def get_samples(self, data_file):
# time = self.dict_files[data_file]['time']
audio_clip = AudioFileClip(data_file)
clip = audio_clip.set_fps(16000)
# num_samples = int(clip.fps * time)
data_frame = np.array(list(clip.subclip(0).iter_frames()))
data_frame = data_frame.mean(1)
chunk_size = 640 # split audio file to chuncks of 40ms
audio = np.pad(data_frame,
(0, chunk_size - data_frame.shape[0] % chunk_size),
'constant')
audio = np.reshape(audio, (-1, chunk_size)).astype(np.float32)
return audio
def _get_samples(self, data_file):
time = self.dict_files[data_file]['time']
if 'audio' in self.input_type.lower():
audio_clip = AudioFileClip(str(data_file))
clip = audio_clip.set_fps(16000)
num_samples = int(clip.fps * (time[1] - time[0]))
elif 'video' in self.input_type.lower():
clip = VideoFileClip(str(data_file))
if self.dict_files[data_file]['labels'].shape[0] == 1:
clip_list = np.reshape(
np.array(list(clip.iter_frames())).mean(1), (1, -1))
return clip_list, self.dict_files[data_file]['labels']
frames = []
for i in range(len(time) - 1):
start_time = time[i]
end_time = time[i + 1]
data_frame = np.array(
list(clip.subclip(start_time, end_time).iter_frames()))
if 'audio' in self.input_type.lower():
data_frame = np.squeeze(data_frame)
data_frame = data_frame.mean(1)[:num_samples]
frames.append(data_frame.astype(np.float32))
self.shape = data_frame.shape
if i == 0:
chunk_size = 640 # split audio file to chuncks of 40 ms
audio = np.pad(data_frame,
(0, chunk_size - data_frame.shape[0] % chunk_size),
'constant')
audio = np.reshape(audio, (-1, chunk_size)).astype(np.float32)
frames = [audio]
return frames, self.dict_files[data_file]['labels']
