Dataset Versions

v1

2022-05-23 10:00pm

Generated on May 23, 2022

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%
1436Images
Valid Set 8%
127Images
Test Set 4%
73Images

Preprocessing

Auto-Orient: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Resize: Stretch to 720x720
Tile: 1 rows x 1 columns
Filter Null: Require at least 80% of images to contain annotations.

Augmentations

Outputs per training example: 3
Flip: Horizontal
90° Rotate: Clockwise, Counter-Clockwise
Crop: 0% Minimum Zoom, 10% Maximum Zoom
Grayscale: Apply to 25% of images
Saturation: Between -10% and +10%
Brightness: Between -10% and +10%
Exposure: Between -15% and +15%
Blur: Up to 5px
Noise: Up to 1% of pixels
Mosaic: Applied
Bounding Box: Brightness: Between -3% and +3%
Bounding Box: Exposure: Between -5% and +5%
Bounding Box: Blur: Up to 2px
Bounding Box: Noise: Up to 1% of pixels

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