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insan

Object Detection

insan Image Dataset

v7

2024-03-22 1:41pm

Generated on Mar 22, 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.
CreateML JSON
CreateML JSON format is used with Apple's CreateML and Turi Create tools.
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Dataset Split

Train Set 84%
216Images
Valid Set 9%
24Images
Test Set 6%
16Images

Preprocessing

Auto-Orient: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Dynamic Crop: Class: domuz
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Adaptive Equalization
Tile: 2 rows x 2 columns

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise
Rotation: Between -15° and +15°
Shear: ±10° Horizontal, ±10° Vertical
Grayscale: Apply to 15% of images
Saturation: Between -31% and +31%
Brightness: Between -15% and +15%
Blur: Up to 2.5px
Noise: Up to 0.1% of pixels
Mosaic: Applied
Bounding Box: Flip: Horizontal
Bounding Box: Blur: Up to 2.5px