Dataset Versions

Versions
2023-11-29 6:11am
v56
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a year ago
2023-11-27 2:04pm
v55
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a year ago
2023-11-27 9:59am
v54
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a year ago
2023-11-27 9:23am
v53
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2023-11-27 8:47am
v52
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2023-11-27 8:40am
v51
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2023-11-27 8:35am
v50
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a year ago
2023-11-27 6:53am
v49
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a year ago
2023-11-27 1:02am
v48
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a year ago
2023-11-27 12:40am
v47
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a year ago
2023-11-27 12:19am
v46
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a year ago
2023-11-26 11:53pm
v45
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a year ago
2023-11-26 11:36pm
v44
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a year ago
2023-11-26 11:25pm
v43
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a year ago
2023-11-26 11:05pm
v42
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a year ago
2023-11-26 10:45pm
v41
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a year ago
2023-11-26 10:29pm
v40
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a year ago
2023-11-26 10:02pm
v39
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a year ago
2023-11-26 9:41pm
v38
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a year ago
2023-11-26 9:31pm
v37
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a year ago
2023-11-26 6:26pm
v36
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a year ago
2023-11-26 6:11pm
v35
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a year ago
2023-11-26 6:05pm
v34
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a year ago
2023-11-26 5:58pm
v33
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a year ago
2023-11-26 5:56pm
v32
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a year ago
2023-11-26 5:52pm
v31
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a year ago
2023-11-26 5:40pm
v30
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a year ago
2023-11-26 5:19pm
v29
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a year ago
2023-11-26 4:50pm
v28
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a year ago
2023-11-26 4:30pm
v27
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a year ago
2023-11-25 11:46pm
v26
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a year ago
2023-11-25 9:43pm
v25
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a year ago
2023-11-25 6:09pm
v24
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a year ago
2023-11-25 5:57pm
v23
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a year ago
2023-11-25 5:39pm
v22
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a year ago
2023-11-25 5:05pm
v21
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a year ago
2023-11-25 3:13pm
v20
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a year ago
2023-11-25 2:20pm
v19
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a year ago
2023-11-24 11:05pm
v18
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a year ago
2023-11-24 9:28pm
v17
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a year ago
2023-11-24 9:27pm
v16
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a year ago
2023-11-24 6:56pm
v15
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a year ago
2023-11-24 6:26pm
v14
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a year ago
2023-11-24 5:44pm
v13
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a year ago
2023-11-24 11:40am
v7
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a year ago
2023-11-24 6:33am
v6
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a year ago
2023-11-24 6:09am
v5
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a year ago
2023-11-23 6:42pm
v4
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a year ago
2023-11-23 6:41pm
v3
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a year ago
2023-11-23 6:40pm
v2
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a year ago
2023-11-23 6:38pm
v1
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a year ago
v41

2023-11-26 10:45pm

Generated on Nov 26, 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
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Dataset Split

Train Set 98%
81Images
Valid Set 1%
1Images
Test Set 1%
1Images

Preprocessing

Auto-Orient: Applied

Augmentations

Outputs per training example: 3
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Rotation: Between -15° and +15°
Hue: Between -180° and +180°
Saturation: Between -25% and +25%
Brightness: Between -25% and +25%
Exposure: Between -20% and +20%
Blur: Up to 1.25px
Noise: Up to 5% of pixels
Mosaic: Applied
Bounding Box: Flip: Horizontal, Vertical

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