Dataset Versions

v4

2024-05-19 9:51am

Generated on May 19, 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 93%
603Images
Valid Set 4%
29Images
Test Set 3%
19Images

Preprocessing

Auto-Orient: Applied
Static Crop: 0-100% Horizontal Region, 25-79% Vertical Region
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Adaptive Equalization
Grayscale: Applied
Tile: 4 rows x 4 columns
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, 30% Maximum Zoom
Rotation: Between -45° and +45°
Hue: Between -15° and +15°
Saturation: Between -69% and +69%
Brightness: Between -15% and +15%
Bounding Box: Flip: Horizontal, Vertical
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Bounding Box: Crop: 0% Minimum Zoom, 50% Maximum Zoom
Bounding Box: Rotation: Between -16° and +16°
Bounding Box: Shear: ±10° Horizontal, ±10° Vertical
Bounding Box: Brightness: Between -15% and +15%
Bounding Box: Exposure: Between -99% and +99%
Bounding Box: Noise: Up to 10% of pixels

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