WISD

VA-Football

Object Detection

VA-Football Image Dataset

v4

Official Model

Generated on Jun 12, 2023

Popular Download Formats

Pascal VOC XML
Common XML annotation format for local data munging (pioneered by ImageNet).
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.

Dataset Split

Train Set 83%
744Images
Valid Set 13%
115Images
Test Set 4%
40Images

Preprocessing

Auto-Orient: Applied
Resize: Stretch to 640x640

Augmentations

Outputs per training example: 3
Flip: Horizontal
Crop: 0% Minimum Zoom, 33% Maximum Zoom
Shear: ±15° Horizontal, ±15° Vertical
Saturation: Between -25% and +25%
Brightness: Between -30% and +30%
Exposure: Between -17% and +17%
Noise: Up to 1% of pixels
Cutout: 3 boxes with 5% size each
goalkeepers-referee-player-balls
1430 images
FYP
fyp
football-players
1440 images
Arbitre-Joueur-Ballon
674 images