Football Players Image Dataset
Versions
2022-12-28 1:33pm
v15
Dec 28, 2022
2022-12-10 1:01pm
v14
Dec 10, 2022
2022-12-05 3:38pm
v13
Dec 5, 2022
2022-12-01 2:26pm
v12
Dec 1, 2022
2022-12-01 1:37pm
v11
Dec 1, 2022
2022-11-29 3:45pm
v10
Nov 29, 2022
2022-11-29 3:26pm
v9
Nov 29, 2022
v8
v8
Feb 26, 2022
Shared Version
v7
Oct 15, 2021
v6
v6
Oct 5, 2021
v5
v5
Sep 28, 2021
v4
v4
Sep 23, 2021
v3
v3
Sep 22, 2021
v2
v2
Sep 20, 2021
Football Players
v1
Sep 17, 2021
v3
v3
Generated on Sep 22, 2021
Popular Download Formats
YOLOv8
TXT annotations and YAML config used with YOLOv8.
YOLOv5
TXT annotations and YAML config used with YOLOv5.
YOLOv7
TXT annotations and YAML config used with YOLOv7.
MT-YOLOv6
MT-YOLOv6 TXT annotations used with meituan/YOLOv6.
COCO JSON
COCO JSON annotations are used with EfficientDet Pytorch and Detectron 2.
YOLO Darknet
Darknet TXT annotations used with YOLO Darknet (both v3 and v4) and YOLOv3 PyTorch.
Pascal VOC XML
Common XML annotation format for local data munging (pioneered by ImageNet).
TFRecord
TFRecord binary format used for both Tensorflow 1.5 and Tensorflow 2.0 Object Detection models.
CreateML JSON
CreateML JSON format is used with Apple's CreateML and Turi Create tools.
Other Formats
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221 Total Images
View All Images
Dataset Split
Train Set 70%
155Images
Valid Set 20%
44Images
Test Set 10%
22Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 416x416
Auto-Adjust Contrast: Using Adaptive Equalization
Augmentations
Outputs per training example: 1
Saturation: Between -42% and +42%
Brightness: Between -32% and +32%
Mosaic: Applied
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