Build Your Own AI Personal Trainer with Python
Table of Contents
- Introduction
- Building the Personal Trainer
- Using Python and AI/ML Technologies
- Registering and Logging In
- Selecting a Difficulty Level
- Starting the Training
- How the AI Trainer Works
- Capturing Video Images
- Detecting Human Body Parts
- Calculating Joint Angles
- Validating Exercise Form
- Demonstrating Exercises
- Warm-up Exercises
- Proper Form Instructions
- Rest Periods
- Tracking Stats and Performance
- Understanding the Code Base
- Python Libraries Used
- MediaPipe for Coordinate Extraction
- Nylas for Email Automation
- Google Technologies for Speech
- Conclusion
Building Your Own Personal Trainer Using Python and AI/ML Technologies
Are You interested in learning more about artificial intelligence or looking for a fun project to do? In this video, I will Show you something mind-blowing - how to build your own personal trainer using Python and some AI and ML technologies. Whether you are new to AI or already have some experience, this video is for you.
Introduction
Hello everyone, my name is Trisom Ako, and welcome to my YouTube Channel. Today, I am excited to share my first ever AI project with you. I have built a personal trainer that uses computer vision algorithms to track your exercise form and provide real-time feedback. In this article, I will guide you through the process of building your own personal trainer and explain the concepts and technologies behind it.
Building the Personal Trainer
Using Python and AI/ML Technologies
To build the personal trainer, I used a combination of Python and AI/ML technologies. Python is a simple and easy-to-understand programming language, making it perfect for this project. I also relied on several libraries, including MediaPipe, Nylas, and Google Text-to-Speech, to handle various tasks.
Registering and Logging In
Before you can start using the personal trainer, you need to register using your email. This step ensures that your progress and workout data can be stored and retrieved. Once registered, you can log in to the application and access the training features.
Selecting a Difficulty Level
The personal trainer offers different difficulty levels to accommodate users of all fitness levels. You can choose a level that suits your capabilities and goals. This customization allows the trainer to provide appropriate exercises and track progress accurately.
Starting the Training
To begin a training session, simply signal that you are ready by saying the word "ready." The application will take this as a command to start tracking your exercises. The trainer will guide you through a series of exercises, including warm-ups and specific workouts. It uses computer vision algorithms to detect your body parts and joints, ensuring that you are performing the exercises correctly.
How the AI Trainer Works
Capturing Video Images
The personal trainer works by capturing video images using your computer's camera. Each frame of the video is analyzed to detect and track your body parts and joints. This continuous tracking allows the trainer to provide real-time feedback on your exercise form.
Detecting Human Body Parts
Using machine learning algorithms, the personal trainer can detect specific joints and body parts in a video stream. For this purpose, I used the MediaPipe library, which is an open-source API that works with multiple programming languages. MediaPipe provides 32 different human body points, allowing the trainer to track the movement and position of these points accurately.
Calculating Joint Angles
With the x and y coordinates of specific joints provided by MediaPipe, I applied mathematical functions to calculate the angles between different body parts. For example, the angle between the shoulder, elbow, and wrist can help determine the start and end points of a push-up. By validating these angles, the trainer ensures that you are performing the exercises correctly.
Validating Exercise Form
To ensure that you maintain the proper form during exercises, the personal trainer uses predefined thresholds for the minimum and maximum angles. These thresholds are manually defined for each exercise and act as benchmarks for validating your form. By comparing the actual angles with the expected ones, the trainer provides real-time feedback on your performance.
Demonstrating Exercises
Warm-up Exercises
Before starting the main workout, the personal trainer guides you through a series of warm-up exercises to prepare your body. These exercises are essential to prevent injury and optimize your performance during the workout.
Proper Form Instructions
To assist you in performing the exercises correctly, the personal trainer displays instructions in the form of pictures. These instructions demonstrate the proper technique and form for each exercise. By following these instructions, you can ensure that you are maximizing the effectiveness of your workout.
Rest Periods
The personal trainer allows you to customize the rest periods between exercises. You can specify the number of seconds you want to rest before starting a new exercise. This flexibility allows you to tailor the training session to your needs and capabilities.
Tracking Stats and Performance
Throughout the training session, the personal trainer tracks various stats, such as calories burned and time spent exercising. These stats are compiled and sent to your email after each workout. By reviewing this data, you can gauge your progress and make adjustments to your fitness routine.
Understanding the Code Base
To fully understand the code base of the personal trainer, I will provide a brief overview of the different components and libraries used.
Python Libraries Used
Several Python libraries were utilized in building the personal trainer. The main library is MediaPipe, which provides the functionality to detect body parts and joints in a video stream. OpenCV, another library, is used for video processing, allowing the trainer to capture and analyze video frames. Nylas, a powerful API, enables email automation, making it possible to send workout performance data to your email. Lastly, Google Text-to-Speech is used for audio communication between the computer and the user.
MediaPipe for Coordinate Extraction
MediaPipe is a versatile library that works across multiple platforms and programming languages. It provides the necessary tools to extract the x and y coordinates of specific body parts and joints. These coordinates are crucial for calculating joint angles and validating exercise form.
Nylas for Email Automation
Nylas is an API that allows seamless integration of email and calendars into applications. In the personal trainer, I used Nylas to automate sending emails to users after they have completed their workouts. This feature ensures that users receive their workout performance data directly in their email inboxes.
Google Technologies for Speech
To enable communication between the computer and the user, I utilized Google technologies for speech conversion. Google Text-to-Speech converts text into speech, allowing the personal trainer to provide instructions and feedback audibly. Additionally, the Speech Recognition library enables the trainer to interpret user commands via speech-to-text conversion.
Conclusion
In conclusion, building a personal trainer using Python and AI/ML technologies opens up a world of possibilities. With the ability to track and analyze exercise form, provide real-time feedback, and automate workout performance reporting, personal trainers can be taken to a whole new level. If you are interested in learning more about AI and ML or looking for a challenging project, I encourage you to start working on your personal trainer. By taking on personal projects, you can not only expand your knowledge and skills but also make a positive impact on your fitness Journey.
Don't forget to check out the publicly available code for this project on my GitHub repository. Feel free to clone it and explore the different components and functionalities. If you enjoy this video, please like, subscribe, and share it to help my channel grow and motivate me to Create more exciting content. Thank you for watching, and I hope you learned something new today!
Highlights
- Learn how to build your own personal trainer using Python and AI/ML technologies
- Utilize computer vision algorithms to track exercise form and provide real-time feedback
- Customize difficulty levels and receive personalized workout plans
- Discover the inner workings of the personal trainer code base
- Explore the libraries and technologies used, including MediaPipe, Nylas, and Google Text-to-Speech
- Step-by-step instructions and demonstrations of exercises
- Review and track workout performance statistics
- Engage in personal projects to enhance your AI and ML skills
- Access publicly available code and documentation on GitHub
- Support the growth of the YouTube channel by liking, subscribing, and sharing the video