53 lines
1.2 KiB
Python
53 lines
1.2 KiB
Python
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### LIBRARIES ------
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import pandas as pd
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import numpy as np
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import os, glob
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from siuba import _ as D
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import siuba.dply.verbs
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import siuba.dply.vector
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from opendbm import FacialActivity #needed with docker?
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from opendbm import Movement as mv #needed with docker?
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from opendbm import VerbalAcoustics as va
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from opendbm import Speech as sp
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### FINDING DATASETS ----
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# find mp4 files -- assume in sample_data folder
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str_ext = '*_actor.mp4'
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list_mp4 = glob.glob(str_ext)
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path_file = list_mp4[0]
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### VERBAL ACOUSTICS -----
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#fit the model
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model_va = va()
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model_va.fit(path_file)
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#model_va = va().fit(pathfile) # one-line alternative
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var_intensity = model_va.get_audio_intensity()
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# get audio intensity
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df_va_intensity = var_intensity.to_dataframe()
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print(df_va_intensity)
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# get attributes from audio intesity
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va_inten_mean = var_intensity.mean()
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### Movement
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model_mv = mv()
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model_mv.fit(path_file) # Requires Docker
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#get head movement
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var_headmv = model_mv.get_head_movement()
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#convert head movement to dataframe
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df_headmv = var_headmv.to_dataframe()
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#note can check to see headmovement in jupyter:variables
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# this can be helpful for QC to see if head movement was captured.
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# wheh face is not detected no movement is captured and return is array of nan
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