💡I built my own personal trainer using Python and AI.
🏋️♀️The trainer detects human movements in real-time using ML algorithms.
📷It uses video images captured by a camera to locate specific joints and body parts.
⚙️Users can register using an email, choose a difficulty level, and start exercising.
📊The trainer validates exercises by checking the angle between different joints.
What technologies did you use to build the personal trainer?
—I used Python, AI/ML algorithms, the MediaPipe library, OpenCV, Nylas API, and Google text-to-speech.
How does the trainer provide exercise instructions?
—It shows instructions in the form of pictures and offers a customizable duration for resting between exercises.
Can I track my workout performance?
—Yes, the trainer sends you an email with workout stats, including calories burned and time spent exercising.
Is the code available?
—Yes, I have made the code publicly available on my GitHub repository.
What advice do you have for learning AI/ML?
—Start working on personal projects and continue learning and experimenting. It's a great way to grow as an engineer.
00:00Introduction and motivation for building a personal trainer with Python and AI.
01:20Demonstration of the personal trainer with a one-minute demo.
02:23Explanation of the Python libraries and AI technologies used in the project.
04:00Code overview and organization of the project files.
07:00Conclusion, encouragement to explore AI/ML through personal projects, and call-to-action to like, subscribe, and share the video.
