NTU

cpl-firstSector

Object Detection

cpl-firstSector Image Dataset

v3

2024-04-28 12:12am

Generated on Apr 27, 2024

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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.
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Dataset Split

Train Set 80%
372Images
Valid Set 7%
31Images
Test Set 13%
62Images

Preprocessing

Auto-Orient: Applied
Resize: Stretch to 640x640
Filter Null: Require all images to contain annotations.

Augmentations

Outputs per training example: 3
Rotation: Between -15° and +15°
Shear: ±10° Horizontal, ±10° Vertical
Brightness: Between -25% and +25%
Exposure: Between -15% and +15%
Blur: Up to 1.5px
Noise: Up to 0.5% of pixels
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