Antu Winner

D1-Class Balanced Dataset

Object Detection

D1-Class Balanced Dataset Image Dataset

v2

D1-Class Balanced

Generated on Aug 25, 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
CreateML JSON format is used with Apple's CreateML and Turi Create tools.
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Dataset Split

Train Set 100%
1144Images
Valid Set %
0Images
Test Set %
0Images

Preprocessing

Auto-Orient: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Resize: Stretch to 416x416
Grayscale: Applied
Auto-Adjust Contrast: Using Histogram Equalization
Filter Null: Require at least 1% of images to contain annotations.

Augmentations

Outputs per training example: 1
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Rotation: Between -25° and +25°
Shear: ±15° Horizontal, ±15° Vertical
Hue: Between -41° and +41°
Saturation: Between -18% and +18%
Brightness: Between -15% and +15%
Blur: Up to 1.25px
Noise: Up to 5% of pixels
Bounding Box: Rotation: Between -15° and +15°
Bounding Box: Brightness: Between -25% and +25%
Bounding Box: Noise: Up to 5% of pixels
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