Dataset Versions

Versions
2023-04-06 3:13pm
v60
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2 years ago
2023-04-06 3:13pm
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2023-04-06 3:13pm
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2023-04-06 3:12pm
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2023-04-06 3:11pm
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2023-04-06 3:10pm
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2023-04-06 3:09pm
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2023-04-06 3:08pm
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2023-04-06 3:07pm
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2023-04-06 3:06pm
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2023-04-06 3:03pm
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2023-04-06 3:01pm
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2023-04-06 3:00pm
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2023-04-06 2:59pm
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2023-04-06 2:59pm
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2023-04-06 2:58pm
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2023-04-06 2:57pm
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2023-04-06 2:57pm
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2023-04-06 2:56pm
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2023-04-06 2:56pm
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2023-04-06 2:55pm
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2023-04-06 2:54pm
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2023-04-06 2:54pm
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2023-03-31 9:57am
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2023-03-31 9:50am
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2023-03-31 9:49am
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2023-03-31 9:47am
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2023-03-31 9:46am
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2023-03-31 9:44am
v2
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2023-03-31 9:42am
v1
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2 years ago
v33

2023-04-06 2:55pm

Generated on Apr 6, 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 92%
479Images
Valid Set 8%
40Images
Test Set 0%
1Images

Preprocessing

No preprocessing steps were applied.

Augmentations

Outputs per training example: 3
Brightness: Between -29% and +29%