Dataset Versions

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Versions
2023-10-26 5:25pm
v13
·
a year ago
2023-09-11 3:08pm
v12
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a year ago
2023-08-28 3:22pm
v11
·
a year ago
2023-08-25 8:46pm
v10
·
a year ago
2023-07-14 9:41pm
v8
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a year ago
2023-07-14 9:34pm
v7
·
a year ago
2023-07-09 12:52am
v6
·
a year ago
2023-07-07 4:57pm
v5
·
a year ago
2023-07-07 4:47pm
v4
·
a year ago
2023-05-10 9:20am
v3
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2 years ago
2023-05-10 9:18am
v2
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2 years ago
2023-05-10 9:17am
v1
·
2 years ago
v10

2023-08-25 8:46pm

Generated on Aug 25, 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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106 Total Images

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Dataset Split

Train Set 81%
86Images
Valid Set 8%
9Images
Test Set 10%
11Images

Preprocessing

No preprocessing steps were applied.

Augmentations

Outputs per training example: 2
Flip: Horizontal
90° Rotate: Clockwise, Counter-Clockwise
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Shear: ±15° Horizontal, ±15° Vertical
Blur: Up to 2.5px
Mosaic: Applied
Bounding Box: Flip: Horizontal
Bounding Box: Crop: 0% Minimum Zoom, 20% Maximum Zoom
Bounding Box: Rotation: Between -15° and +15°
Bounding Box: Shear: ±15° Horizontal, ±15° Vertical
Bounding Box: Brightness: Between -25% and +25%
Bounding Box: Noise: Up to 5% of pixels

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