Creating Your Own AI Fitness Trainer: Analyzing Squats with MediaPipe

In this computer vision tutorial video, we will see the working of our application AI fitness trainer that will accurately monitor our squats, analyze the data and offer real-time feedback to develop such an app.
We leverage Media Pipe's deep learning-based human post-estimation solution.

❓Building an AI Fitness Trainer:

Mastering Squats with MediaPipe's Deep Learning Algorithm, Whether you're a beginner or a seasoned pro, imagine having an AI fitness trainer that guides you through perfect squats effortlessly. In order to achieve this ambitious goal, we can leverage the capabilities of a cutting-edge deep learning-based human pose estimation algorithm.
When it comes to estimating human poses, there are several popular frameworks available, including OpenPose, AlphaPose, Yolov7, and MediaPipe, to name a few. After careful consideration, we've chosen MediaPipe's Pose pipeline due to its exceptional inference speed on CPU. By harnessing the power of MediaPipe's Pose pipeline, we can accurately estimate human keypoints, providing real-time feedback and guidance during squat exercises. This AI fitness trainer will ensure that your squats are executed with precision, helping you improve your form, prevent injuries, and optimize your workout routine.

Join us on this exciting journey as we dive into the fascinating world of AI fitness training and discover how MediaPipe's deep learning algorithm can revolutionize the way we perform squats. Get ready to elevate your fitness game with our step-by-step tutorial on building your own AI fitness trainer using MediaPipe for flawless squat execution.

Topics Covered

✅Body Pose Estimation Using MediaPipe
✅Intuition of Frontal and Side View for Posture Analysis
✅Building an AI Fitness Trainer Using MediaPipe Pose to Analyze Squats
✅State Diagram Explanation While Performing Squats
✅Application Workflow for the AI Fitness Trainer
✅Key Concepts While Designing The Application
✅Angle Calculation
✅Feedback Actions for the AI Fitness Trainer Application
✅Computing Inactive Times
✅Test Cases in the AI Fitness Trainer Application
✅Modes of Squats – Beginner vs. Pro

⭐️ Time Stamps:⭐️
00:00-00:16: Introduction
00:16-01:58: Mediapipe's Human Pose Estimation
01:58-02:47: Test Cases
02:47-03:42: Counting a Squat
03:42-03:55: Outro

Resources:
Processing, Image Classification, Object Detection, Face Detection, Face Recognition, YOLO, Segmentation, Pose Estimation, and many more using OpenCV(Python/C++), PyTorch, and TensorFlow.

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🔖Hashtags🔖
#mediapipe #objectdetection #deeplearning #computervision #learnopencv #opencv #AIFitnessTrainer #SquatAnalysis #MediaPipePoseEstimation #PerfectSquats #FitnessTechnology #DeepLearningAlgorithm #WorkoutGuidance #FormCorrection #FitnessRevolution #AIWorkoutBuddy #BuildYourOwnTrainer #FitnessTech #EnhancePerformance #InjuryPrevention #OptimizeWorkout #FitnessGoals #AIInnovation #FitTech #SquatPerfection #AIAssistedWorkouts #TrainSmarter

[SaqibHussain-ings]

Is there is any video while building it?

[pradnya]

Ca you give code for other exercises or give some hints about other exercises

[syoyo]

Hi. May I know the version of Gradio and python interpreter that you are using?

[atharvtambekar]

can i integrate this into a react-native app !!??

[PrashantDevshali]

hey how can I use streamlit for web interface ?

[maysoonbaraka]

Can I change to another exercise.? You did a great job!

[srivatsakulkarni]

Where in the code should we give video as input and where is the output recorded

[JorgeLopez-octt]

it seems streaming on gradio isn't working

[think]

Plz reply me sir can we built an app for android for motion detection with python code embedded with java 🤔🤔

[manavpanchal]

good ai knowledge but no exercise knowledge

[RazorLiveGG]

I have a question, once the code is executed, the live stream section does not work, it pretends to turn on my camera but nothing is displayed, how can it be resolved?

[mazentarek]

that's my grad project idea, guys, you've just ruined it. 🥲