stack.
Do you want to build intelligent mobile apps that can understand human movements, detect yoga poses, and count exercises in real-time? If so, this course is for you!
In this comprehensive course, you'll learn how to integrate pose detection models into Flutter apps from scratch. Whether you're building fitness trackers, AI-powered yoga trainers, or interactive gaming applications, pose detection allows you to analyze human body movements by identifying key points—such as shoulders, elbows, knees, and ankles.
What You’ll Learn in This Course
Introduction to Pose Detection and its real-world applications in fitness, sports, healthcare, and gaming
How to integrate pose detection models in Flutter using both images and live camera footage
Develop AI-powered apps, including:
A Yoga Trainer App that detects and evaluates yoga poses
An Exercise Counter App that tracks body movements and counts repetitions in real-time
Process pose detection results to recognize body postures and improve user experience
Real-time pose detection in Flutter for interactive applications
Build ML-based fitness tracking apps in Flutter from scratch
Course Structure
Introduction to Pose Detection – Understanding key points, joints, and motion tracking
Pose Detection with Images – Select images from the gallery or capture with the camera, process poses, and detect exercises
Real-time Pose Detection – Implement AI-powered motion tracking to detect and count workouts instantly
Hands-on Flutter Projects – Step-by-step guidance on building interactive, ML-based fitness and wellness apps
Who Is This Course For?
Flutter developers (beginners & experienced) who want to integrate AI-based pose detection
Mobile app developers looking to enhance apps with real-time motion tracking
Fitness & wellness app creators who want to build interactive workout applications
Anyone interested in Flutter app development and AI-powered mobile experiences
Why Take This Course?
Hands-on projects for real-world experience
Step-by-step guidance to integrate pose detection in Flutter
No prior machine learning knowledge required – just basic Flutter & Dart
Join us today and start building the next generation of AI-powered fitness, wellness, and gaming apps in Flutter. Let’s get moving!