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[Improvement] add option to keep tail frames #1050

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Jul 23, 2021
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[Improvement] add option to keep tail frames #1050

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59 changes: 32 additions & 27 deletions mmaction/datasets/pipelines/loading.py
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Original file line number Diff line number Diff line change
Expand Up @@ -99,6 +99,8 @@ class SampleFrames:
start_index (None): This argument is deprecated and moved to dataset
class (``BaseDataset``, ``VideoDatset``, ``RawframeDataset``, etc),
see this: https://github.com/open-mmlab/mmaction2/pull/89.
keep_tail_frames (bool): Whether to keep tail frames when sampling.
Default: False.
"""

def __init__(self,
Expand All @@ -109,7 +111,8 @@ def __init__(self,
twice_sample=False,
out_of_bound_opt='loop',
test_mode=False,
start_index=None):
start_index=None,
keep_tail_frames=False):

self.clip_len = clip_len
self.frame_interval = frame_interval
Expand All @@ -118,6 +121,7 @@ def __init__(self,
self.twice_sample = twice_sample
self.out_of_bound_opt = out_of_bound_opt
self.test_mode = test_mode
self.keep_tail_frames = keep_tail_frames
assert self.out_of_bound_opt in ['loop', 'repeat_last']

if start_index is not None:
Expand All @@ -140,21 +144,32 @@ def _get_train_clips(self, num_frames):
np.ndarray: Sampled frame indices in train mode.
"""
ori_clip_len = self.clip_len * self.frame_interval
avg_interval = (num_frames - ori_clip_len + 1) // self.num_clips

if avg_interval > 0:
base_offsets = np.arange(self.num_clips) * avg_interval
clip_offsets = base_offsets + np.random.randint(
avg_interval, size=self.num_clips)
elif num_frames > max(self.num_clips, ori_clip_len):
clip_offsets = np.sort(
np.random.randint(
num_frames - ori_clip_len + 1, size=self.num_clips))
elif avg_interval == 0:
ratio = (num_frames - ori_clip_len + 1.0) / self.num_clips
clip_offsets = np.around(np.arange(self.num_clips) * ratio)
if self.keep_tail_frames:
avg_interval = (num_frames - ori_clip_len + 1) / float(
self.num_clips)
if num_frames > ori_clip_len - 1:
base_offsets = np.arange(self.num_clips) * avg_interval
clip_offsets = (base_offsets + np.random.uniform(
0, avg_interval, self.num_clips)).astype(np.int)
else:
clip_offsets = np.zeros((self.num_clips, ), dtype=np.int)
else:
clip_offsets = np.zeros((self.num_clips, ), dtype=np.int)
avg_interval = (num_frames - ori_clip_len + 1) // self.num_clips

if avg_interval > 0:
base_offsets = np.arange(self.num_clips) * avg_interval
clip_offsets = base_offsets + np.random.randint(
avg_interval, size=self.num_clips)
elif num_frames > max(self.num_clips, ori_clip_len):
clip_offsets = np.sort(
np.random.randint(
num_frames - ori_clip_len + 1, size=self.num_clips))
elif avg_interval == 0:
ratio = (num_frames - ori_clip_len + 1.0) / self.num_clips
clip_offsets = np.around(np.arange(self.num_clips) * ratio)
else:
clip_offsets = np.zeros((self.num_clips, ), dtype=np.int)

return clip_offsets

Expand Down Expand Up @@ -333,21 +348,11 @@ class DenseSampleFrames(SampleFrames):
"""

def __init__(self,
clip_len,
frame_interval=1,
num_clips=1,
*args,
sample_range=64,
num_sample_positions=10,
temporal_jitter=False,
out_of_bound_opt='loop',
test_mode=False):
super().__init__(
clip_len,
frame_interval,
num_clips,
temporal_jitter,
out_of_bound_opt=out_of_bound_opt,
test_mode=test_mode)
**kwargs):
super().__init__(*args, **kwargs)
self.sample_range = sample_range
self.num_sample_positions = num_sample_positions

Expand Down
9 changes: 9 additions & 0 deletions tests/test_data/test_pipelines/test_loadings/test_sampling.py
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Original file line number Diff line number Diff line change
Expand Up @@ -26,6 +26,15 @@ def test_sample_frames(self):
clip_len=3, frame_interval=1, num_clips=5, start_index=1)
SampleFrames(**config)

# Sample Frame with tail Frames
video_result = copy.deepcopy(self.video_results)
frame_result = copy.deepcopy(self.frame_results)
config = dict(
clip_len=3, frame_interval=1, num_clips=5, keep_tail_frames=True)
sample_frames = SampleFrames(**config)
sample_frames(video_result)
sample_frames(frame_result)

# Sample Frame with no temporal_jitter
# clip_len=3, frame_interval=1, num_clips=5
video_result = copy.deepcopy(self.video_results)
Expand Down