image_id
int32
0
71
image
image
mask
image
shapes
string
7
"[{'type': 'box', 'label': 'BALL', 'points': [(665.36, 570.7), (868.95, 779.51)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
3
"[{'type': 'box', 'label': 'BALL', 'points': [(870.4, 446.1), (1085.8, 699.61)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
1
"[{'type': 'box', 'label': 'BALL', 'points': [(507.48, 827.74), (709.08, 1029.34)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
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"[{'type': 'box', 'label': 'BALL', 'points': [(551.91, 678.6), (754.9, 883.0)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
13
"[{'type': 'box', 'label': 'BALL', 'points': [(655.01, 680.55), (874.22, 907.38)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
10
"[{'type': 'box', 'label': 'BALL', 'points': [(851.34, 465.16), (1076.27, 688.18)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
4
"[]"
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"[{'type': 'box', 'label': 'BALL', 'points': [(706.5, 611.93), (940.93, 836.86)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
0
"[{'type': 'box', 'label': 'BALL', 'points': [(290.48, 1269.28), (472.41, 1361.07)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
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"[]"
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"[{'type': 'box', 'label': 'BALL', 'points': [(792.16, 394.03), (1006.8, 606.91)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
11
"[{'type': 'box', 'label': 'BALL', 'points': [(847.53, 517.8), (1075.1, 741.55)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
8
"[{'type': 'box', 'label': 'BALL', 'points': [(764.95, 471.56), (989.71, 687.9)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
2
"[{'type': 'box', 'label': 'BALL', 'points': [(712.19, 524.25), (954.27, 752.99)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
21
"[{'type': 'box', 'label': 'BALL', 'points': [(726.38, 737.05), (903.8, 931.01)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
17
"[{'type': 'box', 'label': 'BALL', 'points': [(489.75, 61.06), (691.8, 263.11)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
15
"[{'type': 'box', 'label': 'BALL', 'points': [(1039.67, 444.19), (1239.81, 665.3)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
20
"[{'type': 'box', 'label': 'BALL', 'points': [(708.95, 596.68), (899.57, 812.08)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
27
"[{'type': 'box', 'label': 'BALL', 'points': [(561.03, 11.62), (719.56, 182.38)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
24
"[{'type': 'box', 'label': 'BALL', 'points': [(612.34, 361.98), (738.74, 510.72)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
18
"[{'type': 'box', 'label': 'BALL', 'points': [(469.84, 45.65), (719.49, 286.62)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
26
"[{'type': 'box', 'label': 'BALL', 'points': [(581.68, 30.9), (723.39, 186.41)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
14
"[{'type': 'box', 'label': 'BALL', 'points': [(1002.88, 449.9), (1225.9, 678.65)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
19
"[{'type': 'box', 'label': 'BALL', 'points': [(671.74, 169.39), (975.66, 490.68)], 'attributes': {'occluded': 'false', 'basket': 'true'}}]"
23
"[{'type': 'box', 'label': 'BALL', 'points': [(787.3, 604.22), (931.65, 747.62)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
25
"[{'type': 'box', 'label': 'BALL', 'points': [(474.33, 182.01), (611.29, 301.51)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
22
"[{'type': 'box', 'label': 'BALL', 'points': [(791.1, 744.49), (950.13, 918.23)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
16
"[{'type': 'box', 'label': 'BALL', 'points': [(525.01, 47.05), (701.33, 236.07)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
32
"[{'type': 'box', 'label': 'BALL', 'points': [(504.48, 400.11), (531.37, 449.32)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
29
"[{'type': 'box', 'label': 'BALL', 'points': [(564.4, 608.01), (616.06, 666.29)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
31
"[{'type': 'box', 'label': 'BALL', 'points': [(535.9, 429.33), (587.88, 491.79)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
38
"[{'type': 'box', 'label': 'BALL', 'points': [(402.1, 175.89), (459.83, 231.7)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
35
"[{'type': 'box', 'label': 'BALL', 'points': [(429.46, 380.55), (481.9, 433.4)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
37
"[{'type': 'box', 'label': 'BALL', 'points': [(422.37, 247.67), (476.15, 302.03)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
28
"[{'type': 'box', 'label': 'BALL', 'points': [(620.14, 457.96), (675.76, 520.44)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
34
"[{'type': 'box', 'label': 'BALL', 'points': [(452.29, 361.54), (506.7, 415.9)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
36
"[{'type': 'box', 'label': 'BALL', 'points': [(427.28, 315.22), (474.3, 368.53)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
33
"[{'type': 'box', 'label': 'BALL', 'points': [(469.74, 362.74), (521.81, 419.39)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
30
"[{'type': 'box', 'label': 'BALL', 'points': [(482.03, 343.04), (539.25, 395.49)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
47
"[{'type': 'box', 'label': 'BALL', 'points': [(272.98, 36.34), (594.21, 340.42)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
50
"[]"
48
"[{'type': 'box', 'label': 'BALL', 'points': [(620.95, 354.72), (914.5, 656.42)], 'attributes': {'occluded': 'false', 'basket': 'true'}}]"
42
"[{'type': 'box', 'label': 'BALL', 'points': [(757.77, 479.87), (973.66, 719.61)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
40
"[{'type': 'box', 'label': 'BALL', 'points': [(585.01, 469.23), (730.83, 640.73)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
45
"[{'type': 'box', 'label': 'BALL', 'points': [(28.46, 431.97), (328.2, 716.65)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
56
"[{'type': 'box', 'label': 'BALL', 'points': [(718.55, 38.66), (931.93, 248.9)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
53
"[{'type': 'box', 'label': 'BALL', 'points': [(618.07, 72.22), (813.62, 276.12)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
43
"[{'type': 'box', 'label': 'BALL', 'points': [(777.6, 678.19), (978.43, 906.63)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
55
"[{'type': 'box', 'label': 'BALL', 'points': [(689.36, 31.23), (891.24, 243.56)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
39
"[{'type': 'box', 'label': 'BALL', 'points': [(618.43, 428.62), (765.13, 605.45)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
44
"[{'type': 'box', 'label': 'BALL', 'points': [(275.18, 848.59), (514.67, 1106.16)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
52
"[{'type': 'box', 'label': 'BALL', 'points': [(590.1, 152.74), (770.99, 347.6)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
46
"[{'type': 'box', 'label': 'BALL', 'points': [(15.81, 125.61), (314.04, 429.87)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
54
"[{'type': 'box', 'label': 'BALL', 'points': [(660.95, 24.69), (846.53, 233.28)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
51
"[{'type': 'box', 'label': 'BALL', 'points': [(656.66, 312.72), (717.53, 459.92)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
41
"[{'type': 'box', 'label': 'BALL', 'points': [(830.88, 186.45), (1002.43, 326.62)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
65
"[{'type': 'box', 'label': 'BALL', 'points': [(217.59, 1183.46), (369.15, 1337.5)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
60
"[{'type': 'box', 'label': 'BALL', 'points': [(400.62, 379.19), (514.66, 563.03)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
58
"[{'type': 'box', 'label': 'BALL', 'points': [(188.93, 679.92), (364.7, 853.33)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
64
"[{'type': 'box', 'label': 'BALL', 'points': [(173.77, 864.65), (340.25, 1026.04)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
63
"[{'type': 'box', 'label': 'BALL', 'points': [(547.8, 93.79), (743.5, 307.8)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
71
"[{'type': 'box', 'label': 'BALL', 'points': [(322.23, 657.97), (468.51, 836.11)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
68
"[{'type': 'box', 'label': 'BALL', 'points': [(313.97, 680.62), (466.15, 857.58)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
70
"[{'type': 'box', 'label': 'BALL', 'points': [(508.76, 627.96), (667.31, 803.5)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
57
"[{'type': 'box', 'label': 'BALL', 'points': [(190.39, 645.51), (358.85, 835.21)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
62
"[{'type': 'box', 'label': 'BALL', 'points': [(369.54, 416.02), (539.41, 614.21)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
67
"[{'type': 'box', 'label': 'BALL', 'points': [(289.44, 705.51), (452.23, 882.47)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
69
"[{'type': 'box', 'label': 'BALL', 'points': [(316.57, 657.97), (460.49, 827.85)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"
66
"[{'type': 'box', 'label': 'BALL', 'points': [(239.65, 816.05), (394.19, 972.95)], 'attributes': {'occluded': 'false', 'basket': 'false'}}]"
59
"[{'type': 'box', 'label': 'BALL', 'points': [(229.32, 442.94), (403.44, 617.06)], 'attributes': {'occluded': 'true', 'basket': 'false'}}]"

Basketball Tracking

Tracking is a deep learning process where the algorithm tracks the movement of an object.

The dataset consist of screenshots from videos of basketball games with the ball labeled with a bounging box. The dataset can be used to train a neural network in ball control recognition. The dataset is useful for automating the camera operator's work during a match, allowing the ball to be efficiently kept in frame.

Get the dataset

This is just an example of the data

Leave a request on https://trainingdata.pro/data-market to discuss your requirements, learn about the price and buy the dataset.

Dataset structure

  • img - contains of original images of basketball players.
  • boxes - includes bounding box labeling for a ball in the original images.
  • annotations.xml - contains coordinates of the boxes and labels, created for the original photo

Data Format

Each image from img folder is accompanied by an XML-annotation in the annotations.xml file indicating the coordinates of the bounding boxes for the ball position. For each point, the x and y coordinates are provided.

Attributes

  • occluded - the ball visability (true if the the ball is occluded by 30%)
  • basket - the position related to the basket (true if the ball is covered with a basket on any distinguishable area)

Example of XML file structure

Basketball Tracking might be made in accordance with your requirements.

TrainingData

More datasets in TrainingData's Kaggle account: https://www.kaggle.com/trainingdatapro/datasets

TrainingData's GitHub: https://github.com/Trainingdata-datamarket/TrainingData_All_datasets

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