Dataset Versions

v2

2024-11-05 5:38pm

Generated on Nov 5, 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 87%
192Images
Valid Set 8%
18Images
Test Set 5%
10Images

Preprocessing

Auto-Orient: Applied
Dynamic Crop: Class: KTP
Resize: Stretch to 640x640
Grayscale: Applied
Auto-Adjust Contrast: Using Adaptive Equalization
Filter Null: Require all images to contain annotations.

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -15° and +15°
Grayscale: Apply to 15% of images
Hue: Between -15° and +15°
Saturation: Between -15% and +15%
Brightness: Between -15% and +15%
Exposure: Between -15% and +15%
Blur: Up to 2.5px
Noise: Up to 0.1% of pixels
Bounding Box: Flip: Horizontal, Vertical
Bounding Box: Rotation: Between -10° and +10°
Bounding Box: Brightness: Between -10% and +10%
Bounding Box: Exposure: Between -10% and +10%
Bounding Box: Blur: Up to 2.5px
Bounding Box: Noise: Up to 0.1% of pixels

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