Think of the Energy Meter as a virtual movement tracker. It combines AI technologies like Computer Vision and Deep Learning to understand how the user moves during the workout, how accurately he/she is performing the exercises. To run an ML model in real-time, we had to make sure that it processes one image frame before another one comes in. However, in our case, we had to hit a baseline performance where 10 images could be processed and scored in each second. This enabled the system to recognise the most common movements in workouts and assign an energy value and score to it.

https://blog.cure.fit/engineering-design/from-offline-to-online-the-cult-live-story/Think of the Energy Meter as a virtual movement tracker. It combines AI technologies like Computer Vision and Deep Learning to understand how the user moves during the workout, how accurately he/she is performing the exercises.

To run an ML model in real-time, we had to make sure that it processes one image frame before another one comes in. However, in our case, we had to hit a baseline performance where 10 images could be processed and scored in each second. This enabled the system to recognise the most common movements in workouts and assign an energy value and score to it.

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