Dataset Versions

v2

2024-01-31 7:24am

Generated on Jan 31, 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 82%
4542Images
Valid Set 12%
653Images
Test Set 6%
347Images

Preprocessing

Auto-Orient: Applied
Resize: Stretch to 320x160
Auto-Adjust Contrast: Using Adaptive Equalization
Grayscale: Applied
Tile: 2 rows x 2 columns
Filter Null: Require at least 54% of images to contain annotations.

Augmentations

Outputs per training example: 2
Hue: Between -15° and +15°
Saturation: Between -25% and +25%
Brightness: Between -15% and +15%
Exposure: Between -10% and +10%
Blur: Up to 2.5px
Noise: Up to 0.1% of pixels