Dataset Versions

Versions
2024-11-08 9:54am
v28
·
14 days ago
2023-11-13 6:13pm
v27
·
a year ago
2023-11-13 6:13pm
v26
·
a year ago
2023-11-13 6:08pm
v25
·
a year ago
2023-11-13 6:06pm
v24
·
a year ago
2023-11-13 4:28pm
v23
·
a year ago
2023-11-13 1:36pm
v22
·
a year ago
2023-11-13 1:31pm
v20
·
a year ago
2023-11-10 5:29pm
v19
·
a year ago
2023-11-10 5:08pm
v18
·
a year ago
2023-11-10 12:24pm
v17
·
a year ago
2023-11-10 12:23pm
v16
·
a year ago
2023-11-10 12:13pm
v15
·
a year ago
2023-11-10 9:32am
v12
·
a year ago
2023-11-10 9:02am
v10
·
a year ago
2023-11-09 7:17am
v9
·
a year ago
2023-11-09 7:06am
v8
·
a year ago
2023-11-09 10:47am
v7
·
a year ago
2023-11-09 10:24am
v6
·
a year ago
2023-11-08 9:55pm
v5
·
a year ago
2023-11-08 9:35pm
v4
·
a year ago
2023-11-08 9:24pm
v3
·
a year ago
2023-11-08 11:58am
v2
·
a year ago
2023-11-08 11:56am
v1
·
a year ago
v22

2023-11-13 1:36pm

Generated on Nov 13, 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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730 Total Images

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Dataset Split

Train Set 90%
657Images
Valid Set 10%
73Images
Test Set %
0Images

Preprocessing

Resize: Stretch to 224x224

Augmentations

Outputs per training example: 3
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Saturation: Between -25% and +25%
Brightness: Between -5% and +5%
Blur: Up to 1px

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