Dataset Versions

v1

2024-11-20 4:43am

Generated on Nov 19, 2024

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
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Dataset Split

Train Set 88%
17568Images
Valid Set 8%
1644Images
Test Set 4%
830Images

Preprocessing

Auto-Orient: Applied
Isolate Objects: Applied
Resize: Fit (reflect edges) in 640x640
Auto-Adjust Contrast: Using Adaptive Equalization
Modify Classes: 20 remapped, 0 dropped
Filter Null: Require all images to contain annotations.

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Crop: 0% Minimum Zoom, 13% Maximum Zoom
Hue: Between -11° and +11°
Saturation: Between -23% and +23%
Brightness: Between -22% and +22%
Exposure: Between -14% and +14%
Blur: Up to 4.2px
Noise: Up to 1.92% of pixels
Cutout: 1 boxes with 15% size each
Bounding Box: Flip: Horizontal, Vertical
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Bounding Box: Crop: 0% Minimum Zoom, 13% Maximum Zoom
Bounding Box: Brightness: Between -22% and +22%
Bounding Box: Exposure: Between -14% and +14%
Bounding Box: Blur: Up to 4.2px
Bounding Box: Noise: Up to 1.92% of pixels

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