Dataset Versions

Versions
2023-06-29 7:14pm
v91
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a year ago
2023-06-28 3:37pm
v90
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a year ago
2023-06-27 5:53pm
v88
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2023-06-27 11:35am
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2023-06-20 3:21pm
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2023-06-19 11:39pm
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2023-06-13 9:37pm
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2023-06-13 4:26pm
v81
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2023-06-13 4:21pm
v80
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2023-06-12 7:44pm
v79
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2023-06-12 4:18pm
v78
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2023-06-09 10:16pm
v77
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2023-06-09 10:08pm
v76
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2023-06-09 8:52pm
v75
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2023-06-09 7:51pm
v74
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2023-06-09 7:43pm
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2023-06-08 7:56pm
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2023-06-08 6:21pm
v70
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2023-06-08 6:14pm
v69
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2023-06-08 6:05pm
v68
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2023-06-08 5:52pm
v67
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2023-06-08 5:46pm
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2023-06-08 5:40pm
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2023-06-08 5:31pm
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2023-06-08 5:03pm
v63
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2023-06-08 4:53pm
v62
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2023-06-08 4:04pm
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2023-06-08 3:29pm
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2023-06-08 3:14pm
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2023-06-08 2:40pm
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2023-06-08 1:02pm
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2023-06-08 12:38pm
v51
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2023-06-08 11:36am
v50
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2023-06-04 10:21pm
v40
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a year ago
2023-06-04 3:34pm
v39
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a year ago
2023-06-03 9:13pm
v38
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2023-06-03 8:55pm
v37
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2023-06-03 5:18pm
v36
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2023-06-02 10:19pm
v35
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2023-06-02 5:37pm
v34
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2023-06-01 11:00pm
v33
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2023-06-01 6:12pm
v32
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2023-06-01 3:15pm
v31
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2023-06-01 2:53pm
v30
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a year ago
2023-04-27 5:47pm
v29
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2 years ago
2023-04-16 6:29am
v28
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2 years ago
2023-04-16 9:52am
v27
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2 years ago
2023-04-15 11:01pm
v26
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2 years ago
2023-04-15 9:34pm
v25
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2 years ago
2023-04-15 8:58pm
v24
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2 years ago
2023-04-15 7:14pm
v23
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2 years ago
2023-04-15 2:18pm
v22
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2 years ago
2023-04-14 9:08pm
v21
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2 years ago
2023-04-13 10:04pm
v20
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2 years ago
2023-04-13 8:31pm
v19
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2 years ago
2023-04-12 9:41pm
v18
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2 years ago
2023-04-12 9:16pm
v17
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2 years ago
2023-04-12 8:46pm
v16
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2 years ago
2023-04-11 11:51pm
v15
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2 years ago
2023-03-31 5:48pm
v14
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2 years ago
2023-03-30 4:41pm
v13
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2 years ago
2023-03-29 9:20pm
v12
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2 years ago
2023-03-22 10:00pm
v1
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2 years ago
v40

2023-06-04 10:21pm

Generated on Jun 4, 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 87%
2750Images
Valid Set 8%
268Images
Test Set 4%
140Images

Preprocessing

Auto-Orient: Applied
Resize: Stretch to 640x640

Augmentations

Outputs per training example: 3
Rotation: Between -15° and +15°

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