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import csv
import numpy as np
from pyVHR.datasets.dataset import Dataset
from pyVHR.signals.bvp import BVPsignal
class UBFC2(Dataset):
"""
UBFC dataset structure:
-----------------
datasetDIR/
| |-- SubjDIR1/
| |-- vid.avi
|...
| |-- SubjDIRM/
| |-- vid.avi
"""
name = 'UBFC2'
signalGT = 'BVP' # GT signal type
numLevels = 2 # depth of the filesystem collecting video and BVP files
numSubjects = 26 # number of subjects
video_EXT = 'avi' # extension of the video files
frameRate = 30 # vieo frame rate
VIDEO_SUBSTRING = '' # substring contained in the filename
SIG_EXT = 'txt' # extension of the BVP files
SIG_SUBSTRING = '' # substring contained in the filename
SIG_SampleRate = 30 # sample rate of the BVP files
skinThresh = [40,60] # thresholds for skin detection
def readSigfile(self, filename):
""" Load BVP signal.
Must return a 1-dim (row array) signal
"""
gtTrace = []
gtTime = []
gtHR = []
with open(filename, 'r') as f:
x = f.readlines()
s = x[0].split(' ')
s = list(filter(lambda a: a != '', s))
gtTrace = np.array(s).astype(np.float64)
t = x[2].split(' ')
t = list(filter(lambda a: a != '', t))
gtTime = np.array(t).astype(np.float64)
hr = x[1].split(' ')
hr = list(filter(lambda a: a != '', hr))
gtHR = np.array(hr).astype(np.float64)
data = np.array(gtTrace)
time = np.array(gtTime)
self.SIG_SampleRate = np.round(1/np.mean(np.diff(time)))
return BVPsignal(data, self.SIG_SampleRate)
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