Dataset Versions

v1

2024-08-08 9:06pm

Generated on Aug 8, 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.
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Dataset Split

Train Set 85%
6852Images
Valid Set 12%
940Images
Test Set 4%
284Images

Preprocessing

Auto-Orient: Applied
Isolate Objects: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Dynamic Crop: Class: Adulto
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Contrast Stretching
Grayscale: Applied
Tile: 2 rows x 2 columns

Augmentations

Outputs per training example: 3
90° Rotate: Clockwise, Counter-Clockwise
Crop: 0% Minimum Zoom, 21% Maximum Zoom
Rotation: Between -15° and +15°
Shear: ±27° Horizontal, ±6° Vertical
Grayscale: Apply to 20% of images
Saturation: Between -30% and +30%
Exposure: Between -10% and +10%
Blur: Up to 2.5px
Noise: Up to 1.41% of pixels
Mosaic: Applied
Bounding Box: Flip: Horizontal
Bounding Box: Crop: 0% Minimum Zoom, 20% Maximum Zoom
Bounding Box: Rotation: Between -15° and +15°
Bounding Box: Shear: ±10° Horizontal, ±10° Vertical
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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