Dataset Versions

Versions
2023-08-20 11:48pm
v22
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a year ago
2023-08-20 11:47pm
v21
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a year ago
2023-08-20 11:13pm
v20
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a year ago
2023-08-20 11:12pm
v19
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a year ago
2023-08-20 11:12pm
v18
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a year ago
2023-08-20 11:11pm
v17
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a year ago
2023-08-20 11:10pm
v16
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a year ago
2023-08-20 11:10pm
v15
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a year ago
2023-08-20 11:09pm
v14
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a year ago
2023-08-20 11:08pm
v13
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a year ago
2023-08-20 11:08pm
v12
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a year ago
2023-08-20 11:07pm
v11
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a year ago
2023-08-20 11:06pm
v10
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a year ago
2023-08-20 11:06pm
v9
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a year ago
2023-08-20 11:05pm
v8
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a year ago
2023-08-20 11:04pm
v7
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a year ago
2023-08-20 11:03pm
v6
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a year ago
2023-08-20 11:02pm
v5
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a year ago
2023-08-20 11:01pm
v4
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a year ago
2023-08-20 11:00pm
v3
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a year ago
2023-08-20 10:59pm
v2
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a year ago
2023-08-20 10:58pm
v1
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a year ago
v7

2023-08-20 11:04pm

Generated on Aug 20, 2023
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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 Image Dataset Image Dataset Image Dataset Image Dataset Image Dataset Image Dataset Image Dataset Image Dataset Image Dataset Image Dataset Image Dataset Image

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
Shear: ±13° Horizontal, ±18° Vertical
Grayscale: Apply to 26% of images
Saturation: Between -24% and +24%

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