Dataset Versions

v3

2024-05-08 9:32am

Generated on May 8, 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.
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Dataset Split

Train Set 89%
708Images
Valid Set 8%
60Images
Test Set 4%
32Images

Preprocessing

Auto-Orient: Applied
Isolate Objects: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Dynamic Crop: Class: ISLAK ASFLAT
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Histogram Equalization
Tile: 2 rows x 2 columns

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -15° and +15°
Shear: ±10° Horizontal, ±14° Vertical
Grayscale: Apply to 15% of images
Saturation: Between -19% and +19%
Brightness: Between -20% and +20%
Noise: Up to 1.01% of pixels
Cutout: 2 boxes with 8% size each
Bounding Box: Flip: Horizontal, Vertical
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise
Bounding Box: Rotation: Between -15° and +15°
Bounding Box: Shear: ±10° Horizontal, ±10° Vertical
Bounding Box: Brightness: Between -15% and +15%
Bounding Box: Blur: Up to 2.5px

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