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This project enables the user to easily collect a automatically annotated dataset of human exercise with video. The collected datasets can then be used to train a deep learning model for exercise recognition and repetition rate estimation with the project Action-Recognition.
scheduleCap.py collects a labelled dataset of exercise movements in the form of ordered webcam images.
- check that the testing is off (TESTING = False)
- that the user id (USER_ID) is correct
information is stored and retreved from the file: Action_Recording_Schedule.json
This includes information such as action_types, a list of possible actions state_types, a list of possible states in the schedule. schedule, list of entries in the form {state: time period}