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The task addressed is that of counting repetitions of almost all types of exercises from a live video source. The solution uses PoseNet[1], a Tensorflow model, to extract human pose estimation data from each frame, and successive frames are run against the algorithm proposed to get the live count of repetitions (reps) done until that frame. The solution runs completely offline and the method is proven to be robust enough to handle real world videos and does not require to be pre-trained except for the pose estimation part.

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