Dataset Versions

v9

Augmented but recreated because roboflow didn-t let me re-upload the model since I uploaded the wrong one last time so the pictures in here might not be the exact ones trained- but the augmentation parameters are the same

Generated on Mar 5, 2024

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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 87%
5793Images
Valid Set 8%
545Images
Test Set 4%
288Images

Preprocessing

No preprocessing steps were applied.

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Crop: 0% Minimum Zoom, 82% Maximum Zoom
Shear: ±15° Horizontal, ±15° Vertical
Grayscale: Apply to 24% of images
Hue: Between -25° and +25°
Saturation: Between -25% and +25%
Brightness: Between -25% and +25%
Exposure: Between -15% and +15%
Blur: Up to 2px
Noise: Up to 1.99% of pixels