Dataset Versions

v3

V5

Generated on Sep 3, 2023

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 63%
7040Images
Valid Set 16%
1830Images
Test Set 20%
2238Images

Preprocessing

Auto-Orient: Applied
Auto-Adjust Contrast: Using Adaptive Equalization
Grayscale: Applied
Modify Classes: 9 remapped, 0 dropped
Filter Null: Require at least 60% of images to contain annotations.

Augmentations

Outputs per training example: 2
Flip: Horizontal
90° Rotate: Clockwise, Counter-Clockwise
Crop: 0% Minimum Zoom, 5% Maximum Zoom
Rotation: Between -15° and +15°
Saturation: Between -10% and +10%
Brightness: Between -5% and +5%
Exposure: Between -5% and +5%
Blur: Up to 1px
Noise: Up to 5% of pixels
Mosaic: Applied
Bounding Box: Flip: Horizontal, Vertical
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise
Bounding Box: Crop: 0% Minimum Zoom, 11% Maximum Zoom
Bounding Box: Rotation: Between -15° and +15°
Bounding Box: Shear: ±15° Horizontal, ±15° Vertical
Bounding Box: Brightness: Between -10% and +10%
Bounding Box: Exposure: Between -8% and +8%
Bounding Box: Blur: Up to 0.5px
Bounding Box: Noise: Up to 2% of pixels

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