Dataset Versions

v3

2024-11-21 7:09pm

Generated on Nov 21, 2024

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
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Dataset Split

Train Set 88%
6258Images
Valid Set 8%
596Images
Test Set 4%
297Images

Preprocessing

Auto-Orient: Applied
Resize: Fit (black edges) in 640x640
Auto-Adjust Contrast: Using Adaptive Equalization
Modify Classes: 20 remapped, 0 dropped
Filter Null: Require all images to contain annotations.

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Crop: 0% Minimum Zoom, 19% Maximum Zoom
Rotation: Between -15° and +15°
Shear: ±15° Horizontal, ±14° Vertical
Hue: Between -15° and +15°
Saturation: Between -15% and +15%
Brightness: Between -13% and +13%
Exposure: Between -11% and +11%
Blur: Up to 1.8px
Noise: Up to 1.64% of pixels
Cutout: 1 boxes with 11% size each
Bounding Box: Flip: Horizontal, Vertical
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Bounding Box: Crop: 0% Minimum Zoom, 14% Maximum Zoom
Bounding Box: Rotation: Between -11° and +11°
Bounding Box: Shear: ±13° Horizontal, ±13° Vertical
Bounding Box: Brightness: Between -15% and +15%
Bounding Box: Exposure: Between -7% and +7%
Bounding Box: Blur: Up to 1.5px
Bounding Box: Noise: Up to 1.8% of pixels

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