Dataset Versions

Versions
2024-11-24 10:50pm
v41
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a month ago
2024-11-21 5:20am
v40
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a month ago
2024-11-18 3:46am
v36
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a month ago
2024-07-31 4:26am
v28
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5 months ago
2024-07-30 5:50pm
v26
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5 months ago
2024-07-28 10:20pm
v25
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5 months ago
2024-07-28 8:03pm
v24
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5 months ago
2024-07-28 3:34pm
v23
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5 months ago
2024-07-28 1:28pm
v22
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5 months ago
2024-07-25 11:42am
v21
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5 months ago
2024-07-25 8:05am
v20
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5 months ago
2024-07-25 12:42am
v19
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5 months ago
2024-07-24 10:47pm
v18
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5 months ago
2024-07-24 8:48pm
v17
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5 months ago
2024-07-24 5:32pm
v16
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5 months ago
2024-07-24 5:12pm
v15
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5 months ago
2024-07-24 12:46pm
v14
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5 months ago
2024-07-23 1:03pm
v12
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5 months ago
2024-07-16 1:25pm
v10
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5 months ago
2024-07-15 1:06am
v9
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5 months ago
2024-07-15 1:04am
v8
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5 months ago
2024-07-14 3:37am
v7
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5 months ago
2024-03-21 3:39am
v6
·
9 months ago
2024-03-21 2:56am
v5
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9 months ago
v6

2024-03-21 3:39am

Generated on Mar 21, 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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CreateML JSON format is used with Apple's CreateML and Turi Create tools.
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184 Total Images

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Dataset Split

Train Set 88%
162Images
Valid Set 9%
16Images
Test Set 3%
6Images

Preprocessing

Auto-Orient: Applied
Resize: Stretch to 640x390

Augmentations

Outputs per training example: 3
Crop: 0% Minimum Zoom, 7% Maximum Zoom
Rotation: Between -2° and +2°
Grayscale: Apply to 15% of images
Saturation: Between -25% and +25%
Blur: Up to 1.5px

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