Dataset Versions

v2

2023-10-28 7:40pm

Generated on Oct 28, 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 93%
10440Images
Valid Set 6%
696Images
Test Set 1%
124Images

Preprocessing

Auto-Orient: Applied
Isolate Objects: Applied
Static Crop: 31-75% Horizontal Region, 0-41% Vertical Region
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Adaptive Equalization
Grayscale: Applied
Tile: 2 rows x 2 columns
Filter Null: Require at least 52% of images to contain annotations.

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
Shear: ±15° Horizontal, ±24° Vertical
Grayscale: Apply to 25% of images
Hue: Between -134° and +134°
Brightness: Between -53% and +53%
Blur: Up to 3.75px
Noise: Up to 9% of pixels
Cutout: 18 boxes with 10% size each
Mosaic: Applied
Bounding Box: Shear: ±15° Horizontal, ±15° Vertical
Bounding Box: Brightness: Between -25% and +25%
Bounding Box: Noise: Up to 5% of pixels