Dataset Versions

Versions
2024-08-06 11:35pm
v47
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5 months ago
2024-05-11 7:30pm
v46
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8 months ago
2024-04-29 6:10pm
v45
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8 months ago
2024-03-08 2:02pm
v44
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10 months ago
2024-03-07 9:34am
v43
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10 months ago
2024-02-29 1:33pm
v42
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10 months ago
2024-02-07 10:52am
v41
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a year ago
2024-02-05 3:38pm
v40
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a year ago
2024-01-31 6:51pm
v39
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a year ago
2024-01-30 4:45pm
v38
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a year ago
2024-01-29 12:41pm
v37
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a year ago
2024-01-26 11:47am
v36
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a year ago
2024-01-25 7:09pm
v35
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a year ago
2024-01-19 3:32pm
v34
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a year ago
2024-01-16 11:43am
v33
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a year ago
2024-01-12 10:58am
v32
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a year ago
2024-01-11 5:11pm
v31
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a year ago
2024-01-10 2:08pm
v30
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a year ago
2024-01-08 1:38pm
v29
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a year ago
2024-01-08 11:07am
v28
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a year ago
2024-01-08 11:04am
v27
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a year ago
2024-01-05 12:29pm
v26
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a year ago
2024-01-04 3:25pm
v25
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a year ago
2024-01-03 3:41pm
v24
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a year ago
2024-01-03 12:23pm
v23
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a year ago
2024-01-02 6:58pm
v22
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a year ago
2023-12-27 1:48pm
v21
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a year ago
2023-12-27 12:44pm
v20
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a year ago
2023-12-22 9:22am
v19
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a year ago
2023-12-20 10:16am
v18
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a year ago
2023-12-18 12:48pm
v17
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a year ago
2023-12-18 12:46pm
v16
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a year ago
2023-12-17 4:25pm
v15
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a year ago
2023-12-17 4:16pm
v14
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a year ago
2023-12-16 3:52am
v13
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a year ago
2023-12-16 2:47am
v12
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a year ago
2023-12-13 11:43am
v11
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a year ago
2023-12-13 10:07am
v10
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a year ago
2023-12-11 1:03pm
v9
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a year ago
2023-12-08 7:34pm
v8
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a year ago
2023-12-08 9:11am
v7
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a year ago
2023-12-07 9:48pm
v6
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a year ago
2023-12-07 7:04pm
v5
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a year ago
2023-12-06 4:03pm
v4
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a year ago
2023-12-06 4:02pm
v2
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a year ago
2023-12-06 2:43pm
v1
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a year ago
v19

2023-12-22 9:22am

Generated on Dec 22, 2023

Popular Download Formats

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.
Other Formats
Choose another format.

Dataset Split

Train Set 5%
3Images
Valid Set %
0Images
Test Set 95%
55Images

Preprocessing

Auto-Adjust Contrast: Using Adaptive Equalization

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
Brightness: Between -10% and +10%
Blur: Up to 1.5px
Noise: Up to 5% of pixels

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