Dataset Versions

v9

416-3

Generated on Dec 27, 2021

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 72%
483Images
Valid Set 19%
128Images
Test Set 9%
64Images

Preprocessing

Auto-Orient: Applied
Resize: Stretch to 416x416
Grayscale: Applied
Auto-Adjust Contrast: Using Adaptive Equalization
Filter Null: Require all images to contain annotations.

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Rotation: Between -15° and +15°
Shear: ±15° Horizontal, ±15° Vertical
Grayscale: Apply to 25% of images
Hue: Between -25° and +25°
Saturation: Between -25% and +25%
Brightness: Between -25% and +25%
Exposure: Between -25% and +25%
Blur: Up to 10px
Noise: Up to 5% of pixels
Bounding Box: Flip: Horizontal, Vertical
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Bounding Box: Rotation: Between -15° and +15°
Bounding Box: Brightness: Between -38% and +38%
Bounding Box: Exposure: Between -37% and +37%
Bounding Box: Blur: Up to 10px
Bounding Box: Noise: Up to 5% of pixels

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