def ENF_estimator(power_signal0):
fs = 1000 # downsampling frequency
nfft = 8192
frame_size = 1 # change it to 6 for videos with large length recording
overlap = 0
power_signal_object = pyenf.pyENF(signal0=power_signal0,
fs=fs,
nominal=60,
harmonic_multiples=1,
duration=0.1,
strip_index=0,
frame_size_secs=frame_size,
nfft=nfft,
overlap_amount_secs=overlap)
power_spectro_strip, power_frequency_support = power_signal_object.compute_spectrogam_strips(
)
power_weights = power_signal_object.compute_combining_weights_from_harmonics(
)
power_OurStripCell, power_initial_frequency = power_signal_object.compute_combined_spectrum(
power_spectro_strip, power_weights, power_frequency_support)
power_ENF = power_signal_object.compute_ENF_from_combined_strip(
power_OurStripCell, power_initial_frequency)
# add a dynamic plot of the ENF here
return power_ENF
def give_me_ENF(fs,nfft,frame_size,overlap,harmonics_mul,signal_file,nominal):
power_signal_object = pyenf.pyENF(signal0=signal_file, fs=fs, nominal=nominal, harmonic_multiples=harmonics_mul, duration=0.1,
strip_index=0, frame_size_secs=frame_size, nfft=nfft, overlap_amount_secs=overlap)
power_spectro_strip, power_frequency_support = power_signal_object.compute_spectrogam_strips()
power_weights = power_signal_object.compute_combining_weights_from_harmonics()
power_OurStripCell, power_initial_frequency = power_signal_object.compute_combined_spectrum(power_spectro_strip,
power_weights,
power_frequency_support)
ENF = power_signal_object.compute_ENF_from_combined_strip(power_OurStripCell, power_initial_frequency)
#print(power_weights)
#print(power_initial_frequency)
return ENF
filename = power1_filepath
signal0, fs = librosa.load(filename, sr=fs) # loading the video ENF data
power_signal_filename = power2_filepath
power_signal0_orig, fs = librosa.load(power_signal_filename,
sr=fs) # loading the power ENF data
power_signal0 = power_signal0_orig[:len(signal0)]
# ENF extraction from video recording
video_signal_object = pyenf.pyENF(signal0=signal0,
fs=fs,
nominal=60,
harmonic_multiples=1,
duration=1,
strip_index=0,
frame_size_secs=frame_size,
nfft=nfft,
overlap_amount_secs=overlap,
width_signal=0.02,
width_band=1)
spectro_strip, frequency_support = video_signal_object.compute_spectrogam_strips(
)
weights = video_signal_object.compute_combining_weights_from_harmonics()
OurStripCell, initial_frequency = video_signal_object.compute_combined_spectrum(
spectro_strip, weights, frequency_support)
ENF = video_signal_object.compute_ENF_from_combined_strip(
OurStripCell, initial_frequency)
# uncomment when comparing only 2 graphs.
# creating figures for 2 plots