Dataset Versions

Versions
2023-07-06 10:33am
v14
·
a year ago
2023-07-05 9:00pm
v13
·
a year ago
2023-06-27 8:54am
v12
·
a year ago
2023-06-23 9:35am
v11
·
a year ago
2023-06-22 1:55am
v10
·
a year ago
2023-06-22 1:09am
v9
·
a year ago
2023-06-22 1:07am
v8
·
a year ago
2023-06-22 12:30am
v4
·
a year ago
2023-06-22 12:22am
v3
·
a year ago
2023-06-22 12:16am
v2
·
a year ago
2023-06-20 12:33pm
v1
·
a year ago
v8

2023-06-22 1:07am

Generated on Jun 22, 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.
CreateML JSON
CreateML JSON format is used with Apple's CreateML and Turi Create tools.
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188 Total Images

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Dataset Split

Train Set 90%
170Images
Valid Set 4%
7Images
Test Set 6%
11Images

Preprocessing

Auto-Orient: Applied
Isolate Objects: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Grayscale: Applied
Tile: 2 rows x 2 columns
Filter Null: Require all images to contain annotations.

Augmentations

Outputs per training example: 2
Rotation: Between -17° and +17°
Grayscale: Apply to 25% of images
Hue: Between -109° and +109°
Saturation: Between -41% and +41%
Noise: Up to 5% of pixels
Mosaic: Applied
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise
Bounding Box: Crop: 0% Minimum Zoom, 20% Maximum Zoom
Bounding Box: Shear: ±15° Horizontal, ±15° Vertical
Bounding Box: Blur: Up to 2.5px

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