Dataset Versions

v7

2024-09-21 2:30pm

Generated on Sep 21, 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 89%
3780Images
Valid Set 7%
300Images
Test Set 4%
152Images

Preprocessing

Auto-Orient: Applied
Isolate Objects: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Dynamic Crop: Class: Box
Resize: Stretch to 1920x1080
Auto-Adjust Contrast: Using Adaptive Equalization
Grayscale: Applied
Tile: 2 rows x 2 columns

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 -15° and +15°
Shear: ±10° Horizontal, ±10° Vertical
Grayscale: Apply to 25% of images
Hue: Between -25° and +25°
Saturation: Between -25% and +25%
Brightness: Between -15% and +15%
Exposure: Between -15% and +15%
Blur: Up to 2.5px
Noise: Up to 1.96% of pixels
Cutout: 3 boxes with 10% size each
Mosaic: Applied
Bounding Box: Flip: Horizontal
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise
Bounding Box: Crop: 0% Minimum Zoom, 20% Maximum Zoom
Bounding Box: Rotation: Between -15° and +15°
Bounding Box: Shear: ±10° Horizontal, ±10° Vertical
Bounding Box: Brightness: Between -15% and +15%
Bounding Box: Exposure: Between -10% and +10%
Bounding Box: Blur: Up to 2.5px
Bounding Box: Noise: Up to 0.1% of pixels

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