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image_id
int64 0
6.12k
| image
imagewidth (px) 640
640
| width
int32 640
640
| height
int32 640
640
| objects
sequence |
|---|---|---|---|---|
1,162
| 640
| 640
|
{
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|
4,635
| 640
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3,597
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4,431
| 640
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4,334
| 640
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6,037
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10
| 640
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4,067
| 640
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1,253
| 640
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2,744
| 640
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2,039
| 640
| 640
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{
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|
5,353
| 640
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{
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1
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5,296
| 640
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{
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1
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|
5,162
| 640
| 640
|
{
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9171
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1
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|
4,085
| 640
| 640
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{
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[
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1
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|
1,610
| 640
| 640
|
{
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2458
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405768
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[
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636,
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1
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|
5,916
| 640
| 640
|
{
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[
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1
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|
4,296
| 640
| 640
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{
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367537
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[
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1
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|
1,803
| 640
| 640
|
{
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2722
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9171
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[
23,
389,
83,
110.5
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],
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1
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|
2,685
| 640
| 640
|
{
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4060
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5134
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[
466,
211,
63,
81.5
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1
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|
414
| 640
| 640
|
{
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665
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407682
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[
1,
1,
638.5,
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1
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|
5,134
| 640
| 640
|
{
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7949
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398112
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[
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638,
624
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1
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|
3,509
| 640
| 640
|
{
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5342
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10092
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[
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1
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|
1,911
| 640
| 640
|
{
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8545
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[
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81,
105.5
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1
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|
3,481
| 640
| 640
|
{
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1
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|
3,694
| 640
| 640
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{
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403.5
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1
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|
5,631
| 640
| 640
|
{
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8720
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11056
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[
40,
101,
91,
121.5
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1
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|
5,229
| 640
| 640
|
{
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|
5,609
| 640
| 640
|
{
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[
451,
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1
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} |
|
4,071
| 640
| 640
|
{
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6192
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363222
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[
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612,
593.5
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1
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} |
|
5,563
| 640
| 640
|
{
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8633
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7892
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[
320,
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77,
102.5
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1
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} |
|
4,275
| 640
| 640
|
{
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6542
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369648
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[
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1
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|
2,090
| 640
| 640
|
{
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3132
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7892
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[
247,
489,
77,
102.5
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1
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} |
|
2,218
| 640
| 640
|
{
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3310
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393754
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[
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626,
629
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],
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1
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|
3,309
| 640
| 640
|
{
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5001
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7500
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[
434,
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75,
100
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],
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1
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} |
|
851
| 640
| 640
|
{
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1286
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381300
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[
10,
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620,
615
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1
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} |
|
5,699
| 640
| 640
|
{
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8807
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7500
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[
555,
276,
75,
100
]
],
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1
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} |
|
1,057
| 640
| 640
|
{
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1614
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5622
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[
418,
9,
65,
86.5
]
],
"category": [
1
]
} |
|
1,863
| 640
| 640
|
{
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2830
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5292
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[
377,
246,
63,
84
]
],
"category": [
1
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} |
|
5,703
| 640
| 640
|
{
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8811
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395000
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[
6,
10,
632,
625
]
],
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1
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} |
|
391
| 640
| 640
|
{
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635
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378224
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"bbox": [
[
16,
17,
615.5,
614.5
]
],
"category": [
1
]
} |
|
3,785
| 640
| 640
|
{
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5766
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374544
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[
13,
17,
612,
612
]
],
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1
]
} |
|
291
| 640
| 640
|
{
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489
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399726
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[
4,
6,
636,
628.5
]
],
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1
]
} |
|
3,693
| 640
| 640
|
{
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5633
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5795
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[
398,
540,
67,
86.5
]
],
"category": [
1
]
} |
|
2,235
| 640
| 640
|
{
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3327
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11056
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"bbox": [
[
13,
152,
91,
121.5
]
],
"category": [
1
]
} |
|
790
| 640
| 640
|
{
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1192
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7500
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[
27,
48,
75,
100
]
],
"category": [
1
]
} |
|
231
| 640
| 640
|
{
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405
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9647
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"bbox": [
[
55,
368,
85,
113.5
]
],
"category": [
1
]
} |
|
5,669
| 640
| 640
|
{
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8769
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5996
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"bbox": [
[
165,
173,
67,
89.5
]
],
"category": [
1
]
} |
|
5,230
| 640
| 640
|
{
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8119
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379146
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"bbox": [
[
11,
13,
617,
614.5
]
],
"category": [
1
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} |
|
2,324
| 640
| 640
|
{
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3483
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398152
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"bbox": [
[
6,
6,
634,
628
]
],
"category": [
1
]
} |
|
85
| 640
| 640
|
{
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127,
128,
129,
130,
131,
132,
133,
134,
135,
136,
137
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7837,
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627,
5510,
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987,
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21420,
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251,
222,
29.5,
39.5
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[
310,
162,
75,
104.5
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[
127,
177,
57,
76.5
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[
331,
399,
22,
28.5
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[
236,
411,
51.5,
107
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[
112,
354,
81.5,
133
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[
358,
469,
23.5,
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[
448,
128,
87,
323.5
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[
283,
324,
49.5,
118
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[
384,
448,
46,
138.5
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[
370,
302,
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[
134,
285,
204,
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[
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320.5,
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2,
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2,
2,
2,
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2,
2
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} |
|
6,026
| 640
| 640
|
{
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7300
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[
353,
183,
73,
100
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],
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1
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} |
|
1,919
| 640
| 640
|
{
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2898
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5622
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[
189,
199,
65,
86.5
]
],
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1
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} |
|
3,210
| 640
| 640
|
{
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4876
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286442
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[
23,
70,
598,
479
]
],
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1
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} |
|
3,298
| 640
| 640
|
{
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4982
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10092
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[
261,
96,
87,
116
]
],
"category": [
1
]
} |
|
2,542
| 640
| 640
|
{
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3845
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9171
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"bbox": [
[
385,
248,
83,
110.5
]
],
"category": [
1
]
} |
|
1,160
| 640
| 640
|
{
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1743
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9647
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"bbox": [
[
20,
123,
85,
113.5
]
],
"category": [
1
]
} |
|
1,999
| 640
| 640
|
{
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2996
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407044
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"bbox": [
[
1,
2,
638,
638
]
],
"category": [
1
]
} |
|
2,164
| 640
| 640
|
{
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3256
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5996
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"bbox": [
[
463,
459,
67,
89.5
]
],
"category": [
1
]
} |
|
3,526
| 640
| 640
|
{
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5359
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7117
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"bbox": [
[
233,
343,
73,
97.5
]
],
"category": [
1
]
} |
|
4,376
| 640
| 640
|
{
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6666
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5622
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"bbox": [
[
208,
139,
65,
86.5
]
],
"category": [
1
]
} |
|
1,236
| 640
| 640
|
{
"id": [
1876
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407043
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"bbox": [
[
1,
3,
639,
637
]
],
"category": [
1
]
} |
|
5,508
| 640
| 640
|
{
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8557
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405130
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"bbox": [
[
5,
2,
635,
638
]
],
"category": [
1
]
} |
|
4,588
| 640
| 640
|
{
"id": [
7012
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359032
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"bbox": [
[
20,
23,
607.5,
591
]
],
"category": [
1
]
} |
|
1,800
| 640
| 640
|
{
"id": [
2719
],
"area": [
7500
],
"bbox": [
[
2,
218,
75,
100
]
],
"category": [
1
]
} |
|
1,729
| 640
| 640
|
{
"id": [
2624
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393126
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"bbox": [
[
7,
7,
628.5,
625.5
]
],
"category": [
1
]
} |
|
5,588
| 640
| 640
|
{
"id": [
8658
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"area": [
210325
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"bbox": [
[
96,
87,
447.5,
470
]
],
"category": [
2
]
} |
|
5,351
| 640
| 640
|
{
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8316
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395312
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"bbox": [
[
11,
3,
625,
632.5
]
],
"category": [
1
]
} |
|
5,747
| 640
| 640
|
{
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8880
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388901
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"bbox": [
[
20,
3,
611,
636.5
]
],
"category": [
1
]
} |
|
5,143
| 640
| 640
|
{
"id": [
7958
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404492
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"bbox": [
[
5,
2,
634,
638
]
],
"category": [
1
]
} |
|
2,806
| 640
| 640
|
{
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4229
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9171
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"bbox": [
[
138,
328,
83,
110.5
]
],
"category": [
1
]
} |
|
1,363
| 640
| 640
|
{
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2081
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398157
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"bbox": [
[
11,
7,
629,
633
]
],
"category": [
1
]
} |
|
6,027
| 640
| 640
|
{
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9290
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389996
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[
7,
7,
626.5,
622.5
]
],
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1
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} |
|
5,855
| 640
| 640
|
{
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9040
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363509
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[
32,
19,
593,
613
]
],
"category": [
1
]
} |
|
3,560
| 640
| 640
|
{
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5447
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5292
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[
498,
378,
63,
84
]
],
"category": [
1
]
} |
|
2,477
| 640
| 640
|
{
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3765
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389376
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[
9,
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949
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1,998
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5,376
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459
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2,926
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4,432
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4,953
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End of preview. Expand
in Data Studio
Dataset Card for coins-1apki
** The original COCO dataset is stored at dataset.tar.gz**
Dataset Summary
coins-1apki
Supported Tasks and Leaderboards
object-detection: The dataset can be used to train a model for Object Detection.
Languages
English
Dataset Structure
Data Instances
A data point comprises an image and its object annotations.
{
'image_id': 15,
'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=640x640 at 0x2373B065C18>,
'width': 964043,
'height': 640,
'objects': {
'id': [114, 115, 116, 117],
'area': [3796, 1596, 152768, 81002],
'bbox': [
[302.0, 109.0, 73.0, 52.0],
[810.0, 100.0, 57.0, 28.0],
[160.0, 31.0, 248.0, 616.0],
[741.0, 68.0, 202.0, 401.0]
],
'category': [4, 4, 0, 0]
}
}
Data Fields
image: the image idimage:PIL.Image.Imageobject containing the image. Note that when accessing the image column:dataset[0]["image"]the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the"image"column, i.e.dataset[0]["image"]should always be preferred overdataset["image"][0]width: the image widthheight: the image heightobjects: a dictionary containing bounding box metadata for the objects present on the imageid: the annotation idarea: the area of the bounding boxbbox: the object's bounding box (in the coco format)category: the object's category.
Who are the annotators?
Annotators are Roboflow users
Additional Information
Licensing Information
See original homepage https://universe.roboflow.com/object-detection/coins-1apki
Citation Information
@misc{ coins-1apki,
title = { coins 1apki Dataset },
type = { Open Source Dataset },
author = { Roboflow 100 },
howpublished = { \url{ https://universe.roboflow.com/object-detection/coins-1apki } },
url = { https://universe.roboflow.com/object-detection/coins-1apki },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { nov },
note = { visited on 2023-03-29 },
}"
Contributions
Thanks to @mariosasko for adding this dataset.
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