ReverseChoreography

Repository for Reverse Choreograph (Fall 2021-Spring 2022)

data:

Folder containing raw motion data

motion capture:

captureScript_mac, mediaposetest3, python_test, reverse_choreo_capture all perform motion-capture tasks. Note that only the first of these works for macs. Also note that python_test may be deprecated. Note that switching cameras requires changing the video capture index.

preprocessed:

Folder containing files generated by preprocess.ipynb. For each file in the data folder, 3 files (x, y, and z data) are created here containing position and displacement data for each used body point.

parser_output:

Folder containing a single .csv file where each row corresponds to one data run and the columns contain features extracted from that data run. Generated by parser-update.ipynb

recommendation pipeline:

model.sav is the best regression model obtained by running preprocess.ipynb, parser.ipynb, then regression_model_testing.ipynb

classification_model.sav is the best classification model obtained by performing preprocessing, parsing, and classification training.

recommend.py accepts a csv file containing motion information, allows the user to specify a tempo selected by the dancer, recommends 5 songs using model.sav, and recommends 5 songs using classification_model.sav.

Running:

Note that mac-fullScript.py will run all motion-capture and recommendation tasks in one fluid script for macs.

To successfully run recommend.py or mac-fullScript.py, be sure to log into the Spotify web client and have modified the Spotify client credentials in the file. If told that there is no active device when running a script with the Spotify client open, try first playing a song (can be just for 1 second) and then re-running the script.