Dataset Versions

v3

240 train. -ver. 144 train - 2 own dataset -- bigger bounding box---

Generated on May 19, 2022

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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 83%
240Images
Valid Set 6%
16Images
Test Set 11%
32Images

Preprocessing

No preprocessing steps were applied.

Augmentations

Outputs per training example: 3
Flip: Horizontal
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -12° and +12°
Shear: ±15° Horizontal, ±15° Vertical
Grayscale: Apply to 26% of images
Hue: Between -25° and +25°
Saturation: Between -25% and +25%
Brightness: Between -25% and +25%
Exposure: Between -25% and +25%
Blur: Up to 2.25px
Noise: Up to 6% of pixels
Bounding Box: Crop: 0% Minimum Zoom, 20% Maximum Zoom
Bounding Box: Brightness: Between -25% and +25%
Bounding Box: Exposure: Between -25% and +25%
Bounding Box: Blur: Up to 10px

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