Dataset Versions

v2

2

Generated on May 24, 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.
Other Formats
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Dataset Split

Train Set 88%
1436Images
Valid Set 8%
133Images
Test Set 4%
67Images

Preprocessing

Auto-Orient: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Tile: 1 rows x 1 columns
Filter Null: Require at least 80% of images to contain annotations.

Augmentations

Outputs per training example: 3
Flip: Horizontal
90° Rotate: Clockwise, Counter-Clockwise
Crop: 0% Minimum Zoom, 10% Maximum Zoom
Grayscale: Apply to 25% of images
Saturation: Between -10% and +10%
Brightness: Between -10% and +10%
Exposure: Between -15% and +15%
Blur: Up to 5px
Noise: Up to 1% of pixels
Bounding Box: Brightness: Between -3% and +3%
Bounding Box: Exposure: Between -5% and +5%
Bounding Box: Blur: Up to 2px
Bounding Box: Noise: Up to 1% of pixels

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