Dataset Versions

Versions
2022-10-01 6:44pm
v15
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2 years ago
2022-10-01 6:44pm
v14
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2 years ago
2022-10-01 6:43pm
v13
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2 years ago
2022-10-01 6:40pm
v12
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2 years ago
2022-10-01 6:39pm
v11
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2 years ago
2022-10-01 6:38pm
v10
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2 years ago
2022-10-01 6:38pm
v9
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2 years ago
2022-10-01 6:37pm
v8
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2 years ago
2022-10-01 6:23pm
v7
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2 years ago
2022-10-01 6:22pm
v6
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2 years ago
2022-10-01 6:21pm
v5
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2 years ago
2022-10-01 6:21pm
v4
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2 years ago
2022-10-01 6:20pm
v3
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2 years ago
2022-10-01 6:19pm
v2
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2 years ago
2022-10-01 6:18pm
v1
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2 years ago
v14

2022-10-01 6:44pm

Generated on Oct 1, 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.
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30 Total Images

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Dataset Split

Train Set 100%
30Images
Valid Set %
0Images
Test Set %
0Images

Preprocessing

Auto-Orient: Applied
Resize: Stretch to 640x640

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Rotation: Between -15° and +15°
Shear: ±15° Horizontal, ±15° Vertical
Grayscale: Apply to 25% of images
Saturation: Between -25% and +25%
Brightness: Between -25% and +25%
Exposure: Between -25% and +25%
Noise: Up to 3% of pixels

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