Dataset Versions

v1

switch_1_20211027_1

Generated on Oct 27, 2021

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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
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Dataset Split

Train Set 87%
27Images
Valid Set 10%
3Images
Test Set 3%
1Images

Preprocessing

Auto-Orient: Applied
Resize: Stretch to 416x416

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -21° and +21°
Shear: ±15° Horizontal, ±15° Vertical
Grayscale: Apply to 25% of images
Saturation: Between -40% and +40%
Exposure: Between -25% and +25%
Blur: Up to 2px
Noise: Up to 5% of pixels
Cutout: 3 boxes with 10% size each
Mosaic: Applied
Bounding Box: Crop: 0% Minimum Zoom, 20% Maximum Zoom
Bounding Box: Rotation: Between -15° and +15°
Bounding Box: Shear: ±15° Horizontal, ±15° Vertical
Bounding Box: Brightness: Between -25% and +25%
Bounding Box: Noise: Up to 5% of pixels

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