forked from okankop/Efficient-3DCNNs
-
Notifications
You must be signed in to change notification settings - Fork 0
/
temporal_transforms.py
134 lines (94 loc) · 3.61 KB
/
temporal_transforms.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
import random
import math
class LoopPadding(object):
def __init__(self, size, downsample):
self.size = size
self.downsample = downsample
def __call__(self, frame_indices):
vid_duration = len(frame_indices)
clip_duration = self.size * self.downsample
out = frame_indices
for index in out:
if len(out) >= clip_duration:
break
out.append(index)
selected_frames = [out[i] for i in range(0, clip_duration, self.downsample)]
return out
class TemporalBeginCrop(object):
"""Temporally crop the given frame indices at a beginning.
If the number of frames is less than the size,
loop the indices as many times as necessary to satisfy the size.
Args:
size (int): Desired output size of the crop.
"""
def __init__(self, size, downsample):
self.size = size
self.downsample = downsample
def __call__(self, frame_indices):
vid_duration = len(frame_indices)
clip_duration = self.size * self.downsample
out = frame_indices[:clip_duration]
for index in out:
if len(out) >= clip_duration:
break
out.append(index)
selected_frames = [out[i] for i in range(0, clip_duration, self.downsample)]
return selected_frames
class TemporalCenterCrop(object):
"""Temporally crop the given frame indices at a center.
If the number of frames is less than the size,
loop the indices as many times as necessary to satisfy the size.
Args:
size (int): Desired output size of the crop.
"""
def __init__(self, size, downsample):
self.size = size
self.downsample = downsample
def __call__(self, frame_indices):
"""
Args:
frame_indices (list): frame indices to be cropped.
Returns:
list: Cropped frame indices.
"""
vid_duration = len(frame_indices)
clip_duration = self.size * self.downsample
center_index = len(frame_indices) // 2
begin_index = max(0, center_index - (clip_duration // 2))
end_index = min(begin_index + clip_duration, vid_duration)
out = frame_indices[begin_index:end_index]
for index in out:
if len(out) >= clip_duration:
break
out.append(index)
selected_frames = [out[i] for i in range(0, clip_duration, self.downsample)]
return selected_frames
class TemporalRandomCrop(object):
"""Temporally crop the given frame indices at a random location.
If the number of frames is less than the size,
loop the indices as many times as necessary to satisfy the size.
Args:
size (int): Desired output size of the crop.
"""
def __init__(self, size, downsample):
self.size = size
self.downsample = downsample
def __call__(self, frame_indices):
"""
Args:
frame_indices (list): frame indices to be cropped.
Returns:
list: Cropped frame indices.
"""
vid_duration = len(frame_indices)
clip_duration = self.size * self.downsample
rand_end = max(0, vid_duration - clip_duration - 1)
begin_index = random.randint(0, rand_end)
end_index = min(begin_index + clip_duration, vid_duration)
out = frame_indices[begin_index:end_index]
for index in out:
if len(out) >= clip_duration:
break
out.append(index)
selected_frames = [out[i] for i in range(0, clip_duration, self.downsample)]
return selected_frames