def extract(self, path):
capture = cv2.VideoCapture(path)
# frame size
# height = int(capture.get(cv.CV_CAP_PROP_FRAME_HEIGHT))
# width = int(capture.get(cv.CV_CAP_PROP_FRAME_WIDTH))
# video "size"
framePerSecond = capture.get(cv.CV_CAP_PROP_FPS)
frameCount = int(capture.get(cv.CV_CAP_PROP_FRAME_COUNT))
# duration = frameCount / framePerSecond
data = np.NaN * np.ones((frameCount, self.get_dimension()))
while True:
f = int(capture.get(cv.CV_CAP_PROP_POS_FRAMES))
success, frame = capture.read()
if not success:
break
data[f, :] = self.process_frame(frame)
duration = step = 1. / framePerSecond
sliding_window = SlidingWindow(start=0., duration=duration, step=step)
return SlidingWindowFeature(data, sliding_window)
def iterdiff(self, feature, focus):
"""(middle, difference) generator
`middle`
`difference`
Parameters
----------
feature : SlidingWindowFeature
Pre-extracted features
"""
sliding_window = SlidingWindow(duration=self.duration,
step=self.step,
start=focus.start,
end=focus.end)
for left in sliding_window:
right = Segment(start=left.end + self.gap,
end=left.end + self.gap + self.duration)
middle = .5 * (left.end + right.start)
yield middle, self.diff(left, right, feature)
def __init__(self, duration=0.025, step=0.01):
super(LibrosaFeatureExtractor, self).__init__()
self.duration = duration
self.step = step
self.sliding_window_ = SlidingWindow(start=-.5 * self.duration,
duration=self.duration,
step=self.step)
def __init__(self, sample_rate=16000, duration=0.025, step=0.01):
super(PySpeechFeaturesExtractor, self).__init__()
self.sample_rate = sample_rate
self.duration = duration
self.step = step
self.sliding_window_ = SlidingWindow(start=-.5 * self.duration,
duration=self.duration,
step=self.step)
def __init__(self, sample_rate=16000, augmentation=None,
duration=0.025, step=0.01):
super().__init__(sample_rate=sample_rate,
augmentation=augmentation)
self.duration = duration
self.step = step
self.sliding_window_ = SlidingWindow(start=-.5*self.duration,
duration=self.duration,
step=self.step)
def __init__(self, duration=0.025, step=0.010, stack=1):
super(YaafeFeatureExtractor, self).__init__()
self.duration = duration
self.step = step
self.stack = stack
start = -0.5 * self.duration
self.sliding_window_ = SlidingWindow(start=start,
duration=self.duration,
step=self.step)
self.engine_ = yaafelib.Engine()