Dataset Versions

v3

2023-02-03 6:44pm

Generated on Feb 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.
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Dataset Split

Train Set 82%
2364Images
Valid Set 11%
330Images
Test Set 7%
195Images

Preprocessing

Auto-Orient: Applied
Isolate Objects: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Adaptive Equalization
Tile: 1 rows x 1 columns

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
Rotation: Between -20° and +20°
Grayscale: Apply to 33% of images
Saturation: Between -25% and +25%
Exposure: Between -25% and +25%
Noise: Up to 5% of pixels
Cutout: 3 boxes with 10% size each
Bounding Box: Flip: Horizontal
Bounding Box: Crop: 0% Minimum Zoom, 20% Maximum Zoom
Bounding Box: Shear: ±15° Horizontal, ±15° Vertical
Bounding Box: Noise: Up to 5% of pixels

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