Dataset Versions
Versions
raw-images_Classes-Player_Ref_Ball-150imgs
v16
· 2 years ago
resize640_aug10x_Classes-Player_Ref_Ball-150imgs
v15
· 2 years ago
omitGoalieGOAL-aug10x_USA-NED-COCOChkpt_v3-150imgs
v14
· 2 years ago
omitGoalieGOAL-aug10x_USA-NED-SaloChkpt_v2-69imgs
v13
· 2 years ago
omitGoalieGOAL-aug10x_USA-NED-COCOChkpt_v2-69imgs
v12
· 2 years ago
resized640-aug10x_USA-NED-COCOChkpt_v2-69imgs
v11
· 2 years ago
resized640-aug10x_USA-NED-SaloChkpt_v2-69imgs
v10
· 2 years ago
resized640-aug10x_USA-NED-SaloChkpt
v9
· 2 years ago
resized640-aug10x_Player-SaloChkpt
v8
· 2 years ago
resized640-aug10x_Player
v6
· 2 years ago
resized640_mosaic-aug10x_Player
v5
· 2 years ago
resized640-aug10x_Team1Team2
v4
· 2 years ago
resized640_mosaic-aug10x_Team1Team2
v3
· 2 years ago
resized640-aug10x-USA-NED
v2
· 2 years ago
resized640_mosaic-aug10x-USA-NED
v1
· 2 years ago
v4
resized640-aug10x_Team1Team2
Generated on Dec 3, 2022
Popular Download Formats
YOLOv11
TXT annotations and YAML config used with YOLOv11.
YOLOv9
TXT annotations and YAML config used with YOLOv9.
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.
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.
PaliGemma
PaliGemma JSONL format used for fine-tuning PaliGemma, Google's open multimodal vision model.
CreateML JSON
CreateML JSON format is used with Apple's CreateML and Turi Create tools.
Other Formats
Choose another format.
115 Total Images
View All ImagesDataset Split
Train Set 96%
110Images
Valid Set 3%
3Images
Test Set 2%
2Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Modify Classes: 2 remapped, 0 dropped
Augmentations
Outputs per training example: 10
Flip: Horizontal
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -10° and +10°
Shear: ±2° Horizontal, ±2° Vertical
Grayscale: Apply to 5% of images
Hue: Between -10° and +10°
Saturation: Between -15% and +15%
Brightness: Between -20% and +20%
Exposure: Between -20% and +20%
Blur: Up to 0.5px
Cutout: 5 boxes with 1% size each