Dataset Versions

v3

2024-12-11 1:19pm

Generated on Dec 11, 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
Choose another format.

Dataset Split

Train Set 88%
2517Images
Valid Set 8%
227Images
Test Set 4%
126Images

Preprocessing

Auto-Orient: Applied
Static Crop: 19-74% Horizontal Region, 7-79% Vertical Region
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Adaptive Equalization
Grayscale: Applied
Tile: 3 rows x 3 columns
Filter Null: Require all images to contain annotations.

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Rotation: Between -10° and +10°
Shear: ±12° Horizontal, ±11° Vertical
Grayscale: Apply to 18% of images
Hue: Between -10° and +10°
Saturation: Between -29% and +29%
Brightness: Between -12% and +12%
Exposure: Between -13% and +13%
Blur: Up to 2.2px
Noise: Up to 1.76% of pixels
Bounding Box: Rotation: Between -12° and +12°
Bounding Box: Shear: ±6° Horizontal, ±7° Vertical
Bounding Box: Brightness: Between -17% and +17%
Bounding Box: Exposure: Between -10% and +10%
Bounding Box: Blur: Up to 2px
Bounding Box: Noise: Up to 0.74% of pixels