Dataset Versions

v2

2022-03-06 2:07pm

Generated on Mar 6, 2022

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.
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Dataset Split

Train Set 92%
6831Images
Valid Set 4%
297Images
Test Set 4%
270Images

Preprocessing

Auto-Orient: Applied
Isolate Objects: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Resize: Stretch to 416x416
Auto-Adjust Contrast: Using Adaptive Equalization
Tile: 3 rows x 3 columns

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
Rotation: Between -45° and +45°
Hue: Between -11° and +11°
Brightness: Between -30% and +30%
Exposure: Between -25% and +25%
Blur: Up to 15.25px
Noise: Up to 10% of pixels
Cutout: 13 boxes with 10% size each
Mosaic: Applied
Bounding Box: Brightness: Between -25% and +25%
Bounding Box: Blur: Up to 6.25px

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