Dataset Versions

v1

2022-11-16 7:43pm

Generated on Nov 16, 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 90%
32976Images
Valid Set 7%
2480Images
Test Set 3%
1200Images

Preprocessing

Auto-Orient: Applied
Static Crop: 30-70% Horizontal Region, 30-70% Vertical Region
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Adaptive Equalization
Tile: 4 rows x 4 columns

Augmentations

Outputs per training example: 3
Shear: ±15° Horizontal, ±30° Vertical
Grayscale: Apply to 60% of images
Hue: Between -90° and +90°
Saturation: Between -70% and +70%
Exposure: Between -65% and +65%
Noise: Up to 13% of pixels
Cutout: 10 boxes with 15% size each
Mosaic: Applied
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise
Bounding Box: Rotation: Between -20° and +20°
Bounding Box: Brightness: Between -65% and +65%

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