Datasets:
AIML-TUDA
/
COCOLogic-v2

Dataset card Data Studio Files
xet
 Community
rule_id
int8
rule_name
string
rule_sample_type
string
group_index
int8
group_position
int32
image_id
int64
image_index
int32
file_name
string
rule_label
int8
rule_variant_ids
list
rule_boundary_type
int8
labels
list
rule_variants
list
boundary_type
list
sample_type
list
category_counts
list
object_names
list
object_counts
list
n_objects
int32
1
Signal and Ride
positive
1
0
26,879
122
train2017/000000026879.jpg
1
[ 1 ]
0
[ 1, 0, 0, 1, 0, 0, 0, 0, 0, 0 ]
[ [ 1 ], [], [], [ 2 ], [], [], [], [], [], [] ]
[ 0, 0, 0, 0, 0, 2, 3, 2, 0, 0 ]
[ "positive", "far_from_boundary", "far_from_boundary", "positive", "far_from_boundary", "near_boundary", "near_boundary", "near_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 1, 2, 0, 0, 0, 0, 2, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "bicycle", "car", "truck", "traffic light", "fire hydrant" ]
[ 1, 2, 2, 1, 1 ]
7
1
Signal and Ride
positive
1
1
154,830
95
train2017/000000154830.jpg
1
[ 1 ]
0
[ 1, 0, 0, 1, 0, 0, 0, 0, 0, 0 ]
[ [ 1 ], [], [], [ 2 ], [], [], [], [], [], [] ]
[ 0, 0, 0, 0, 0, 1, 0, 2, 1, 2 ]
[ "positive", "far_from_boundary", "far_from_boundary", "positive", "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "near_boundary", "near_boundary" ]
[ 0, 3, 3, 3, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "bicycle", "car", "traffic light", "backpack" ]
[ 3, 3, 3, 5, 1 ]
15
1
Signal and Ride
positive
1
2
204,279
230
train2017/000000204279.jpg
1
[ 1 ]
0
[ 1, 0, 0, 1, 0, 0, 0, 0, 0, 0 ]
[ [ 1 ], [], [], [ 2 ], [], [], [], [], [], [] ]
[ 0, 0, 0, 0, 0, 0, 0, 2, 1, 2 ]
[ "positive", "far_from_boundary", "far_from_boundary", "positive", "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "near_boundary", "near_boundary" ]
[ 0, 2, 1, 1, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "bicycle", "car", "traffic light", "handbag" ]
[ 2, 1, 1, 3, 2 ]
9
1
Signal and Ride
positive
2
0
115,502
132
train2017/000000115502.jpg
1
[ 2 ]
0
[ 1, 0, 0, 1, 0, 0, 0, 0, 1, 0 ]
[ [ 2 ], [], [], [ 2 ], [], [], [], [], [ 2 ], [] ]
[ 0, 0, 0, 0, 0, 0, 0, 6, 0, 2 ]
[ "positive", "far_from_boundary", "far_from_boundary", "positive", "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "positive", "near_boundary" ]
[ 0, 4, 0, 1, 0, 0, 1, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "car", "bus", "traffic light" ]
[ 4, 1, 1, 5 ]
11
1
Signal and Ride
positive
2
1
488,403
210
train2017/000000488403.jpg
1
[ 2 ]
0
[ 1, 0, 0, 1, 0, 0, 0, 0, 0, 0 ]
[ [ 2 ], [], [], [ 2 ], [], [], [], [], [], [] ]
[ 0, 0, 0, 0, 0, 1, 3, 6, 4, 0 ]
[ "positive", "far_from_boundary", "far_from_boundary", "positive", "far_from_boundary", "near_boundary", "near_boundary", "near_boundary", "near_boundary", "far_from_boundary" ]
[ 0, 0, 0, 10, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
[ "car", "bus", "traffic light" ]
[ 10, 1, 1 ]
12
1
Signal and Ride
positive
2
2
493,806
111
train2017/000000493806.jpg
1
[ 2 ]
0
[ 1, 0, 0, 1, 0, 1, 0, 0, 1, 0 ]
[ [ 2 ], [], [], [ 2 ], [], [ 1 ], [], [], [ 2 ], [] ]
[ 0, 0, 0, 0, 0, 0, 0, 6, 0, 2 ]
[ "positive", "far_from_boundary", "far_from_boundary", "positive", "far_from_boundary", "positive", "far_from_boundary", "near_boundary", "positive", "near_boundary" ]
[ 0, 12, 0, 3, 0, 0, 1, 0, 1, 0, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
[ "person", "car", "bus", "truck", "traffic light" ]
[ 12, 3, 1, 1, 6 ]
23
1
Signal and Ride
positive
3
0
325,666
14
train2017/000000325666.jpg
1
[ 3 ]
0
[ 1, 0, 0, 1, 0, 1, 0, 1, 0, 0 ]
[ [ 3 ], [], [], [ 2 ], [], [ 1 ], [], [ 3 ], [], [] ]
[ 0, 0, 0, 0, 0, 0, 3, 0, 4, 0 ]
[ "positive", "far_from_boundary", "far_from_boundary", "positive", "far_from_boundary", "positive", "near_boundary", "positive", "near_boundary", "far_from_boundary" ]
[ 0, 0, 0, 11, 0, 0, 0, 1, 3, 0, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
[ "car", "train", "truck", "traffic light" ]
[ 11, 1, 3, 9 ]
24
1
Signal and Ride
positive
3
1
427,348
150
train2017/000000427348.jpg
1
[ 3 ]
0
[ 1, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [ 3 ], [], [], [], [], [], [], [], [], [] ]
[ 0, 0, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "positive", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "train", "traffic light" ]
[ 1, 1 ]
2
1
Signal and Ride
near_boundary
1
0
541,571
170
train2017/000000541571.jpg
0
[]
1
[ 0, 0, 0, 0, 0, 0, 0, 1, 0, 0 ]
[ [], [], [], [], [], [], [], [ 1 ], [], [] ]
[ 1, 1, 0, 2, 0, 0, 3, 0, 3, 0 ]
[ "near_boundary", "near_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "positive", "near_boundary", "far_from_boundary" ]
[ 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "bicycle", "bird", "bottle" ]
[ 1, 1, 1 ]
3
1
Signal and Ride
near_boundary
1
1
455,675
232
train2017/000000455675.jpg
0
[]
1
[ 0, 0, 0, 0, 0, 0, 0, 1, 1, 0 ]
[ [], [], [], [], [], [], [], [ 1 ], [ 1 ], [] ]
[ 1, 0, 0, 2, 0, 0, 0, 0, 0, 4 ]
[ "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "positive", "positive", "near_boundary" ]
[ 0, 6, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "bicycle", "backpack", "surfboard" ]
[ 6, 3, 1, 1 ]
11
1
Signal and Ride
near_boundary
1
2
58,464
45
train2017/000000058464.jpg
0
[]
1
[ 0, 0, 0, 1, 0, 0, 0, 1, 1, 0 ]
[ [], [], [], [ 1 ], [], [], [], [ 1 ], [ 1 ], [] ]
[ 1, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ "near_boundary", "far_from_boundary", "far_from_boundary", "positive", "far_from_boundary", "far_from_boundary", "far_from_boundary", "positive", "positive", "far_from_boundary" ]
[ 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "bicycle", "dog", "umbrella" ]
[ 1, 1, 1, 1 ]
4
1
Signal and Ride
near_boundary
2
0
32,681
190
train2017/000000032681.jpg
0
[]
2
[ 0, 0, 0, 0, 0, 0, 0, 1, 0, 0 ]
[ [], [], [], [], [], [], [], [ 4 ], [], [] ]
[ 2, 0, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "positive", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "bus" ]
[ 2 ]
2
1
Signal and Ride
near_boundary
2
1
93,586
177
train2017/000000093586.jpg
0
[]
2
[ 0, 0, 0, 0, 0, 0, 0, 1, 0, 0 ]
[ [], [], [], [], [], [], [], [ 4 ], [], [] ]
[ 2, 0, 0, 2, 0, 0, 0, 0, 2, 0 ]
[ "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "positive", "near_boundary", "far_from_boundary" ]
[ 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "bus" ]
[ 1, 1 ]
2
1
Signal and Ride
near_boundary
2
2
396,257
220
train2017/000000396257.jpg
0
[]
2
[ 0, 0, 0, 0, 0, 0, 0, 1, 0, 0 ]
[ [], [], [], [], [], [], [], [ 4 ], [], [] ]
[ 2, 0, 0, 2, 0, 0, 0, 0, 2, 2 ]
[ "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "positive", "near_boundary", "near_boundary" ]
[ 0, 6, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "bus", "bench", "backpack" ]
[ 6, 1, 1, 2 ]
10
1
Signal and Ride
near_boundary
3
0
290,261
212
train2017/000000290261.jpg
0
[]
3
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 3, 0, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "train" ]
[ 1 ]
1
1
Signal and Ride
near_boundary
3
1
417,242
216
train2017/000000417242.jpg
0
[]
3
[ 0, 0, 0, 1, 0, 0, 0, 1, 0, 0 ]
[ [], [], [], [ 2 ], [], [], [], [ 3 ], [], [] ]
[ 3, 0, 0, 0, 0, 2, 3, 0, 4, 0 ]
[ "near_boundary", "far_from_boundary", "far_from_boundary", "positive", "far_from_boundary", "near_boundary", "near_boundary", "positive", "near_boundary", "far_from_boundary" ]
[ 0, 0, 0, 2, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "car", "train", "truck" ]
[ 2, 1, 2 ]
5
1
Signal and Ride
near_boundary
3
2
447,524
16
train2017/000000447524.jpg
0
[]
3
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 3, 0, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "train" ]
[ 2 ]
2
1
Signal and Ride
near_boundary
4
0
512,923
179
train2017/000000512923.jpg
0
[]
4
[ 0, 0, 0, 1, 0, 0, 0, 1, 0, 0 ]
[ [], [], [], [ 2 ], [], [], [], [ 3 ], [], [] ]
[ 4, 0, 0, 0, 0, 2, 3, 0, 4, 0 ]
[ "near_boundary", "far_from_boundary", "far_from_boundary", "positive", "far_from_boundary", "near_boundary", "near_boundary", "positive", "near_boundary", "far_from_boundary" ]
[ 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "car", "truck", "traffic light" ]
[ 1, 1, 5 ]
7
1
Signal and Ride
near_boundary
4
1
100,087
117
train2017/000000100087.jpg
0
[]
4
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 4, 0, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "traffic light" ]
[ 3 ]
3
1
Signal and Ride
near_boundary
4
2
299,409
176
train2017/000000299409.jpg
0
[]
4
[ 0, 0, 0, 1, 0, 1, 0, 1, 0, 0 ]
[ [], [], [], [ 2 ], [], [ 1 ], [], [ 3 ], [], [] ]
[ 4, 0, 0, 0, 0, 0, 3, 0, 4, 0 ]
[ "near_boundary", "far_from_boundary", "far_from_boundary", "positive", "far_from_boundary", "positive", "near_boundary", "positive", "near_boundary", "far_from_boundary" ]
[ 0, 0, 0, 2, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "car", "truck", "traffic light" ]
[ 2, 1, 1 ]
4
1
Signal and Ride
far_from_boundary
0
0
104,002
32
train2017/000000104002.jpg
0
[]
0
[ 0, 0, 1, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [ 1 ], [], [], [], [], [], [], [] ]
[ 0, 0, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "positive", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 12, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
[ "cow" ]
[ 12 ]
12
1
Signal and Ride
far_from_boundary
0
1
156,943
126
train2017/000000156943.jpg
0
[]
0
[ 0, 0, 0, 0, 1, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [ 1 ], [], [], [], [], [] ]
[ 0, 0, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "positive", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 8, 0, 0, 0, 0, 4, 0, 0, 0...
[ "bowl", "orange", "donut", "dining table" ]
[ 3, 8, 4, 1 ]
16
1
Signal and Ride
far_from_boundary
0
2
221,095
188
train2017/000000221095.jpg
0
[]
0
[ 0, 0, 0, 0, 0, 0, 1, 0, 0, 0 ]
[ [], [], [], [], [], [], [ 2 ], [], [], [] ]
[ 0, 0, 0, 2, 0, 0, 0, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "positive", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0...
[ "surfboard", "chair", "laptop", "mouse" ]
[ 1, 3, 1, 1 ]
6
1
Signal and Ride
far_from_boundary
0
3
567,562
125
train2017/000000567562.jpg
0
[]
0
[ 0, 0, 0, 0, 1, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [ 2 ], [], [], [], [], [] ]
[ 0, 4, 0, 2, 0, 0, 2, 0, 2, 2 ]
[ "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "positive", "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "near_boundary" ]
[ 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0, 3, 1, 0, 3, 1, 0, 0, 0, 0, 3, 0, 0, 4, 0, 0, 2, 0...
[ "person", "bottle", "cup", "fork", "spoon", "bowl", "broccoli", "pizza", "chair", "dining table", "book" ]
[ 3, 6, 3, 1, 3, 1, 3, 4, 2, 1, 13 ]
40
2
Double Serving
positive
1
0
486,306
184
train2017/000000486306.jpg
1
[ 1 ]
0
[ 0, 1, 0, 0, 1, 0, 0, 0, 0, 0 ]
[ [], [ 1 ], [], [], [ 2 ], [], [], [], [], [] ]
[ 0, 0, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "positive", "far_from_boundary", "near_boundary", "positive", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 3, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "bottle", "cup", "knife", "spoon", "scissors" ]
[ 4, 3, 1, 2, 1 ]
11
2
Double Serving
positive
1
1
113,139
226
train2017/000000113139.jpg
1
[ 1 ]
0
[ 0, 1, 0, 0, 0, 0, 1, 0, 0, 0 ]
[ [], [ 1 ], [], [], [], [], [ 2 ], [], [], [] ]
[ 0, 0, 0, 2, 1, 0, 0, 0, 0, 0 ]
[ "far_from_boundary", "positive", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "positive", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 2, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0...
[ "bottle", "wine glass", "cup", "chair", "dining table" ]
[ 4, 2, 1, 1, 1 ]
9
2
Double Serving
positive
1
2
154,590
218
train2017/000000154590.jpg
1
[ 1 ]
0
[ 0, 1, 0, 0, 1, 0, 0, 0, 0, 0 ]
[ [], [ 1 ], [], [], [ 1 ], [], [], [], [], [] ]
[ 0, 0, 0, 2, 0, 0, 0, 0, 2, 2 ]
[ "far_from_boundary", "positive", "far_from_boundary", "near_boundary", "positive", "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "near_boundary" ]
[ 0, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 9, 9, 0, 0, 0, 3, 0, 0, 1, 0, 0, 0, 0, 0, 0, 3, 0, 0...
[ "person", "bottle", "wine glass", "cup", "bowl", "sandwich", "cake", "dining table", "cell phone" ]
[ 6, 2, 9, 9, 3, 1, 3, 1, 1 ]
35
2
Double Serving
positive
2
0
72,817
52
train2017/000000072817.jpg
1
[ 2 ]
0
[ 0, 1, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [ 2 ], [], [], [], [], [], [], [], [] ]
[ 0, 0, 0, 2, 3, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "positive", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0...
[ "bottle", "bowl", "pizza", "dining table" ]
[ 1, 1, 1, 1 ]
4
2
Double Serving
positive
2
1
503,148
163
train2017/000000503148.jpg
1
[ 2 ]
0
[ 0, 1, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [ 2 ], [], [], [], [], [], [], [], [] ]
[ 0, 0, 0, 2, 0, 0, 0, 0, 2, 0 ]
[ "far_from_boundary", "positive", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary" ]
[ 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0...
[ "person", "bottle", "pizza" ]
[ 1, 1, 1 ]
3
2
Double Serving
positive
2
2
518,267
58
train2017/000000518267.jpg
1
[ 2 ]
0
[ 0, 1, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [ 2 ], [], [], [], [], [], [], [], [] ]
[ 0, 0, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "positive", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0...
[ "bottle", "wine glass", "fork", "knife", "pizza", "dining table" ]
[ 1, 1, 1, 1, 4, 1 ]
9
2
Double Serving
positive
3
0
59,526
64
train2017/000000059526.jpg
1
[ 3 ]
0
[ 0, 1, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [ 3 ], [], [], [], [], [], [], [], [] ]
[ 0, 0, 0, 2, 1, 0, 0, 0, 2, 2 ]
[ "far_from_boundary", "positive", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "near_boundary" ]
[ 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0...
[ "person", "cup", "pizza" ]
[ 3, 2, 1 ]
6
2
Double Serving
positive
3
1
230,265
166
train2017/000000230265.jpg
1
[ 3 ]
0
[ 0, 1, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [ 3 ], [], [], [], [], [], [], [], [] ]
[ 0, 0, 0, 2, 2, 0, 2, 0, 2, 2 ]
[ "far_from_boundary", "positive", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "near_boundary" ]
[ 0, 12, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 6, 1, 3, 1, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 11, ...
[ "person", "handbag", "wine glass", "cup", "fork", "knife", "spoon", "pizza", "chair", "dining table", "clock" ]
[ 12, 1, 1, 6, 1, 3, 1, 2, 11, 3, 1 ]
42
2
Double Serving
near_boundary
1
0
96,711
204
train2017/000000096711.jpg
0
[]
1
[ 0, 0, 0, 0, 0, 0, 0, 1, 1, 0 ]
[ [], [], [], [], [], [], [], [ 1 ], [ 1 ], [] ]
[ 1, 1, 0, 2, 0, 0, 0, 0, 0, 2 ]
[ "near_boundary", "near_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "positive", "positive", "near_boundary" ]
[ 0, 8, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "bicycle", "bench", "handbag", "bottle", "sandwich" ]
[ 8, 5, 2, 2, 2, 1 ]
20
2
Double Serving
near_boundary
1
1
334,777
198
train2017/000000334777.jpg
0
[]
1
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 0, 1, 0, 2, 4, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0...
[ "bottle", "bowl", "broccoli", "carrot", "dining table" ]
[ 1, 6, 1, 1, 1 ]
10
2
Double Serving
near_boundary
1
2
410,436
144
train2017/000000410436.jpg
0
[]
1
[ 0, 0, 0, 0, 0, 0, 1, 0, 0, 0 ]
[ [], [], [], [], [], [], [ 2 ], [], [], [] ]
[ 0, 1, 0, 2, 0, 0, 0, 0, 0, 0 ]
[ "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "positive", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0...
[ "bottle", "chair", "potted plant", "tv", "mouse", "keyboard", "cell phone" ]
[ 1, 1, 1, 2, 1, 1, 1 ]
8
2
Double Serving
near_boundary
2
0
43,560
18
train2017/000000043560.jpg
0
[]
2
[ 0, 0, 0, 0, 1, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [ 2 ], [], [], [], [], [] ]
[ 0, 2, 0, 2, 0, 0, 0, 0, 2, 2 ]
[ "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "positive", "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "near_boundary" ]
[ 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 1, 0, 2, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "cup", "fork", "spoon", "apple", "dining table" ]
[ 3, 3, 1, 2, 2, 1 ]
12
2
Double Serving
near_boundary
2
1
533,220
104
train2017/000000533220.jpg
0
[]
2
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 0, 2, 0, 2, 2, 0, 2, 0, 2, 2 ]
[ "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "near_boundary" ]
[ 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 13, ...
[ "person", "cup", "chair", "potted plant", "dining table" ]
[ 4, 4, 13, 3, 5 ]
29
2
Double Serving
near_boundary
2
2
324,829
100
train2017/000000324829.jpg
0
[]
2
[ 0, 0, 0, 0, 1, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [ 2 ], [], [], [], [], [] ]
[ 0, 2, 0, 2, 0, 0, 2, 0, 2, 0 ]
[ "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "positive", "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "far_from_boundary" ]
[ 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 2, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0...
[ "person", "cup", "fork", "knife", "chair", "dining table" ]
[ 1, 3, 2, 4, 1, 1 ]
12
2
Double Serving
near_boundary
3
0
95,349
55
train2017/000000095349.jpg
0
[]
3
[ 0, 0, 0, 0, 1, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [ 1 ], [], [], [], [], [] ]
[ 0, 3, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "positive", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 3, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0...
[ "spoon", "bowl", "pizza", "dining table" ]
[ 1, 3, 2, 1 ]
7
2
Double Serving
near_boundary
3
1
10,217
222
train2017/000000010217.jpg
0
[]
3
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 0, 3, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0...
[ "pizza", "mouse" ]
[ 1, 1 ]
2
2
Double Serving
near_boundary
3
2
103,280
164
train2017/000000103280.jpg
0
[]
3
[ 0, 0, 0, 0, 1, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [ 1 ], [], [], [], [], [] ]
[ 0, 3, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "positive", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0...
[ "bowl", "pizza", "dining table" ]
[ 3, 1, 1 ]
5
2
Double Serving
near_boundary
4
0
78,858
2
train2017/000000078858.jpg
0
[]
4
[ 0, 0, 0, 0, 1, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [ 2 ], [], [], [], [], [] ]
[ 0, 4, 0, 2, 0, 0, 2, 0, 2, 2 ]
[ "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "positive", "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "near_boundary" ]
[ 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 3, 2, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 5, 0...
[ "person", "bottle", "cup", "fork", "knife", "pizza", "chair", "dining table" ]
[ 3, 3, 3, 2, 3, 1, 5, 1 ]
21
2
Double Serving
near_boundary
4
1
214,924
174
train2017/000000214924.jpg
0
[]
4
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 0, 4, 0, 2, 1, 0, 2, 0, 2, 2 ]
[ "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "near_boundary" ]
[ 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 2, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0...
[ "person", "bottle", "cup", "fork", "spoon", "pizza", "chair", "potted plant", "dining table" ]
[ 2, 1, 2, 1, 1, 1, 1, 2, 2 ]
13
2
Double Serving
near_boundary
4
2
556,039
1
train2017/000000556039.jpg
0
[]
4
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 0, 4, 0, 2, 2, 0, 2, 0, 2, 0 ]
[ "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "far_from_boundary" ]
[ 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 1, 5, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0...
[ "person", "bottle", "wine glass", "cup", "fork", "spoon", "pizza", "chair" ]
[ 1, 5, 1, 5, 1, 1, 1, 1 ]
16
2
Double Serving
far_from_boundary
0
0
87,264
102
train2017/000000087264.jpg
0
[]
0
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 0, 0, 2, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "cow", "clock" ]
[ 1, 1 ]
2
2
Double Serving
far_from_boundary
0
1
185,360
4
train2017/000000185360.jpg
0
[]
0
[ 0, 0, 0, 1, 0, 0, 0, 1, 0, 0 ]
[ [], [], [], [ 2 ], [], [], [], [ 3 ], [], [] ]
[ 0, 0, 2, 0, 0, 0, 3, 0, 4, 0 ]
[ "far_from_boundary", "far_from_boundary", "near_boundary", "positive", "far_from_boundary", "far_from_boundary", "near_boundary", "positive", "near_boundary", "far_from_boundary" ]
[ 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "car", "cow" ]
[ 1, 1 ]
2
2
Double Serving
far_from_boundary
0
2
308,172
205
train2017/000000308172.jpg
0
[]
0
[ 0, 0, 0, 0, 0, 0, 0, 1, 1, 0 ]
[ [], [], [], [], [], [], [], [ 1 ], [ 1 ], [] ]
[ 1, 0, 0, 2, 0, 0, 0, 0, 0, 2 ]
[ "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "positive", "positive", "near_boundary" ]
[ 0, 6, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "bicycle", "skateboard" ]
[ 6, 1, 3 ]
10
2
Double Serving
far_from_boundary
0
3
396,550
124
train2017/000000396550.jpg
0
[]
0
[ 0, 0, 1, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [ 3 ], [], [], [], [], [], [], [] ]
[ 0, 0, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "positive", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "sheep" ]
[ 9 ]
9
3
Herd Alone
positive
1
0
140,500
97
train2017/000000140500.jpg
1
[ 1 ]
0
[ 0, 0, 1, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [ 1 ], [], [], [], [], [], [], [] ]
[ 0, 0, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "positive", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "boat", "cow" ]
[ 1, 4 ]
5
3
Herd Alone
positive
1
1
323,396
145
train2017/000000323396.jpg
1
[ 1 ]
0
[ 0, 0, 1, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [ 1 ], [], [], [], [], [], [], [] ]
[ 0, 0, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "positive", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "cow" ]
[ 2 ]
2
3
Herd Alone
positive
1
2
489,391
192
train2017/000000489391.jpg
1
[ 1 ]
0
[ 0, 0, 1, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [ 1 ], [], [], [], [], [], [], [] ]
[ 0, 0, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "positive", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "cow" ]
[ 2 ]
2
3
Herd Alone
positive
2
0
125,853
181
train2017/000000125853.jpg
1
[ 2 ]
0
[ 0, 0, 1, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [ 2 ], [], [], [], [], [], [], [] ]
[ 0, 0, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "positive", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 12, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
[ "elephant" ]
[ 12 ]
12
3
Herd Alone
positive
2
1
136,542
155
train2017/000000136542.jpg
1
[ 2 ]
0
[ 0, 0, 1, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [ 2 ], [], [], [], [], [], [], [] ]
[ 0, 0, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "positive", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "elephant" ]
[ 4 ]
4
3
Herd Alone
positive
2
2
358,425
7
train2017/000000358425.jpg
1
[ 2 ]
0
[ 0, 0, 1, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [ 2 ], [], [], [], [], [], [], [] ]
[ 0, 0, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "positive", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "elephant" ]
[ 2 ]
2
3
Herd Alone
positive
3
0
31,451
98
train2017/000000031451.jpg
1
[ 3 ]
0
[ 0, 0, 1, 1, 0, 0, 0, 1, 0, 0 ]
[ [], [], [ 3 ], [ 2 ], [], [], [], [ 3 ], [], [] ]
[ 0, 0, 0, 0, 0, 1, 3, 0, 4, 0 ]
[ "far_from_boundary", "far_from_boundary", "positive", "positive", "far_from_boundary", "near_boundary", "near_boundary", "positive", "near_boundary", "far_from_boundary" ]
[ 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "car", "horse", "sheep" ]
[ 3, 1, 3 ]
7
3
Herd Alone
positive
3
1
48,421
131
train2017/000000048421.jpg
1
[ 3 ]
0
[ 0, 0, 1, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [ 3 ], [], [], [], [], [], [], [] ]
[ 0, 0, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "positive", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "sheep" ]
[ 2 ]
2
3
Herd Alone
near_boundary
1
0
145,259
162
train2017/000000145259.jpg
0
[]
1
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 0, 0, 1, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "elephant" ]
[ 1 ]
1
3
Herd Alone
near_boundary
1
1
149,151
74
train2017/000000149151.jpg
0
[]
1
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 0, 0, 1, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "elephant" ]
[ 1 ]
1
3
Herd Alone
near_boundary
2
0
191,681
89
train2017/000000191681.jpg
0
[]
2
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 0, 0, 2, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "bird", "cow" ]
[ 3, 1 ]
4
3
Herd Alone
near_boundary
2
1
201,064
161
train2017/000000201064.jpg
0
[]
2
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 0, 0, 2, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "bird", "cow" ]
[ 1, 1 ]
2
3
Herd Alone
near_boundary
3
0
273,052
71
train2017/000000273052.jpg
0
[]
3
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 0, 0, 3, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "sheep" ]
[ 1 ]
1
3
Herd Alone
near_boundary
3
1
563,381
81
train2017/000000563381.jpg
0
[]
3
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 0, 0, 3, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "sheep" ]
[ 1 ]
1
3
Herd Alone
near_boundary
4
0
297,514
20
train2017/000000297514.jpg
0
[]
4
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 0, 0, 4, 2, 0, 0, 0, 0, 2, 2 ]
[ "far_from_boundary", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "near_boundary" ]
[ 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "elephant" ]
[ 5, 4 ]
9
3
Herd Alone
near_boundary
4
1
295,162
119
train2017/000000295162.jpg
0
[]
4
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 0, 0, 4, 2, 0, 0, 0, 0, 2, 0 ]
[ "far_from_boundary", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary" ]
[ 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "elephant" ]
[ 1, 2 ]
3
3
Herd Alone
near_boundary
5
0
549,936
23
train2017/000000549936.jpg
0
[]
5
[ 0, 0, 0, 0, 0, 0, 0, 1, 1, 0 ]
[ [], [], [], [], [], [], [], [ 3 ], [ 2 ], [] ]
[ 0, 0, 5, 1, 0, 2, 0, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "positive", "positive", "far_from_boundary" ]
[ 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 13, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
[ "person", "car", "truck", "dog", "cow" ]
[ 1, 1, 1, 2, 13 ]
18
3
Herd Alone
near_boundary
5
1
246,064
133
train2017/000000246064.jpg
0
[]
5
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 0, 0, 5, 2, 0, 0, 0, 0, 2, 0 ]
[ "far_from_boundary", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary" ]
[ 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "cow" ]
[ 1, 3 ]
4
3
Herd Alone
near_boundary
6
0
11,802
8
train2017/000000011802.jpg
0
[]
6
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 0, 0, 6, 2, 0, 0, 0, 0, 2, 2 ]
[ "far_from_boundary", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "near_boundary" ]
[ 0, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "sheep" ]
[ 9, 7 ]
16
3
Herd Alone
near_boundary
6
1
77,693
168
train2017/000000077693.jpg
0
[]
6
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 0, 0, 6, 2, 0, 0, 0, 0, 2, 2 ]
[ "far_from_boundary", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "near_boundary" ]
[ 0, 13, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
[ "person", "sheep" ]
[ 13, 7 ]
20
3
Herd Alone
far_from_boundary
0
0
200,003
143
train2017/000000200003.jpg
0
[]
0
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 1 ]
[ [], [], [], [], [], [], [], [], [], [ 1 ] ]
[ 0, 0, 0, 2, 0, 0, 0, 0, 2, 0 ]
[ "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "positive" ]
[ 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "surfboard" ]
[ 2, 2 ]
4
3
Herd Alone
far_from_boundary
0
1
293,276
180
train2017/000000293276.jpg
0
[]
0
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 0, 0, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "cat", "bed" ]
[ 1, 1 ]
2
3
Herd Alone
far_from_boundary
0
2
334,301
217
train2017/000000334301.jpg
0
[]
0
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 1 ]
[ [], [], [], [], [], [], [], [], [], [ 1 ] ]
[ 0, 0, 0, 2, 0, 0, 0, 0, 2, 0 ]
[ "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "positive" ]
[ 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "surfboard" ]
[ 1, 1 ]
2
3
Herd Alone
far_from_boundary
0
3
458,958
96
train2017/000000458958.jpg
0
[]
0
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 3, 0, 0, 2, 0, 0, 0, 0, 2, 2 ]
[ "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "near_boundary" ]
[ 0, 4, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "train" ]
[ 4, 1 ]
5
4
Either Dog or Car
positive
1
0
254,228
127
train2017/000000254228.jpg
1
[ 1 ]
0
[ 0, 0, 0, 1, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [ 1 ], [], [], [], [], [], [] ]
[ 0, 0, 2, 0, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "near_boundary", "positive", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "dog", "cow" ]
[ 1, 1 ]
2
4
Either Dog or Car
positive
1
1
296,700
120
train2017/000000296700.jpg
1
[ 1 ]
0
[ 0, 0, 0, 1, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [ 1 ], [], [], [], [], [], [] ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 2, 0 ]
[ "far_from_boundary", "far_from_boundary", "far_from_boundary", "positive", "far_from_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary" ]
[ 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "dog", "cell phone" ]
[ 1, 1, 1 ]
3
4
Either Dog or Car
positive
1
2
497,494
152
train2017/000000497494.jpg
1
[ 1 ]
0
[ 0, 1, 0, 1, 0, 0, 0, 0, 0, 0 ]
[ [], [ 1 ], [], [ 1 ], [], [], [], [], [], [] ]
[ 0, 0, 0, 0, 1, 0, 0, 0, 2, 0 ]
[ "far_from_boundary", "positive", "far_from_boundary", "positive", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary" ]
[ 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "dog", "bottle", "cup", "spoon", "bowl", "bed", "remote" ]
[ 1, 1, 1, 1, 1, 1, 1, 2 ]
9
4
Either Dog or Car
positive
1
3
404,163
91
train2017/000000404163.jpg
1
[ 1 ]
0
[ 0, 0, 0, 1, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [ 1 ], [], [], [], [], [], [] ]
[ 0, 1, 0, 0, 0, 0, 2, 0, 2, 2 ]
[ "far_from_boundary", "near_boundary", "far_from_boundary", "positive", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "near_boundary" ]
[ 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0...
[ "person", "bench", "dog", "bottle", "chair", "potted plant", "dining table", "book" ]
[ 3, 1, 1, 5, 4, 2, 1, 11 ]
28
4
Either Dog or Car
positive
2
0
185,844
227
train2017/000000185844.jpg
1
[ 2 ]
0
[ 1, 0, 0, 1, 0, 1, 0, 0, 1, 0 ]
[ [ 2 ], [], [], [ 2 ], [], [ 1 ], [], [], [ 2 ], [] ]
[ 0, 0, 0, 0, 0, 0, 0, 6, 0, 2 ]
[ "positive", "far_from_boundary", "far_from_boundary", "positive", "far_from_boundary", "positive", "far_from_boundary", "near_boundary", "positive", "near_boundary" ]
[ 0, 7, 0, 9, 0, 0, 1, 0, 4, 0, 3, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "car", "bus", "truck", "traffic light", "bench" ]
[ 7, 9, 1, 4, 3, 1 ]
25
4
Either Dog or Car
positive
2
1
506,782
182
train2017/000000506782.jpg
1
[ 2 ]
0
[ 0, 0, 0, 1, 0, 0, 0, 1, 0, 0 ]
[ [], [], [], [ 2 ], [], [], [], [ 3 ], [], [] ]
[ 0, 0, 0, 0, 0, 0, 3, 0, 4, 0 ]
[ "far_from_boundary", "far_from_boundary", "far_from_boundary", "positive", "far_from_boundary", "far_from_boundary", "near_boundary", "positive", "near_boundary", "far_from_boundary" ]
[ 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "car", "cat" ]
[ 1, 1 ]
2
4
Either Dog or Car
positive
2
2
347,715
33
train2017/000000347715.jpg
1
[ 2 ]
0
[ 0, 0, 0, 1, 0, 1, 0, 1, 1, 0 ]
[ [], [], [], [ 2 ], [], [ 1 ], [], [ 3 ], [ 2 ], [] ]
[ 4, 0, 0, 0, 0, 0, 0, 0, 0, 2 ]
[ "near_boundary", "far_from_boundary", "far_from_boundary", "positive", "far_from_boundary", "positive", "far_from_boundary", "positive", "positive", "near_boundary" ]
[ 0, 2, 0, 7, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "car", "truck", "traffic light", "parking meter" ]
[ 2, 7, 1, 1, 9 ]
20
4
Either Dog or Car
positive
2
3
253,444
0
train2017/000000253444.jpg
1
[ 2 ]
0
[ 0, 0, 1, 1, 0, 0, 0, 1, 0, 0 ]
[ [], [], [ 2 ], [ 2 ], [], [], [], [ 3 ], [], [] ]
[ 0, 0, 0, 0, 0, 0, 3, 0, 4, 0 ]
[ "far_from_boundary", "far_from_boundary", "positive", "positive", "far_from_boundary", "far_from_boundary", "near_boundary", "positive", "near_boundary", "far_from_boundary" ]
[ 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "car", "elephant", "zebra" ]
[ 1, 2, 3 ]
6
4
Either Dog or Car
near_boundary
1
0
351,840
46
train2017/000000351840.jpg
0
[]
1
[ 0, 0, 0, 0, 0, 1, 0, 1, 0, 0 ]
[ [], [], [], [], [], [ 1 ], [], [ 3 ], [], [] ]
[ 0, 0, 0, 1, 0, 0, 3, 0, 4, 0 ]
[ "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "positive", "near_boundary", "positive", "near_boundary", "far_from_boundary" ]
[ 0, 0, 0, 2, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "car", "truck", "dog" ]
[ 2, 1, 1 ]
4
4
Either Dog or Car
near_boundary
1
1
137,150
201
train2017/000000137150.jpg
0
[]
1
[ 0, 0, 0, 0, 0, 0, 0, 1, 1, 0 ]
[ [], [], [], [], [], [], [], [ 3 ], [ 2 ], [] ]
[ 0, 0, 0, 1, 0, 2, 0, 0, 0, 2 ]
[ "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "positive", "positive", "near_boundary" ]
[ 0, 5, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "car", "truck", "dog", "cow", "banana" ]
[ 5, 1, 1, 2, 1, 6 ]
16
4
Either Dog or Car
near_boundary
1
2
153,692
43
train2017/000000153692.jpg
0
[]
1
[ 1, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [ 1 ], [], [], [], [], [], [], [], [], [] ]
[ 0, 0, 0, 1, 0, 1, 0, 2, 1, 0 ]
[ "positive", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary" ]
[ 0, 1, 1, 10, 0, 0, 0, 0, 0, 0, 11, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
[ "person", "bicycle", "car", "traffic light", "dog", "backpack" ]
[ 1, 1, 10, 11, 1, 1 ]
25
4
Either Dog or Car
near_boundary
1
3
229,105
113
train2017/000000229105.jpg
0
[]
1
[ 0, 0, 0, 0, 0, 1, 0, 1, 1, 0 ]
[ [], [], [], [], [], [ 1 ], [], [ 3 ], [ 2 ], [] ]
[ 0, 0, 0, 1, 0, 0, 0, 0, 0, 2 ]
[ "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "positive", "far_from_boundary", "positive", "positive", "near_boundary" ]
[ 0, 3, 0, 5, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "car", "truck", "dog" ]
[ 3, 5, 3, 1 ]
12
4
Either Dog or Car
near_boundary
1
4
339,852
175
train2017/000000339852.jpg
0
[]
1
[ 0, 0, 0, 0, 0, 0, 0, 1, 0, 0 ]
[ [], [], [], [], [], [], [], [ 3 ], [], [] ]
[ 0, 0, 0, 1, 0, 0, 3, 0, 4, 0 ]
[ "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "positive", "near_boundary", "far_from_boundary" ]
[ 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "car", "dog" ]
[ 1, 1 ]
2
4
Either Dog or Car
near_boundary
1
5
389,410
130
train2017/000000389410.jpg
0
[]
1
[ 0, 0, 0, 0, 0, 0, 0, 1, 0, 0 ]
[ [], [], [], [], [], [], [], [ 3 ], [], [] ]
[ 0, 0, 0, 1, 0, 0, 3, 0, 4, 0 ]
[ "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "positive", "near_boundary", "far_from_boundary" ]
[ 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "car", "dog" ]
[ 1, 2 ]
3
4
Either Dog or Car
near_boundary
1
6
116,663
196
train2017/000000116663.jpg
0
[]
1
[ 0, 0, 0, 0, 0, 0, 0, 1, 1, 0 ]
[ [], [], [], [], [], [], [], [ 3 ], [ 2 ], [] ]
[ 4, 0, 0, 1, 0, 1, 0, 0, 0, 2 ]
[ "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "positive", "positive", "near_boundary" ]
[ 0, 2, 0, 4, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "car", "traffic light", "parking meter", "dog", "book" ]
[ 2, 4, 2, 1, 3, 1 ]
13
4
Either Dog or Car
near_boundary
1
7
558,826
107
train2017/000000558826.jpg
0
[]
1
[ 0, 0, 0, 0, 0, 0, 0, 1, 1, 0 ]
[ [], [], [], [], [], [], [], [ 3 ], [ 2 ], [] ]
[ 0, 0, 0, 1, 0, 1, 0, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "positive", "positive", "far_from_boundary" ]
[ 0, 1, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "car", "dog", "umbrella", "book" ]
[ 1, 2, 1, 1, 1 ]
6
4
Either Dog or Car
near_boundary
2
0
29,075
178
train2017/000000029075.jpg
0
[]
2
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 0, 0, 4, 2, 0, 0, 0, 0, 2, 2 ]
[ "far_from_boundary", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "near_boundary" ]
[ 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 13, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
[ "person", "elephant" ]
[ 4, 13 ]
17
4
Either Dog or Car
near_boundary
2
1
96,500
116
train2017/000000096500.jpg
0
[]
2
[ 0, 1, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [ 3 ], [], [], [], [], [], [], [], [] ]
[ 0, 0, 0, 2, 2, 0, 2, 0, 2, 2 ]
[ "far_from_boundary", "positive", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "near_boundary" ]
[ 0, 13, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 13, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 7, ...
[ "person", "handbag", "cup", "fork", "pizza", "chair", "dining table" ]
[ 13, 1, 13, 1, 7, 7, 3 ]
45
4
Either Dog or Car
near_boundary
2
2
146,078
73
train2017/000000146078.jpg
0
[]
2
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 0, 2, 0, 2, 2, 0, 2, 0, 2, 2 ]
[ "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "near_boundary" ]
[ 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 0, 4, 1, 10, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, ...
[ "person", "cup", "knife", "spoon", "bowl", "chair", "potted plant", "dining table", "oven", "refrigerator", "book", "vase" ]
[ 2, 6, 4, 1, 10, 2, 1, 1, 1, 1, 1, 1 ]
31
4
Either Dog or Car
near_boundary
2
3
164,587
108
train2017/000000164587.jpg
0
[]
2
[ 0, 0, 0, 0, 1, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [ 1 ], [], [], [], [], [] ]
[ 0, 2, 0, 2, 0, 0, 0, 0, 2, 0 ]
[ "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "positive", "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary" ]
[ 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "cup", "bowl", "tv", "oven" ]
[ 1, 1, 3, 1, 1 ]
7
4
Either Dog or Car
near_boundary
2
4
174,932
151
train2017/000000174932.jpg
0
[]
2
[ 0, 0, 1, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [ 2 ], [], [], [], [], [], [], [] ]
[ 0, 0, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "positive", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "elephant" ]
[ 2 ]
2
4
Either Dog or Car
near_boundary
2
5
229,837
206
train2017/000000229837.jpg
0
[]
2
[ 0, 1, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [ 1 ], [], [], [], [], [], [], [], [] ]
[ 0, 0, 0, 2, 1, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "positive", "far_from_boundary", "near_boundary", "near_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 1, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "bottle", "cup", "bowl", "toaster" ]
[ 7, 1, 4, 1 ]
13
4
Either Dog or Car
near_boundary
2
6
207,097
118
train2017/000000207097.jpg
0
[]
2
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [], [], [], [], [], [] ]
[ 0, 0, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "zebra" ]
[ 3 ]
3
4
Either Dog or Car
near_boundary
2
7
478,007
138
train2017/000000478007.jpg
0
[]
2
[ 0, 0, 0, 0, 0, 0, 1, 0, 0, 0 ]
[ [], [], [], [], [], [], [ 1 ], [], [], [] ]
[ 0, 0, 0, 2, 0, 0, 0, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "positive", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1...
[ "couch", "sink" ]
[ 1, 1 ]
2
5
Three of a Kind
positive
1
0
38,046
75
train2017/000000038046.jpg
1
[ 1 ]
0
[ 0, 0, 0, 0, 1, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [ 1 ], [], [], [], [], [] ]
[ 0, 0, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "positive", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 11, 0, 4, 0, 0, 0, 0, 0, ...
[ "bowl", "orange", "carrot" ]
[ 3, 11, 4 ]
18
5
Three of a Kind
positive
1
1
536,369
134
train2017/000000536369.jpg
1
[ 1 ]
0
[ 0, 0, 0, 0, 1, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [ 1 ], [], [], [], [], [] ]
[ 0, 0, 0, 2, 0, 0, 3, 0, 0, 0 ]
[ "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "positive", "far_from_boundary", "near_boundary", "far_from_boundary", "far_from_boundary", "far_from_boundary" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "bowl", "oven" ]
[ 3, 2 ]
5
5
Three of a Kind
positive
1
2
275,900
199
train2017/000000275900.jpg
1
[ 1 ]
0
[ 0, 0, 0, 0, 1, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [ 1 ], [], [], [], [], [] ]
[ 0, 0, 0, 2, 0, 0, 0, 0, 2, 0 ]
[ "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "positive", "far_from_boundary", "far_from_boundary", "far_from_boundary", "near_boundary", "far_from_boundary" ]
[ 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
[ "person", "fork", "spoon", "bowl", "dining table" ]
[ 1, 1, 1, 3, 1 ]
7
5
Three of a Kind
positive
1
3
467,411
211
train2017/000000467411.jpg
1
[ 1 ]
0
[ 0, 0, 0, 0, 1, 0, 0, 0, 0, 0 ]
[ [], [], [], [], [ 1 ], [], [], [], [], [] ]
[ 0, 2, 0, 2, 0, 0, 2, 0, 2, 2 ]
[ "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "positive", "far_from_boundary", "near_boundary", "far_from_boundary", "near_boundary", "near_boundary" ]
[ 0, 12, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 3, 0, 5, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8, ...
[ "person", "bench", "cup", "fork", "spoon", "bowl", "chair", "dining table" ]
[ 12, 1, 2, 3, 5, 3, 8, 1 ]
35