Dataset Versions

v5

2023-10-08 11:53am

Generated on Oct 8, 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 87%
6696Images
Valid Set 8%
652Images
Test Set 5%
364Images

Preprocessing

Auto-Orient: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Adaptive Equalization
Tile: 2 rows x 2 columns
Filter Null: Require at least 1% of images to contain annotations.

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
Rotation: Between -27° and +27°
Grayscale: Apply to 67% of images
Saturation: Between -59% and +59%
Brightness: Between -63% and +63%
Blur: Up to 1.75px
Noise: Up to 5% of pixels
Bounding Box: Brightness: Between -65% and +65%
Bounding Box: Blur: Up to 2.5px
Bounding Box: Noise: Up to 5% of pixels

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