Dataset Versions

Versions
2024-03-27 11:21am
v20
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8 months ago
2024-03-27 10:44am
v19
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8 months ago
2024-03-27 10:16am
v18
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8 months ago
2024-03-25 9:45pm
v17
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8 months ago
2024-03-25 9:37pm
v16
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8 months ago
2024-03-25 8:10pm
v15
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8 months ago
2024-03-25 6:19pm
v14
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8 months ago
2024-03-25 6:02pm
v13
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8 months ago
2024-03-25 5:53pm
v12
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8 months ago
2024-03-25 5:48pm
v11
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8 months ago
2024-03-23 1:21am
v10
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8 months ago
2024-03-23 12:20am
v9
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8 months ago
2024-03-23 12:16am
v8
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8 months ago
2024-03-22 10:56pm
v7
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8 months ago
2024-03-22 10:51pm
v6
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8 months ago
2024-03-22 10:47pm
v5
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8 months ago
2024-03-22 10:46pm
v4
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8 months ago
2024-03-22 10:10pm
v3
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8 months ago
2024-03-22 10-06pm
v2
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8 months ago
2024-03-22 8:41pm
v1
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8 months ago
v2

2024-03-22 10-06pm

Generated on Mar 22, 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.
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1827 Total Images

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Dataset Split

Train Set 92%
1683Images
Valid Set 6%
105Images
Test Set 2%
39Images

Preprocessing

Auto-Orient: Applied
Resize: Fit (black edges) in 640x640
Auto-Adjust Contrast: Using Contrast Stretching

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Rotation: Between -15° and +15°
Shear: ±10° Horizontal, ±10° Vertical
Hue: Between -15° and +15°
Saturation: Between -25% and +25%
Brightness: Between -15% and +15%
Exposure: Between -10% and +10%
Blur: Up to 2.5px
Noise: Up to 0.1% of pixels

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