Dataset Versions

v2

2024-10-07 10:56am

Generated on Oct 7, 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
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Dataset Split

Train Set 88%
2496Images
Valid Set 8%
240Images
Test Set 4%
116Images

Preprocessing

Auto-Orient: Applied
Isolate Objects: Applied
Static Crop: 0-100% Horizontal Region, 0-100% Vertical Region
Dynamic Crop: Class: defected
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Adaptive Equalization
Grayscale: Applied
Tile: 2 rows x 2 columns

Augmentations

Outputs per training example: 3
Flip: Horizontal
90° Rotate: Clockwise, Counter-Clockwise
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -45° and +45°
Shear: ±10° Horizontal, ±10° Vertical
Hue: Between -12° and +12°
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
Mosaic: Applied
Bounding Box: Flip: Horizontal
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Bounding Box: Crop: 0% Minimum Zoom, 22% Maximum Zoom
Bounding Box: Rotation: Between -45° and +45°
Bounding Box: Shear: ±10° Horizontal, ±10° Vertical
Bounding Box: Brightness: Between -15% and +15%
Bounding Box: Exposure: Between -99% and +99%
Bounding Box: Blur: Up to 2.5px
Bounding Box: Noise: Up to 0.1% of pixels

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