92 lines
2.8 KiB
Python
92 lines
2.8 KiB
Python
"""
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file_name: intensity
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project_name: DBM
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created: 2020-20-07
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"""
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import pandas as pd
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import numpy as np
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import glob
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import parselmouth
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import librosa
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from os.path import join
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import logging
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from dbm_lib.dbm_features.raw_features.util import util as ut
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logging.basicConfig(level=logging.INFO)
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logger=logging.getLogger()
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intensity_dir = 'acoustic/intensity'
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csv_ext = '_intensity.csv'
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error_txt = 'error: length less than 0.064'
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def intensity_score(path):
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"""
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Using parselmouth library fetching Intensity
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Args:
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path: (.wav) audio file location
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Returns:
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(list) list of Intensity for each voice frame
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"""
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sound_pat = parselmouth.Sound(path)
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intensity = sound_pat.to_intensity(time_step=.001)
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return intensity.values[0]
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def calc_intensity(video_uri, audio_file, out_loc, fl_name, r_config):
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"""
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Preparing Intensity matrix
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Args:
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audio_file: (.wav) parsed audio file
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out_loc: (str) Output directory for csv's
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"""
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intensity_frames = intensity_score(audio_file)
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df_intensity = pd.DataFrame(intensity_frames, columns=[r_config.aco_int])
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df_intensity['Frames'] = df_intensity.index
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df_intensity['dbm_master_url'] = video_uri
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df_intensity[r_config.err_reason] = 'Pass'# will replace with threshold in future release
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logger.info('Saving Output file {} '.format(out_loc))
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ut.save_output(df_intensity, out_loc, fl_name, intensity_dir, csv_ext)
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def empty_intensity(video_uri, out_loc, fl_name, r_config):
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"""
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Preparing empty Intensity matrix if something fails
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"""
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cols = ['Frames', r_config.aco_int, r_config.err_reason]
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out_val = [[np.nan, np.nan, error_txt]]
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df_int = pd.DataFrame(out_val, columns = cols)
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df_int['dbm_master_url'] = video_uri
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logger.info('Saving Output file {} '.format(out_loc))
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ut.save_output(df_int, out_loc, fl_name, intensity_dir, csv_ext)
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def run_intensity(video_uri, out_dir, r_config):
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"""
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Processing all patient's for fetching Intensity
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-------------------
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-------------------
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Args:
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video_uri: video path; r_config: raw variable config object
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out_dir: (str) Output directory for processed output
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"""
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try:
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input_loc, out_loc, fl_name = ut.filter_path(video_uri, out_dir)
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aud_filter = glob.glob(join(input_loc, fl_name + '.wav'))
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if len(aud_filter)>0:
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audio_file = aud_filter[0]
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aud_dur = librosa.get_duration(filename=audio_file)
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if float(aud_dur) < 0.064:
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logger.info('Output file {} size is less than 0.064sec'.format(audio_file))
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empty_intensity(video_uri, out_loc, fl_name, r_config)
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return
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calc_intensity(video_uri, audio_file, out_loc, fl_name, r_config)
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except Exception as e:
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logger.error('Failed to process audio file') |