def iter_data(self, slice_element=None) -> Iterator[Result]:
"""Get frames and metadata corresponding to segment
Args:
slice_element (optional): If not specified all frames for the segment will be returned
Yields:
dict: dictionary with the fields
* ``meta``: All metadata corresponding to the segment, this is the same as the data
in the labels csv
* ``frames``: list of :class:`PIL.Image.Image` corresponding to the frames specified
in ``slice_element``
* ``id``: UID corresponding to segment
"""
slice_element = slice_element or slice(0, len(self))
for meta in self.meta_data[slice_element]:
clip_id = self._segment_metadata_to_clip_id(meta)
folder = os.path.join(
self.video_segment_dir,
meta[PARTICIPANT_ID_COL],
meta[VIDEO_ID_COL],
clip_id,
)
paths = self._find_frames(folder)
frames = list(resize_images(paths, self.frame_size))
meta["frame_size"] = frames[0].shape
meta["num_frames"] = len(frames)
meta["modality"] = 'rgb'
result = {"meta": meta, "frames": frames, "id": meta[UID_COL]}
yield result
def iter_data(self, slice_element=None) -> Iterator[Result]:
"""Get frames and metadata corresponding to segment
Args:
slice_element (optional): If not specified all frames for the segment will be returned
Yields:
dict: dictionary with the fields
* ``meta``: All metadata corresponding to the segment, this is the same as the data
in the labels csv
* ``frames``: list of :class:`PIL.Image.Image` corresponding to the frames specified
in ``slice_element``
* ``id``: UID corresponding to segment
"""
slice_element = slice_element or slice(0, len(self))
for meta in self.meta_data[slice_element]:
folder = (Path(self.video_segment_dir) / meta["participant_id"] /
meta["video_id"])
paths = [
folder / f"frame_{idx:010d}.jpg"
for idx in range(meta["start_frame"], meta["stop_frame"] + 1)
]
frames = list(resize_images(map(str, paths), self.frame_size))
meta["frame_size"] = frames[0].shape
meta["num_frames"] = len(frames)
result = {
"meta": meta,
"frames": frames,
"id": (self.get_uid(meta))
}
yield result
def iter_data(self, slice_element=None):
slice_element = slice_element or slice(0, len(self))
for meta in self.meta_data[slice_element]:
video_id = meta["video_id"]
folder = Path(
self.video_segment_dir) / meta["participant_id"] / video_id
start_frame = meta["start_frame"]
stop_frame = meta["stop_frame"]
paths = {
axis: [
folder / axis / f"frame_{idx:010d}.jpg"
for idx in range(start_frame, stop_frame)
]
for axis in ["u", "v"]
}
frames = {}
for axis in "u", "v":
frames[axis] = list(
resize_images(map(str, paths[axis]), self.frame_size))
meta["frame_size"] = frames["u"][0].shape
meta["num_frames"] = len(frames["u"])
result = {
"meta": meta,
"frames": list(_intersperse(frames["u"], frames["v"])),
"id": self.get_uid(meta),
}
yield result
def test(self, mock_resize, mock_imread):
mock_imread.side_effect = ['READ_IMAGE1', 'READ_IMAGE2', 'READ_IMAGE3']
mock_resize.side_effect = [
'RESIZED_IMAGE1', 'RESIZED_IMAGE2', 'RESIZED_IMAGE3'
]
input_ = ['ANY_IMAGE1', 'ANY_IMAGE2', 'ANY_IMAGE3']
received = list(resize_images(input_, img_size=1))
self.assertEqual(
['RESIZED_IMAGE1', 'RESIZED_IMAGE2', 'RESIZED_IMAGE3'], received)
def iter_data(self, slice_element=None):
slice_element = slice_element or slice(0, len(self))
for meta in self.all_meta[slice_element]:
video_path = os.path.join(self.videos_dir,
str(meta['id'] + '.gif'))
with temp_dir_for_bursting(self.shm_dir_path) as temp_burst_dir:
frame_paths = burst_video_into_frames(
video_path, temp_burst_dir, frame_rate=self.frame_rate)
frames = list(resize_images(frame_paths, self.frame_size))
result = {'meta': meta, 'frames': frames, 'id': meta['id']}
yield result
def iter_data(self, slice_element=None):
slice_element = slice_element or slice(0, len(self))
for meta in self.meta_data[slice_element]:
paths = self._find_uv_frames(meta)
frames = {}
for axis in "u", "v":
frames[axis] = list(resize_images(paths[axis],
self.frame_size))
meta["frame_size"] = frames["u"][0].shape
meta["num_frames"] = len(frames["u"])
result = {
"meta": meta,
"frames": list(_intersperse(frames["u"], frames["v"])),
"id": meta[UID_COL],
}
yield result